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The sliding mode control (SMC) strategy based on genetic algorithm is proposed for discrete two‐dimensional (2‐D) Markov switching systems with the Roesser model. By means of common 2‐D sliding surface, the 2‐D SMC law is designed for the underlying system. According to Lyapunov stability criteria, sufficient conditions are established for the asymptotic mean‐square stability of the underlying 2‐D Markov switching systems and the reachability of the sliding region is guaranteed. Utilizing an iteration optimizing algorithm, an effective SMC strategy under genetic algorithm is constructed to minimize the sliding region by searching an ideal sliding gain. Finally, the applicability of the proposed 2‐D SMC strategy is verified through an example. [ABSTRACT FROM AUTHOR]

Aiming at resolving trajectory tracking control challenges during high‐speed lane changes in intelligent driving vehicles, an innovative fractional‐order sliding mode control approach is introduced in the present study. The control strategy comprises upper and lower‐level controls. First, the upper‐level control designs the vehicle trajectory tracking controller, integrating a non‐singular terminal sliding mode (NTSM) surface with a fractional‐order fast super‐twisted sliding mode control (FOF‐STSMC) algorithm. The NTSM surface properties ensure rapid convergence of the system tracking error to zero within a finite time, while the fractional‐order control extends the control system's regulation range and enhances algorithm flexibility. Additionally, the integration with the super‐twisting algorithm effectively mitigates oscillation issues in the control input, achieving a smooth input. Second, the lower‐level control aims to enhance vehicle driving stability. Utilizing the reference yaw rate, and sideslip angle and accounting for tire force saturation, a fractional‐order sliding mode control (FOSMC) algorithm is developed to compute the external yaw moment. Through dynamic load allocation, considering the vertical load for each tire, intelligent external yaw moment distribution significantly improves vehicle stability. Finally, the results of the Carsim–Simulink co‐simulation demonstrate that, compared to the STSMC strategy, the FOSMC strategy with front‐wheel‐only steering, and the linear quadratic regulator (LQR) control strategy, the proposed control strategy in this paper reduces the tracking error by 77%, 61%, and 58%, respectively, achieving more precise and stable trajectory tracking under high‐speed conditions. [ABSTRACT FROM AUTHOR]

This paper introduces an innovative adaptive fixed‐time sliding mode control (SMC) method that eliminates chattering, enhancing trajectory tracking accuracy and robustness in nonlinear dynamical systems facing uncertainties and external disturbances. The proposed control scheme ensures fixed‐time convergence of system states to a predefined neighborhood around the origin, independent of initial conditions. An innovative adaptive tuning law is proposed to estimate the unknown upper bounds of synthetic uncertainties and disturbances without requiring prior knowledge. This law forces system states to trend to the sliding surface within a fixed time, achieving stabilization of tracking errors at the origin without undesirable chattering and while avoiding singularities. Comprehensive simulations and comparisons among four control strategies (C1, C2, C3, and C4) demonstrate that the proposed C1 control strategy outperforms others in terms of faster convergence speed, higher tracking accuracy, less chattering, and stronger robustness. [ABSTRACT FROM AUTHOR]

This article investigates anti‐attack stabilization with passivity problem of uncertain singular semi‐Markov jump systems (singular S‐MJSs) with exogenous disturbance and delay. An ingenious non‐fragile observer‐based neural sliding mode control (SMC) scheme is put forward to solve the problem. First, considering unmeasured states, a distinctive non‐fragile and decoupled observer, which does not contain the control input or any auxiliary sliding mode compensator design as in existing observer‐based SMC approaches, is established such that the disadvantages of sliding mode switching in observers in existing literature can be avoided. Then, "only one sliding surface" design and a new system analysis route are presented, and the derived sliding surface is accessibly designed. Next, a new version of stochastic admissibility and passivity sufficient condition is given, and a related algorithm via an optimization problem is proposed to determine the controller gain and the observer gain by linear matrix inequalities (LMIs). Further, a novel observer‐based anti‐attack neural SMC law, which utilizes a neural network‐based approach to approximate actuator attack, is proposed to stabilize the singular S‐MJSs against actuator attack. Finally, simulation and comparison results are presented, which demonstrate the effectiveness and superiority of our method. [ABSTRACT FROM AUTHOR]

This article proposes a second‐order discrete‐time sliding mode controller (DSMC) by only using sampled‐data information of the system output. On one hand, different from the continuous‐time sliding mode control, the finite‐time stability of the closed‐loop system under DSMC is usually not kept due to the limited sampling frequency. On the other hand, in the output feedback framework, the second‐order sliding mode observer cannot independently estimate the internal state of the system if there exist unknown mismatched term and unknown time‐varying coefficient of the control input. To solve the above problems, a joint design strategy of second‐order discrete‐time sliding mode observer and sliding mode controller based on the "non‐separation principle" is proposed. The stability and robustness of the closed‐loop system is analyzed based on the Lyapunov design method. Finally, simulation example verifies the correctness of the theory. [ABSTRACT FROM AUTHOR]

This paper proposes a distributed consensus algorithm in predefined time of time‐varying optimization with inequality constrains for multi‐agent systems (MASs) with external disturbances over an undirected graph. Firstly, by utilizing exponential function, a novel criterion with respect to the stability in predefined time is developed for the nonlinear systems. Secondly, a new distributed switching control protocol, which can inhibit the external unbounded disturbances, is piecewise designed to drive the states of agents to the sliding mode surface via the predefined‐time set by users. Subsequently, under the designed event‐triggered controller (ETC), the states of agents achieve consensus in predefined time on the sliding mode surface. Meanwhile, with the help of log barrier function, the consensus states of agents reach the feasible region and converge to the optimal solution in predefined time. Finally, the correctness and availability of the proposed optimization control algorithm are verified by a simulation example. [ABSTRACT FROM AUTHOR]

In this article, a neuroadaptive sliding mode control (NSMC) strategy based on recurrent neural network (RNN) for robustly and adaptively tracking the desired position and attitude of an uncertain tilting quadrotor unmanned aerial vehicle (TQUAV) with unknown controllers is presented. The main contribution of this article is the real‐time adjustment of unknown flight controllers using the approximation characteristics of RNN, in which the derived approximation errors of RNN are sufficiently estimated by adaptive control method that can reduce or eliminate the impact of error terms on the evolution of closed‐loop systems. Especially, Lyapunov stability analysis is greatly simplified compared to existing methods and does not require amplification or reduction. Finally, the superior performance of the NSMC strategy was verified by comparing simulation results. [ABSTRACT FROM AUTHOR]

In this article, the sliding mode control (SMC) of fractional nonlinear systems (FNSs) with disturbances di(t)$$ {d}_i(t) $$ is studied. First, a useful fractional power‐rate inequality DαV(x(t))≤−μVβ(x(t))$$ {D}^{\alpha }V\left(x(t)\right)\le -\mu {V}^{\beta}\left(x(t)\right) $$ for β∈(0,1)$$ \beta \in \left(0,1\right) $$ is extended to a more general form β>0$$ \beta >0 $$. Based on the generalized inequality, the method of a modified fractional integral SMC is completed, in which the parameter of the symbolic function is extended to ς>1/2$$ \varsigma >1/2 $$ and γ>1/2$$ \gamma >1/2 $$. This increases the degree of freedom of the sliding mode surface (SMS). Then, the SMC of FNSs is studied for the cases of known and unknown disturbances. In the case of known disturbance, it is proved by the generalized inequality and quadratic Lyapunov function method that the state of the FNSs can converge asymptotically to zero on the SMS. For the case of unknown disturbance, a fractional disturbance observer is used to estimate the disturbance by introducing auxiliary variables zi(t)=di(t)−δxi(t)$$ {z}_i(t)={d}_i(t)-\delta {x}_i(t) $$. The disturbance estimation error d˜i(t)$$ {\tilde{d}}_i(t) $$ of the proposed FNSs is proved to be bounded. An equivalent global control law is obtained and asymptotic convergence of the FNSs under the action of the controller is proved. Finally, two numerical simulation examples are given to verify the feasibility of the method proposed in this article. [ABSTRACT FROM AUTHOR]

As a significant type of dynamic systems, switched systems have been successfully applied to the construction of many engineering fields. Recently, the studies of networked switched control systems have received a lot of attention. However, the intervention of the network often causes the delay or packet loss during data transmission, resulting in incomplete data transmission. The paper studies a sliding mode observer design for above‐mentioned systems with external disturbance under an imperfect transmission communication link. By constructing a dynamic event generator, a dynamic event‐triggered mechanism between the event‐generator and controller is developed to save additional network bandwidth and improve system performance. A desirable sliding surface function is built to solve the complexity of system analysis problems caused by network‐induced delay and packet‐dropout‐induced imperfect transmission. Then, a corresponding event‐based integral‐type sliding mode observer is constructed to estimate inaccessible system states, guaranteeing the reachability of the sliding surface. Based on the augmented system dynamics, sufficient conditions are derived to guarantee exponent stability with a weighted ℒ2$$ {\mathcal{L}}_2 $$‐ℒ∞$$ {\mathcal{L}}_{\infty } $$ performance level. Finally, two simulations are presented to demonstrate the feasibility and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This article introduces a control method for trajectory tracking of underactuated unmanned marine vehicles (UMVs), employing the sliding mode predictive control (SMPC) scheme. To address the challenges of demonstrating system stability with a local feedback controller for underactuated UMVs in model predictive control (MPC), this article proposes an auxiliary controller design method based on sliding mode control. A sliding mode dynamic is derived through an error system and sliding surface equations. Compared to existing literature, which predominantly emphasizes demonstrating input‐state stability, this strategy ensures the asymptotic stability of the closed‐loop system by introducing a novel method for selecting weight matrices. Furthermore, extended terminal sets and feasible sets constructed via sliding variables are provided, thereby reducing conservatism. Ultimately, the SMPC scheme is validated through simulation and hardware experiments providing quantitative evidence of its effectiveness in real‐world applications. [ABSTRACT FROM AUTHOR]

Research on the motion control of overhead cranes, constrained by underactuated characteristics, helps improve the efficiency of payload transportation. Most studies require all system state variables (trolley displacement, payload swing angle, and their velocities). In practice, sensors measure and transmit these variables, but noise affects their accuracy, reducing control performance. Additionally, uncertainties in crane parameters, unmodeled friction, and unknown disturbances threaten the system's stability. Traditional methods struggle to address these issues effectively. To address these challenges, this article proposes an adaptive discrete sliding mode control (DSMC) method with a Kalman filter. By extending the state system and considering disturbances as new variables, the Kalman filter effectively eliminates signal noise, accurately estimates disturbances, and estimates system states simultaneously. The proposed method incorporates disturbance compensators into the adaptive DSMC, utilizing exponential terms to suppress oscillations caused by excessively high or low control gains, thus increasing control speed. Experimental comparisons demonstrate the superiority and robustness of the proposed control method under various disturbance conditions. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper proposes a novel integrated guidance and control (IGC) scheme for a bank‐to‐turn (BTT) hypersonic vehicle (HV) in the dive phase with multi‐constraints, input saturation, and complex uncertainties. In the guidance loop, the presence of the terminal impact angle constraints may cause severe saturation of the attack angle, which may lead to the failure of the mission. Motivated by this issue, a range‐varying sliding mode surface is constructed, of which the core is a novel line‐of‐sight (LOS) angle error shaping strategy that drives the LOS angle errors to converge along the prescribed performance functions. On this basis, a range‐based prescribed performance function is designed to portray a practical saturation‐alleviation convergence characteristic of the LOS angle errors. In the control loop, the barrier Lyapunov function (BLF) and barrier function (BF)‐based adaptive law are incorporated to restrict the states within proper regions in the presence of uncertainties. Additionally, an auxiliary system is constructed to deal with the adverse affect caused by input saturation. The stability of the closed‐loop system is proved by the Lyapunov stability theory. Finally, the effectiveness and robustness of the proposed IGC scheme are verified through numerical simulations. [ABSTRACT FROM AUTHOR]

This paper presents a fixed‐time state observer‐based robust adaptive neural fault‐tolerant control (RANFTC) for attitude and altitude tracking and control of quadrotor unmanned aerial vehicles (UAVs), considering multiple actuator faults, parametric uncertainty, and unknown external disturbances simultaneously. A novel fixed‐time state error estimation based on sliding mode observer is designed, which is independent of initial conditions. A proportional–integral–derivative (PID) based sliding mode control (SMC) is proposed to handle actuator faults and unknown disturbances in combination with the fixed‐time observer within the fault‐tolerant control (FTC) design scheme. The radial basis function neural network (RBFNN) is employed with the controller to approximate the uncertain parameters of the system. Furthermore, two new adaptive laws are designed to estimate the sudden actuator fault and the unknown upper bound of disturbances independently. Implementing these estimation schemes avoids overestimation, enhances the robustness of the presented controller, and substantially eliminates the control chattering problem. By applying the Lyapunov stability concept, the suggested control strategy guarantees that the states of the quadrotor UAV converge to the origin in a finite time. Finally, simulation studies are conducted to demonstrate the tracking performance and highlight the effectiveness of the proposed FTC design compared to the existing FTC methods. [ABSTRACT FROM AUTHOR]

ABSTRACT For a class of continuous‐time non‐linear systems with saturated input and unknown non‐linear disturbance, a novel event‐triggered integral reinforcement learning (IRL) control strategy based on recursive terminal sliding mode (RTSM) is proposed in this paper. Firstly, a novel performance index function is designed based on RTSM and a two‐player zero‐sum game, and the robust control problem with saturated input and unknown disturbance can be transformed into an optimal control problem. To avoid the requirement of drift dynamics, the IRL technique is introduced. Secondly, a critic neural network is used to approximate the optimal value function, which not only simplifies algorithm implementation structure, but also relaxes initial admissible control in the learning of neural network weights. Then, considering the event‐triggered mechanism, the asymptotic stability of the closed‐loop system and the uniformly ultimately boundedness of weight estimation errors are proved by utilizing the Lyapunov theory. Finally, simulation results illustrate the effectiveness of the proposed control method. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive study of dynamics identification‐driven diving control for unmanned underwater vehicles (UUVs). Initially, a diving dynamics model of UUVs is established, serving as the foundation for the development of subsequent algorithms. A noise‐reduction least squares (NRLS) algorithm is then derived for parameter identification, demonstrating convergence under measurement noise from a probabilistic perspective. A notable feature of this algorithm is its skill in correcting raw data, thereby improving parameter identification accuracy. Based on the identified model, an improved fast terminal sliding mode control (FTSMC) algorithm is introduced for diving control, consistently ensuring rapid convergence under 16 scenarios. Importantly, the proposed diving control algorithm effectively mitigates chattering by incorporating a dedicated filter, adaptively adjusting the switching gain, and substituting saturation function for sign function. Through experimental validation, the NRLS algorithm's advantage over the traditional least squares method becomes evident, with depth errors consistently below 3.5 cm. This indicates that the identified model closely aligns with the actual model, showcasing a commendable fit. Additionally, when compared to the traditional sliding mode controller and the proportional‐integral‐derivative algorithm, the FTSMC algorithm has superior performance, as indicated by a mean absolute percentage error consistently below 4%. [ABSTRACT FROM AUTHOR]

ABSTRACT A fixed‐time nonsingular terminal sliding mode control (TSMC) method based on emotional neural network (ENN) is proposed for nonlinear systems. First of all, a new terminal sliding surface (TSS) is proposed in this article, which can adaptively adjust when the system states are far and near the origin and achieve fixed time fast convergence. Second, the equivalent control term in the controller is approximated by the ENN, which solves the singularity problem of traditional TSMC and the problem of unknown model information simultaneously. Finally, by using Lyapunov stability theorem, it is proved that the system states are stable in a fixed time during both sliding and reaching stages, which is independent of the initial values. The proposed method is verified and compared on an inverted pendulum system, which shows a better control performance. [ABSTRACT FROM AUTHOR]

ABSTRACT Measuring element is always accompanied by uncertainty disturbances and multiple faults during the long time operation of industrial system in complex environment such as blade and pitch system of floating wind turbines. Timely detection of the fault and fault‐tolerant control (FTC) perform a significant part in ensuring the stable operation of the system and saving maintenance fees. Sliding mode control is extensively applied to FTC because of its good robustness. Therefore, a sliding mode controller is constructed to guarantee the stability of the industrial plant which suffers multiple faults and uncertain disturbances. At the same time, most existing literature does not take into account several faults and uncertain disturbances. Firstly, employing generalized sliding mode method, we devise a sliding mode observer for evaluating state vector, actuator fault and sensor fault of the system. Secondly, according to the state estimation, we construct a sliding mode controller and prove its validity by Lyapunov's theorem. Our controller achieves satisfactory performance, and it is easier to be implemented in practical engineering than other controllers. Finally, we establish a SIMULINK model of blade and pitch system and make simulation experiments. Simulation outcomes validate the availability and practicability of our controller, which also provides a general scheme for fault estimation and FTC of other industrial plants. [ABSTRACT FROM AUTHOR]

ABSTRACT In this paper, a Lyapunov‐like sufficient condition for the fast fixed‐time stability of autonomous systems is proposed. The proposed fast fixed‐time stability theorem ensures a smaller upper bound on the convergence time than the existing fixed‐time stability theorems. The fixed‐time sliding mode controls require switching from the fixed‐time sliding surface to the general sliding surface in the vicinity of the origin to avoid non‐differentiability at that point. It is demonstrated that the switching method converges the system states either to a residual set around the equilibrium point or directly to the equilibrium point, depending on the tuning parameter settings. To address this issue, a new nonsingular sliding surface is proposed based on the fast fixed‐time stability theorem. This approach ensures singularity‐free convergence of the system states to the equilibrium point without additional switching logic for the sliding surfaces or any constraints on tuning parameters. Furthermore, a novel continuous adaptive fast fixed‐time sliding mode control (AFFTSMC) law is proposed for attitude control of a satellite in the presence of the satellite inertia uncertainty and unknown upper‐bounded external disturbance torques. The proposed AFFTSMC law ensures chattering‐free and singularity‐free satellite attitude control. Simulation results are presented for both rest‐to‐rest and tracking attitude maneuvers of a satellite, demonstrating the superiority of the proposed controller. [ABSTRACT FROM AUTHOR]

ABSTRACT This article investigates the issue of finite‐time tracking control for uncertain robotic manipulator systems with unknown actuator faults and shifting loads based upon a fuzzy sliding mode control strategy. A novel fuzzy adaptive sliding mode fault‐tolerant control law is synthesized, where a fuzzy approximation algorithm is utilized to fit the unknown plant parameters, potential disturbances, and relational actuator faults, and the corresponding adaptive robust term is designed to estimate the unidentified boundary of the estimated errors, and the boundedness of all the relevant design parameters of the manipulator systems is ensured combining with the average dwell time mechanism of switched system control theory. Furthermore, the reachability of the pre‐devised sliding surface and the finite‐time convergence of tracking error are achieved under the presented controller design. Ultimately, simulation results exhibit the feasibility and superiority of the proposed algorithm. [ABSTRACT FROM AUTHOR]

ABSTRACT The quasi‐Z‐source cascaded multilevel inverter (qZS‐CMI) can achieve the boost function through the shoot‐through state without the requirement of an additional DC boost circuit. Thus, the efficiency of the system is improved, and each power module can be controlled independently, which makes it more suitable for distributed photovoltaic power generation systems. This paper proposes a multi‐carrier phase‐shifted PWM (MPSPWM) that inserts a shoot‐through signal at the switching moment, in order to address the high switching frequency problem caused by simple boost modulation in qZS‐CMI. In order to improve the dynamic response of the system and reduce the grid‐connected current distortion of qZS‐CMI, this paper proposes a master‐division grid‐connected control strategy. The DC‐link voltage division controllers use the sliding mode control to achieve DC‐link voltage stabilization, and the grid‐connected current master controller adopts an improved deadbeat control to achieve fast tracking of grid‐connected current. When the output power of PV arrays is inconsistent, the differential power allocation between modules is realized by setting the module power allocation factor. Finally, the effectiveness and feasibility of the above theory are verified by three‐module cascaded qZS‐CMI simulation and experiment. [ABSTRACT FROM AUTHOR]

ABSTRACT The paper proposes a novel model‐free adaptive robust controller for load frequency control in multi‐area interconnected power systems. The controller combines model‐free control based on a nonlinear disturbance observer (NDOB) and adaptive integral sliding mode control. The main aim of the controller is to maintain the power system frequency close to the nominal value and achieve a balanced power exchange between tie‐lines, considering the system's nonlinearities and disturbances. The proposed controller comprises four components. First, model‐free intelligent PID control is implemented to overcome the complexity of the current controller, introduce the required dynamics, and reduce higher‐order output derivatives. Second, a nonlinear disturbance observer is utilized to estimate the system dynamics considering uncertainties and load fluctuations. Third, fast convergence is achieved by employing an integral sliding surface. Finally, an adaptation gain dynamic is used to achieve high accuracy. The advantage of the proposed model‐free adaptive robust controller lies in its simple structure and ease of regulation. The closed‐loop system's stability and finite‐time convergence are examined using Lyapunov stability theory. A comparison with recently published papers is conducted to validate the proposed controller's effectiveness. Additionally, robustness testing of the proposed method is performed in different scenarios. [ABSTRACT FROM AUTHOR]

ABSTRACT The current contribution introduces a nonsingular fixed‐time sliding mode control (SMC) scheme for position and velocity tracking of robot manipulators. The approach avoids singularities by introducing a new sliding surface with the special attribute that the exponent employed to achieve fixed time convergence depends on the tracking error and is smaller than one except when the error is exactly zero, whereas the exponent becomes one at zero, which makes the derivative at zero to be well defined. A new theoretical result has been introduced in the form of a lemma to prove this innovative property. Furthermore, model uncertainties are handled by means of a time‐varying gain given by a polynomial of the powers of the norms of the tracking and velocity errors. The fixed‐time convergence is proven employing Lyapunov theory, and the result holds globally. Simulation outcomes confirm the developed theory, and the advantages of the proposed scheme are shown qualitatively by comparing its performance with well‐known equivalent control schemes. [ABSTRACT FROM AUTHOR]

ABSTRACT Real‐world dynamical controlled systems are often subject to input saturation due to the physical constraints of actuators. This causes the response performance of the system to be degraded. To this end, we propose a high‐performance bounded finite time control (HP‐BFTC) method based on sliding mode control for finite time tracking of linear systems with input saturation. In this method, a novel concept of rate regulation finite‐time stability is proposed to achieve better steady‐state performance. A bounded controller based on sliding mode control is proposed to achieve finite‐time stability in rate regulation, wherein a finite time approach rate based on an inverse tangent function is presented to alleviate chattering caused by sign function, and two control parameters are introduced to improve response performance. The rate regulation finite‐time stability of the system is proved in the estimated domain of attraction. In addition, a parameter tuning principle is given to enhance the response performance of the closed‐loop system in transient and steady state. The superiority of the proposed method in performance is verified by a case study. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper proposes a robust discrete‐time integral fast terminal sliding mode predictive control (DIFTSMPC) scheme for DP ship trajectory tracking under the consideration of unmodeled dynamics, environmental disturbance, and input constraints. An improved single closed‐loop control strategy is designed by adopting the earth‐fixed reference velocity as the virtual velocity. The improved nonlinear PID discrete‐time integral fast terminal sliding mode is designed to achieve faster convergence. The unknown nonlinear dynamics and the environmental disturbance are combined as a lumped uncertainty term and estimated using the one‐step delay observation method. Then the corrected sliding model state is optimized to track the reference sliding reaching law in the prediction horizon. The lumped uncertainty estimation is integrated into the sliding mode prediction to guarantee the robustness of the control scheme. The stability of the proposed scheme has been verified. Comparison results demonstrate the effectiveness and superiority in chattering suppressing and constraint handling of the proposed scheme. [ABSTRACT FROM AUTHOR]

ABSTRACT In this paper, the dynamic event‐triggered robust optimal consensus control problem is investigated for nonlinear multi‐agent systems (MASs) with matched and mismatched disturbances via integral sliding mode (ISM) control and the adaptive dynamic programming (ADP) algorithm. First, a dynamic event‐triggered fixed‐time ISM controller is designed to guarantee that the system state converges to the predefined ISM manifold, thereby eliminating the matched disturbances. Next, the consensus control problem is transformed into an optimal control problem by constructing neighborhood error dynamics and a new modified cost function; thus, an event‐triggered‐based coupled Hamilton‐Jacobi‐Bellman equation (HJBE) is established. Then, an ADP‐based single‐critic neural network (NN) is constructed to solve coupled HJBE to obtain the event‐triggered optimal controller, in which the NN weight is updated only at the triggering instants. Through the implementation of these two dynamic event‐triggered mechanisms, resources and controller execution time can be saved. It is proved that the whole closed‐loop system signals are uniformly ultimately bounded by the Lyapunov technique. Finally, two illustrative examples verify the effectiveness and superiority of the proposed control scheme. [ABSTRACT FROM AUTHOR]

In the context of increasing renewable energy penetration and the imperative for efficient utilization, this paper explores the application of maximum power point tracking (MPPT) control for wind turbines. The objective is to optimize wind power generation by maximizing energy capture efficiency while addressing challenges associated with behind‐the‐meter renewables, load flexibility, and encouraging prosumers' participation. This paper proposes an adaptive integral sliding mode MPPT control strategy for wind turbines in the presence of external disturbance and model uncertainties. A new fixed‐time integral sliding mode manifold is constructed, such that the singularity problem can be avoided in the controller design without using any piecewise continuous functions. Then, an adaptive fixed‐time MPPT controller is developed to ensure that the tracking error can converge to a small neighbourhood around zero in fixed time, where the upper bound of the convergence time can be pre‐set based on actual engineering needs by selecting appropriate parameters. By designing update law, no prior knowledge on the upper bound of the lumped uncertainties is required anymore in advance. Stability analysis of the closed‐loop system is conducted using Lyapunov stability theory, and the effectiveness of the proposed strategy is validated through numerical simulations. [ABSTRACT FROM AUTHOR]

This article proposes an extreme learning machine (ELM)‐based super‐twisting integral terminal sliding mode control (STITSMC) for speed regulation of a permanent magnet synchronous motor (PMSM). First, the PMSM is modeled in a non‐cascade control structure for fast system response and uncertainty compensation in the speed and torque loops. Second, the STITSMC is designed with integral actions in both the sliding surface and the reaching law to reduce chattering. Third, the ELM is constructed to compensate for the system lumped disturbance, and relax the disturbance upper bound required by the controller which further reduces the chattering. Fourth, the stability of the whole control system is proved based on the Lyapunov method and the finite time convergence regions are derived for both the reaching and the sliding phases. Finally, the comparative simulations and experiments are conducted to show the superiority of the proposed control. [ABSTRACT FROM AUTHOR]

This paper considers the problem of robust optimal tracking control of multiple autonomous underwater Vehicles (AUVs) subject to uncertain external disturbances. First, the Takagi‐Sugeno (T‐S) fuzzy based technique is utilized to convert the high‐order nonlinear multi‐AUV system into a series of linearized subsystems. Second, a novel fully distributed sliding mode control (FDSMC) strategy is proposed to attenuate the disturbances. Meanwhile, the leader‐following consensus and the nearly optimization of the energy‐cost function for the multi‐AUV system can be achieved simultaneously through the designed optimal nominal control protocol. Moreover, the proposed control strategy has more mild constraints on the communication topologies. Finally, the effectiveness of the proposed FDSMC strategy is verified by numerical simulation studies. [ABSTRACT FROM AUTHOR]

A neural network adaptive integral terminal sliding mode control method with input saturation is proposed for the horizontal vibration problem of high‐speed elevator car systems caused by uncertainties such as guideway excitation and shaft piston wind change. First, considering the input saturation problem existing in the elevator control actuator, a class of smooth functions is introduced to approximate the nonlinearity of switching saturation, and an eight‐degree‐of‐freedom asymmetric anti‐saturation nonlinear system model of the high‐speed elevator car is established; second, in order to solve the singularity problem existing in the terminal sliding‐mode control, a nonlinear term is introduced into the sliding‐mode design, and a neural network is utilized for the fitting of the complex unknown function, and the design of the an adaptive integral terminal sliding mode controller (AITSMC), which enables the state variables of the system to achieve finite time convergence and proves the stability of the system by using Lyapunov theory; finally, under the action of two typical guide excitations, the proposed controller is compared with the passive control and adaptive control (AC), and the results show that, after adopting the proposed control method, the vibration acceleration eigenvalue is reduced by more than 60%, which effectively suppresses the horizontal vibration of the car system and verifies the effectiveness of the proposed controller. [ABSTRACT FROM AUTHOR]

This article addresses robust output regulation for systems affected by disturbances generated by an uncertain exosystem as well as matched external disturbances. The robustness of the feedback loop is achieved by combining internal model based control with sliding mode control, resulting in a structurally simple controller. The design of the proposed controller is presented first for the full information problem, that is, the disturbances generated by the exosystem and the state‐information is available for the control algorithm. This requirement is relaxed in the second step of the controller design, where the observer‐based robust output feedback‐loop structure is developed. Results from a comparative simulation study are presented to illustrate the advantages and the effectiveness of the proposed controller concept. [ABSTRACT FROM AUTHOR]

This article develops a predefined‐time sliding mode control approach for systems with external disturbances and uncertainties through a nonlinear disturbance observer (DO). For addressing predefined‐time stabilization problem of robotic manipulator system, a predefined‐time sliding mode surface is proposed, ensuring system states converge to origin within a predefined‐time once sliding mode surface is attained. Compared to conventional fixed‐time and finite‐time control strategies, a distinctive advantage of this scheme is that system settling time can be explicitly chosen in advance and independent of system states. To achieve predefined‐time performance, a disturbance observer is introduced to generate the disturbance estimate, which can be incorporated into controller to counteract disturbance. To address the systems uncertainty, an adaptive law is employed to estimate the unknown upper boundary of system uncertainties. Finally, the effectiveness and performance of the proposed scheme are illustrated by simulation and experiment. [ABSTRACT FROM AUTHOR]

In this work, an adaptive fast terminal sliding mode control (AFSMC) approach based on joint torque estimation and friction compensation is proposed to enhance the trajectory tracking accuracy of robotic manipulators under variable load conditions. The joint torque estimation utilizes an improved harmonic drive compliance model and adaptive low‐pass filtering, and friction compensation employs a hybrid model accounting for velocity and load torque effects. These compensations reduce the upper bound of the uncertainty, while AFSMC further reduces dependency on upper uncertainty bounds and minimizes the chattering. The stability analysis using the Lyapunov method confirms the effectiveness of this approach. Experimental results demonstrate that the proposed controller achieves smaller root mean square and maximum error of trajectory tracking, thus significantly improving trajectory tracking accuracy under variable load conditions. [ABSTRACT FROM AUTHOR]

Path tracking plays a critical role in autonomous driving for autonomous ground vehicle (AGV). However, AGV faces challenges in accurate tracking and chatter reduction due to external disturbances, making it difficult to meet the tracking performance requirements. Currently, sliding mode control (SMC) and disturbances observer are primarily employed for disturbance estimation. However, ensuring finite‐time robust control remains a significant challenge. To ensure rapid convergence of tracking errors and effective disturbance rejection, this paper proposed a novel non‐singular fast terminal sliding mode (NFTSM) control scheme based on finite‐time disturbance observation (FDO). First, a novel NFTSM controller based on AGV dynamic model is developed to achieve fast convergence of tracking errors. Then, to mitigate disturbances effects and suppress chatter, an innovative FDO method is employed. Finally, based on FDO, the NFTSM‐FDO establishes a control scheme that enhances disturbances suppression and accelerates convergence. The simulation and experimental results demonstrate the innovation of the proposed method. Compared with other SMC methods, the results validate the effectiveness and advantages of the proposed approach, exhibiting fast convergence and superior tracking performance. [ABSTRACT FROM AUTHOR]

This article investigates the fixed‐time rotating consensus problem of second‐order multi‐agent systems in both the leaderless and leader‐following cases. Specifically, in the leaderless case, a distributed controller is developed to drive all agents to reach rotating consensus in fixed‐time. In the leader‐following case, a distributed fixed‐time observer is first proposed to estimate the position of a rotating leader. Then, a local fixed‐time output feedback controller without any velocity measurements is proposed to achieve the leader‐following motion. Furthermore, an integral sliding mode control technique is applied to handle the case where the multi‐agent system is subject to time varying external disturbances. Based on the bi‐limit homogeneity method and Lyapunov theory, we prove that all the agents reach the rotating consensus within a fixed time independent of initial conditions. Finally, simulations illustrate the effectiveness of the proposed controllers. [ABSTRACT FROM AUTHOR]

This work introduces a new actuator fault estimation approach coupled with a fault‐tolerant control (FTC) strategy for uncertain systems in an output feedback framework. The proposed method involves constructing a Multi‐Layer Neural Network (MLNN) observer‐based fault estimation unit to accurately predict system states and potential faults in the actuator channel. An online control allocation (CA) scheme is then developed, utilizing the derived estimates to actively reconfigure the virtual control signals among the healthy redundant actuators in the event of actuator malfunction. Furthermore, an adaptive neural network‐based output integral sliding mode control scheme is designed based on the virtual control. This integration enhances the overall system's robustness and significantly reduces the chattering effect. The stability analysis of the proposed fault estimations scheme is initially performed using MLNN structure, followed by a comprehensive closed‐loop stability analysis to establish the stability of the entire system. Finally, the effectiveness of the proposed method is validated on a nonlinear six‐degree‐of‐freedom model of multirotor unmanned aerial vehicle aircraft. Numerical simulations under different fault and failure scenarios validate the efficacy of the proposed method. The comparative analysis of the proposed scheme is conducted with the static output feedback control allocations and adaptive allocation strategy. This analysis focuses on evaluating performance using metrics such as root mean square error and mean square deviation, particularly in the presence of faults and failures. The results demonstrate the superior performance of the proposed scheme in fault/failure conditions. [ABSTRACT FROM AUTHOR]

This paper presents a nonlinear higher‐order sliding mode control (HO‐SMC) designed for a droop control‐based grid‐forming converter. In weak grid scenarios, where the rate of change of frequency is notably high, achieving a rapid frequency response becomes imperative. The stable operation of a grid‐forming converter using droop control, coupled with classical vector control that employs cascaded voltage and current loops (multiloop) with PI controllers, faces limitations when higher droop coefficients are applied. This constraint on the application of classical vector control in weak grid conditions necessitates alternative solutions. Operating as a grid‐forming converter, the grid‐connected converter with an LCL filter represents a second‐order system. HO‐SMC mitigates the switching challenges associated with conventional SMC by integrating robust feedback linearized control. A graphical method is proposed for designing the switching gain using Lyapunov's direct method to counteract the impact of a matched disturbance. The study demonstrates that the implementation of HO‐SMC in the grid‐forming converter enhances fast frequency response by increasing the gain margin of the power frequency (P--f)$(P\text{--}f)$ loop. Finally, it is illustrated that the proposed control method also improves the transient response of the converter. [ABSTRACT FROM AUTHOR]

ABSTRACT This article investigates a satellite sun‐safe controller based on a super‐twisting disturbance observer (STDO) with interval analysis. First, a variable gain sliding mode control (SMC) algorithm is proposed to ensure that the satellite can achieve a fixed‐axis rotation and sun‐pointing attitude. The controller gains are adjusted according to the disturbance estimation value and the interval of the disturbance estimation error. The important feature of the adaptation algorithm is in non overestimating the values of the control gains. To achieve the purpose of non‐overestimating, a STDO is constructed to estimate the unknown disturbance. Additionally, the interval of the disturbance estimation error is obtained by interval analysis to update the controller gain in real time. Then, the stability and convergence of the closed‐loop system, including the variable gain sliding mode controller and the super‐twisting observer, are verified by using the Lyapunov theory. Finally, hardware‐in‐the‐loop (HIL) experimental results demonstrate that the proposed method not only performs better in terms of convergence and accuracy than the state‐of‐the‐art sun‐safe controller design method but also achieves more negligible chattering in the presence of disturbance torque compared to the fixed gain SMC method. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper presents a nonsingular fast terminal sliding mode control for the PAR 4 parallel robot, focusing on workspace optimization and trajectory planning. First, an analytical inverse kinematic model is derived to calculate the workspace, which is then extended using parameter optimization techniques. Next, a trajectory planning method based on the S‐curve approach is proposed to generate the desired path, with special attention to reducing the cycle time of pick‐and‐place operations using sequential quadratic programming method. Finally, a nonsingular fast terminal sliding mode control strategy is suggested to enable the robot to accurately track the generated trajectory. The stability of the closed‐loop system is analyzed using Lyapunov theory, and the effectiveness of the controller is validated through simulation results. [ABSTRACT FROM AUTHOR]

Although widely used in industrial applications, strong nonlinearity and coupling, high computational complexity prevent high precision tracking control of manipulator. In this paper, to overcome the rely on system model and achieve prescribed convergence, a novel hybrid observer‐based model‐free adaptive high‐order fast terminal sliding model control scheme (HO‐MHTSMC) with prescribed performance is proposed for trajectory tracking control of robot manipulators in the existence of friction and external disturbance. The ultra‐local model is used to approximate the original complex system in a model free form in a short sliding time window, which avoid the accurate modeling of the manipulator system. To compensate for the lumped uncertainties, a hybrid observer based on adaptive time‐delay estimation and adaptive second order sliding mode observer (SOSM) is proposed to achieve finite‐time observation and zero estimation error. Besides, a transformation using prescribed performance function is applied to the system to ensure the transient and steady‐state performance of the trajectory tracking in joint space. Furthermore, a high‐order fast terminal sliding mode control algorithm with backstepping control strategy is used to stabilize the whole system and reduce the chattering problem in conventional sliding mode control. The stability analysis of the system is provided by Lyapunov theorem. Finally, numerical study and co‐simulations show that the proposed control scheme has better performance in tracking accuracy and robustness compared with conventional control schemes. [ABSTRACT FROM AUTHOR]

Summary: In this paper, a prescribed performance model‐free adaptive platooning sliding mode control (PP‐MFAP‐SMC) problem for the nonlinear vehicular platooning systems (VPSs) under denial‐of‐service (DoS) attacks is studied. Firstly, the partial form dynamic linearization (PFDL) technique is employed to convert the nonlinear VPSs into an equivalent linear data model, in which the nonlinear features of the VPSs are compressed into an unknown time‐varying pseudo gradient (PG) vector. Then, an observer is devised to acquire the estimation value of the unknown time‐varying PG vector. To lower the complication of the design, the constrained tracking error is converted into the unconstrained one. Based on which, the sliding mode control (SMC) strategy is proposed to enhance the robustness of the VPSs. Further, a PP‐MFAP‐SMC algorithm with an attack compensation mechanism is developed to ensure that the vehicular tracking errors of the position and velocity can converge to the predefined regions, respectively. Eventually, the effectiveness of the developed algorithm is demonstrated by an actual VPS with the comparisons. [ABSTRACT FROM AUTHOR]

Summary: The primary objective of this paper is to enhance the efficient utilization of communication resources. To achieve this, the paper delves into the disturbance observer based adaptive heading control strategy for Unmanned Marine Vehicles with event‐triggered and input quantization. Furthermore, in order to mitigate the impact of slow time‐varying external disturbances within the control system, the disturbance observer is employed for estimation. Within the context of a networked control, control input is subjected to quantization via an input quantizer, and the process of input quantization is described by using a linear analytical model. Importantly, no foreknowledge of quantization parameters is necessary for the quantized feedback controllers. Subsequently, the sliding mode control method is combined with event‐triggered mechanismss to design quantization feedback control system. The stability of the closed‐loop system is established in line with the fundamental tenets of Lyapunov stability theory, validating the bounded nature of both observation and heading tracking control errors. The effectiveness of the proposed heading control scheme is further underscored through a series of simulation experiments. [ABSTRACT FROM AUTHOR]

ABSTRACT This article introduces a third‐order super‐twisting sliding mode control (Gen‐STSMC) algorithm designed for the secure operation of a grid‐connected photovoltaic (PV) system. The improved method changes the traditional super‐twisting sliding mode control (STSMC) technique by incorporating both a linear term and a higher power term to reduce convergence time and chattering effects. This strategy generates the optimal control signals to regulate the output power of the PV system by compensating the state‐dependent uncertainties using the linear and growing term. The controller's stability analysis is conducted to demonstrate its rapid convergence compared to PI and conventional STSMC scheme. A comparative simulation study against PI and STSMC is conducted to showcase the controller's rapid convergence and robust performance in various grid‐connected PV system scenarios. Experimental tests are also performed to validate the controller's effectiveness in maintaining stable power generation in the presence of environmental fluctuations and DC link voltage variations. [ABSTRACT FROM AUTHOR]

Modular multilevel green converter based high voltage direct current (MMC‐HVDC) transmission system has become a practical solution to interconnect renewable energy sources to main AC grids. Connecting the MMC to a weak AC system is still a challengeable problem. This paper proposes a sliding mode control‐based method for the MMC. By considering short circuit ratio parameter of the AC grid as uncertainty, a suitable mathematical model is developed. Also, relations among control parameters and their validity conditions are obtained. The proposed control scheme has faster dynamic responses to uncertainty and external disturbances compared to the conventional vector current control method with proportional–integral controller. At last, simulation results in the MATLAB/SIMULINK software environment are presented that the proposed control scheme is effective. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper proposes a novel finite‐time adaptive continuous robust control method for buck converters, combining dynamic sliding mode theory with a mismatched disturbance observer. While traditional sliding mode control can effectively manage matched disturbances, it often falls short when faced with mismatched disturbances, potentially compromising system performance. Our developed control strategy introduces a nonlinear sliding mode‐based disturbance observer and an adaptive continuous robust sliding mode control to guide state variables towards desired values. To mitigate the chattering phenomenon, the proposed controller incorporates a super‐twisting algorithm, ensuring continuous control command behavior. We conducted a rigorous finite‐time stability analysis of the control procedure using Lyapunov theory. Furthermore, comprehensive experimental results demonstrate that our proposed control method significantly reduces disturbance effects and enhances the buck converter's performance in terms of robustness and accuracy. [ABSTRACT FROM AUTHOR]

In this article, the stabilization of coupled time fractional parabolic partial differential equations subject to external disturbances is investigated. By using sliding mode control method and backstepping approach, a boundary state feedback controller is designed to reject the matched disturbance and achieve the Mittag‐Leffler input‐to‐state stability of closed‐loop system. The existence of the generalized solution to the closed‐loop system is proven by Galerkin approximation scheme. Simulations are presented to illustrate the validity of our theoretical results. [ABSTRACT FROM AUTHOR]

In this study, a high robust control—second‐order sliding‐mode control (SOSMC) scheme is proposed to improve the DC‐link voltage dynamic performance of the grid‐side converter (GSC) for the doubly‐fed induction generator (DFIG) system under the wind turbine power disturbance and DC‐link capacitance parameter disturbance. In general, the wind speed is change with the environment and further has an effect on the power generation of the DFIG system. Besides, the capacitance of DC‐link capacitor may change with the working condition. To address this issue, a SOSMC scheme is proposed to replace the conventional proportional integral (PI) control for the DC‐link voltage controller of the GSC for the DFIG system in this study. By using the non‐linear SOSMC controller, the DFIG system is robust to the disturbance of the wind speed and the parameter of DC‐link capacitance. Compared with the conventional PI control scheme, the DFIG system with the proposed SOSMC scheme is much more robust, which has been verified in the MATLAB/Simulink platform. [ABSTRACT FROM AUTHOR]

In this paper, an extended state observer based fractional‐order sliding mode control strategy is studied for vehicle steer‐by‐wire systems (SBWSs). The parameter perturbation and external interference are considered in the dynamic model of SBWSs. A fractional‐order sliding mode control scheme is designed to solve the tracking problem and improve the control performance. An extended state observer is further used to estimate the lumped disturbance, and then the estimated value is considered as a feedforward compensation to reduce the chattering phenomenon. Finally, comparison simulation results show that the excellent steering tracking and strong robustness performance have been achieved by the proposed control strategy for SBWSs. [ABSTRACT FROM AUTHOR]

This study presents a new Maximum Power Point Tracking (MPPT) approach for solar photovoltaic (PV) systems, combining the Super‐Twisting Algorithm (STA) and Grey Wolf Optimizer (GWO). The STA‐GWO‐MPPT method improves efficiency in dynamic conditions by using STA for control and GWO for parameter optimization, enhancing stability and robustness. Performance evaluation is conducted through MATLAB/Simulink simulations and experimental validation on a small‐scale test bench. Various quantitative metrics, including rise time, settling time, power production, efficiency, root mean square error (RMSE), and standard deviation (STD), are employed for assessment. Results indicate significantly faster convergence speeds for the proposed method compared to conventional MPPT techniques. Specifically, the rise time for the proposed method is 0.0129 seconds, outperforming Fuzzy Logic Control (FLC) (0.2638 seconds) and Grey Wolf Optimizer with Sliding Mode Control (GWO‐SMC) (0.0181 seconds). Additionally, the proposed method exhibits superior tracking efficiency, with an average efficiency of 99.33%, surpassing FLC (96.93%) and GWO‐SMC (99.19%). Moreover, it reduces power fluctuations, with an RMSE of 7.819% and STD of 6.547%, compared to FLC (RMSE: 13.471%, STD: 4.519%) and GWO‐SMC (RMSE: 8.507%, STD: 6.108%). Overall, this study contributes valuable insights into enhancing MPPT efficiency in solar PV systems, with implications for both research and practical applications. [ABSTRACT FROM AUTHOR]

To enhance the dynamic performance and robustness of the voltage control system of islanded microgrid inverters, a new control strategy combining integral sliding mode (ISM) control and composite nonlinear feedback (CNF) control is proposed. In ISM control, firstly, a new reaching law is designed to improve movement quality in the reaching phase by improving the power term and introducing the inverse tangent function. Then, to improve disturbance observation accuracy, a variable gain extended state observer is designed by improving the regulation mechanism of the state variables according to deviation control. Using the idea of variable damping, linear and nonlinear feedback are combined into CNF control. Specifically, linear feedback provides a small damping ratio for faster system response, while nonlinear feedback increases the damping ratio to improve steady‐state performance. Simulation results show that the integral sliding mode‐composite nonlinear feedback (ISM‐CNF) control strategy cam balances convergence speed and chattering better and achieves higher steady‐state accuracy than conventional strategies. Moreover, ISM‐CNF control has better robustness to reference voltage variations and disturbances caused by sudden load changes. Therefore, the ISM‐CNF control strategy can accomplish voltage control of islanded microgrid inverters quickly and steadily, effectively suppressing system disturbances and enhancing stability and power quality. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

One‐dimensional thrust vectoring turbojet vertical takeoff and landing (VTOL) aircraft have attracted research attention due to their high thrust‐to‐weight ratios and their solution for the slow speed response of turbojet engines. However, there are some uncertainties and physical limitations in their systems, such as external disturbances, unknown parameters and input saturation. To improve the accuracy and convergence speed of trajectory tracking, a fixed‐time control method that is robust to saturation is proposed. The system dynamics are established, and an auxiliary system is built within a fixed time control framework to address the influence of input saturation and increase the error convergence rate. Nonsingular fast terminal sliding mode technology is combined with a few adaptive laws to ensure the robustness of the closed‐loop system against dynamic uncertainties and improve the precision of steady‐state control. The stability of the control system is proven based on Lyapunov, and the controller parameters are optimized based on particle swarm optimization (PSO). The proposed method based on fixed‐time stability guarantees that the states of the closed‐loop system can reach the residual set around zero within the designed time, and an expression for the upper bound on the convergence time is given. Finally, numerical simulations demonstrate the superiority of the proposed method based on the error integral criterion. [ABSTRACT FROM AUTHOR]