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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]

In this paper, split-source inverter (SSI) is proposed for multi-functional grid-connected (MFGC) application because it offers the better boosting capability with fewer components. Furthermore, the SSI could operate as a full active power filter (APF), unlike the impedance source inverter (ZSIs) topologies. This paper proposes a sliding mode control (SMC) scheme for controlling both DC and AC sides of the MFGC system based SSI, the MFGC system aims to compensate the reactive power at grid side, satisfy the non-linear load power demand using the extracted PV power, and inject the remaining PV power into the grid. On DC-side, the SMC scheme is designed to control the DC input current while estimating the duty cycle that ensures the boosting capability. Then, a decoupled control scheme based on the SMC is designed to control the AC-side of the system and estimate the reference voltages that are fed to a modified space vector modulation (MSVM) stage. The entire system is simulated using the MATLAB/Simulink environment and validated experimentally through real-time hardware in the loop setup. The obtained results from simulation and HIL setup demonstrate the effectiveness and robustness of the proposed control scheme in terms of power management and power quality enhancement.

Effective control of the generator’s shaft speed will ensure maximum power is captured from the wind turbines. However, the parameters of the wind energy conversion system (WECS)-based generators, including stator resistance and inductance, could change over time due to power loss, winding degradation, or core saturation. These parametric uncertainties affect the performance of the designed controllers. Although the sliding mode controllers (SMCs) are robust to matched uncertainties, the unmatched parametric uncertainties were not effectively compensated for by the SMC. This study investigated the performance of the SMC and super-twisting SMC (ST-SMC) under unmatched uncertainties using variable wind speed. Initially, the controllers were designed with the nominal parameters of the WECS-based permanent magnet synchronous generator (PMSG). Then, the values of the stator resistance and inductance were changed without changing the control design to test the robustness of the controllers to unmatched uncertainties. Finally, the uncertainties were estimated by the disturbance observer and incorporated into the controllers as a compensation mechanism. The controllers were designed using the synthetic wind profile and validated with the real-wind data. The transient and overall response of the controllers were analyzed using mean-absolute error (MAE) and root-mean-square error (RMSE) of the shaft speed tracking. The results demonstrated that the uncertainty compensation-based SMC/ST-SMC approach provides satisfactory shaft speed tracking performance even under parametric uncertainties.

This paper presents an improved sliding mode control (SMC) for performance enhancement of personal mobility device (PMD) battery charger using fuzzy logic control. The PMD industry has recently been activated to reduce environmental pollution and accordingly, research on PMD battery chargers is being actively conducted. Typically, proportional-integral (PI) control or SMC methods are used to control the output voltage and inductor current of PMD battery charger. However, increasing the gain of PI controllers and SMC method to improve performance results in overshoot in output voltage and ripple in inductor current due to chattering phenomena. Therefore, to overcome the disadvantage, this paper presents improved sliding mode control for performance enhancement of PMD battery charger using fuzzy logic control (FLC). The proposed control method determines the gain used in the SMC by using FLC, and determines the gain of the controller through the membership function and the output intensity, thereby reducing ripple and improving responsiveness. The validity of the proposed control method is verified by the simulation and experimental results.

A predefined-time sliding mode adaptive control method (PDTSMAC)for nonlinear system is proposed in the presence of parameters unknown, external disturbances and arbitrary initial values. Firstly, the expected trajectory of the system is extended to the arrival process with characters of predefined-time convergence and the accurate tracking process of completely tracking the desired trajectory, the design principle of extended trajectory is given; Then, an extreme learning machine (ELM) with exponential convergence of external weights is designed to compensate the uncertainties of the system, and a sliding mode adaptive controller with predefined-time convergence is constructed based on a predefined-time convergent sliding mode surface. The stability of the closed-loop system is proved theoretically. The simulation results show that the control strategy can ensure that the construction robot in arbitrary initial state converges to the extended desired trajectory within the predefined-time, and realizes the complete and accurate tracking of the preset desired trajectory, and the trajectory tracking error is less than 0.008. [ABSTRACT FROM AUTHOR]

Recently renewable energy such as a photovoltaic (PV) system has been utilized more and more since it is pollution-free and permanent. To maintain the PV system functioning at, or near, the peak power point of the PV panel under different conditions such as fluctuating solar irradiation, temperature, and other factors, maximum power point tracking algorithms are required. In this study, a novel hybrid robust intelligent controller for a photovoltaic system is proposed. Three loops are used for creating the proposed controller, ensuring the controller's robustness. The first loop's objective is to locate the photovoltaic system's highest power spots. In the second loop, a novel fractional-order sliding model observer based on deep reinforcement learning optimization approach is proposed as a result of the design of a reliable controller under the lumped uncertainty in the system. Designing a novel back-stepping fast non-singular terminal fractional-order sliding mode controller is achieved at the final step. This method offers a nice transition response, a small tracking error, with a quick response to changes in solar radiation. Numerical analysis shows that the performance of the photovoltaic system by the proposed controller has been able to increase the efficiency of the system significantly. [ABSTRACT FROM AUTHOR]

As photovoltaic energy is clean, renewable, and less noisy, it is increasingly integrated into the grid. This integration aims to overcome energy deficits and get rid of pollution from conventional sources. In this paper, a two-stage configuration of PV energy conversion to a three-phase grid has been studied. The control of this configuration can be divided into two parts, such as DC bus control and AC bus control. The DC bus is controlled by MPPT control. The AC bus is controlled by DC link voltage control, phase-looked loop control, and voltage source inverter control. The contribution in this study aims to improve the quality of energy injected via a new hybrid approach to MPPT control. The proposed control is a combination of robust sliding-mode control and incremental inductance. Unlike conventional hybridization, the proposed control estimates correct the error upon entry of the conductance incremental control. This correction provides an adaptive incremental step for increment conductance control. The proposed control is compared with three other controls under MATLAB/Simulink. Such as incremental conductance, variable step size incremental conductance, and conventional hybrid MPPT incremental inductance-sliding mode control. The simulation results show a remarkable minimization of the ripple phenomenon and the chatter phenomenon. Thus, the quality of the energy injected into the network is improved, such as by reducing the total harmonic distortion of the current and increasing efficiency. [ABSTRACT FROM AUTHOR]

With the large-scale integration of renewable energy into off-grid DC systems, the stability issues caused by their fluctuations have become increasingly prominent. The dual active bridge (DAB) converter, as a DC-DC converter suitable for high power and high voltage level off-grid DC systems, plays a crucial role in maintaining and regulating grid stability through its control methods. However, the existing control methods for DAB are inadequate: linear control fails to meet dynamic response requirements, while nonlinear control relies on detailed model structures and parameters, making the control design complex and less accurate. To address this issue, this paper proposes a feedforward control strategy for a DC-DC converter in an off-grid hydrogen production system based on a linear extended state observer (LESO) and super-twisting sliding mode control (STSMC). Firstly, a reduced-order simplified model of the DAB was constructed through the structure of DAB. Then, based on the reduced-order simplified model, a feedforward control based on LESO and STSMC was designed, and its stability was analyzed. Finally, a simulation comparison of PI, LESO + terminal sliding mode control (TSMC), and LESO + STSMC control methods was conducted in a DC off-grid hydrogen production system. The results verified the proposed control method's enhancement of the DAB's rapid dynamic response capability and the system's transient stability. [ABSTRACT FROM AUTHOR]

This paper introduces an efficient and simple power control for the Wind Energy Conversion System (WECS) based on the Doubly-Fed Induction Generator (DFIG). Due to the limitation performance of the conventional PI controller against DFIG parameters change and wind speed variation; the sliding mode theory is applied in order to overcome these drawbacks. To improve the performances of a WECS, robust and nonlinear control techniques, namely; Conventional Sliding Mode Control (C-SMC) and Third Order Sliding Mode Control (3O-SMC), were implemented to independently control the stator active and reactive powers. However, both techniques exhibited a chattering phenomenon, an undesirable phenomenon caused by discontinuous signals. To overcome this drawback and further enhance previous control techniques, an advanced Variable Gain Super Twisting Algorithm (VGSTA) is proposed and compared to SMC and 3O-SMC. Furthermore, to validate the effectiveness of the proposed VGSTA strategy in comparison to two previous control methods, the WECS was simulated and validates using the MATLAB/Simulink environment. The simulation results clearly demonstrated the superiority of the proposed VGSTA strategy over the previous SMC and 3O-SMC techniques. This was obvious in terms of both fast convergence velocity and reduce chattering phenomenon. [ABSTRACT FROM AUTHOR]

This paper addresses a class of uncertain nonlinear systems with disturbances that are challenging to model by proposing a novel model-free adaptive sliding mode control (MFASMC) scheme based on a discrete-time extended state observer (DESO). Initially, leveraging the pseudo partial derivative (PPD) concept in the model-free adaptive control (MFAC) framework, the discrete-time nonlinear model is converted into a full-form dynamic linearization (FFDL) model. Secondly, using the FFDL data model, a discrete sliding mode controller is designed. A discrete integral sliding mode surface is chosen to mitigate chattering during the reaching phase, and a hyperbolic tangent function with minimal slope variation is selected for smoother switching control. Furthermore, a DESO is designed to estimate uncertainties in the discrete system, enabling real-time compensation for the controller. Finally, a genetic optimization algorithm is employed for parameter tuning to minimize the time cost associated with selecting control parameters. The design process of this scheme relies solely on the data of the controlled system, without depending on a mathematical model. The proposed DESO-MFASMC scheme is tested through simulations using a typical numerical equation and the existing EFG-BC/320 electric heavy-duty forklift from the Quzhou Special Equipment Inspection Center. Simulation results show that the proposed method is significantly superior to the traditional MFAC and PID control methods in tracking accuracy and robustness when dealing with nonlinear disturbance of the system. The DESO-MFASMC scheme proposed in this paper not only shows its advantages in theory but also verifies its effectiveness and practicability in engineering through practical application. [ABSTRACT FROM AUTHOR]

Dual-Active-Bridge (DAB) DC–DC converters are becoming increasingly favored for their efficiency in transferring electrical power across varying voltage levels. They are crucial in enhancing safety and reliability in various fields, such as renewable energy systems, electric vehicles, and the power supplies of electronic devices. This paper introduces a new control strategy for bidirectional isolated DAB DC–DC converters, implementing a Double Integral Super Twisting Sliding Mode Control (DI-STSMC) to accurately regulate the output voltage and current. The approach starts with a state-space representation to mathematically model the DAB converter. In light of model uncertainties and external disturbances, a robust DI-STSMC controller has been formulated to optimize the DAB converter's output performance. This method achieves zero steady-state error without chattering and provides a quick response to fluctuations in load and reference changes. The validity of the proposed technique is demonstrated through simulation results and a control hardware-in-the-loop (CHIL) experimental setup, using Typhoon HIL 606 and Imperix B-Box RCP 3.0 on a 230 W DAB converter. Furthermore, the paper offers a comparative analysis of the DI-STSMC with other control strategies, such as the proportional-integral (PI) controller, standard sliding mode control (SMC), and integral sliding mode control (ISMC). [ABSTRACT FROM AUTHOR]

This paper proposes a novel sliding mode control (SMC) algorithm for direct yaw moment control of four-wheel independent drive electric vehicles (FWID-EVs). The algorithm integrates adaptive law theory, fractional-order theory, and nonsingular terminal sliding mode reaching law theory to reduce chattering, handle uncertainty, and avoid singularities in the SMC system. A sequential quadratic programming (SQP) method is also proposed to optimize the yaw moment distribution under actuator constraints. The performance of the proposed algorithm is evaluated by a hardware-in-the-loop test with two driving maneuvers and compared with two existing SMC-based schemes together with the cases with the change of vehicle parameters and disturbances. The results demonstrate that the proposed algorithm can eliminate chattering and achieve the best lateral stability as compared with the existing schemes. [Display omitted] • A novel AFONT-SMC is proposed to achieve fast global convergence and precise tracking. • An adaptive law is proposed to avoid singularity and strengthen the system robustness. • A new boundary of full vehicle is studied to ensure the controllability of FWID-EVs. • Two new actuator constraints are studied to improve torque distribution in FWID-EVs. [ABSTRACT FROM AUTHOR]

In this article, sliding mode control (SMC) strategy is reported for frequency stabilization in microgrid (MG) using event-triggering mechanism (ETM) subject to load disturbances and uncertainties. The MG systems are characterized as systems affected by large computation and data transmission between different components in a control loop. This acts as a major constraint in a resource-limited network control systems (NCSs). Therefore, an ET-SMC is proposed in this article which not only ensures system stability under uncertainties and disturbance but also effective utilization of communication channel resources in terms of lesser computation and data transmission. The ET approach utilizes a requirement-based control strategy, wherein the control signal is updated and activated solely upon the violation of a predefined triggering condition. It is observed that an ETC approach saves approximately around 80% resources compared to time-triggered approach while maintaining system stability. The proposed design undergoes validation against system parameter variation and energy system nonlinearities, demonstrating that the frequency response remains within acceptable limits. The proposed design is also seen to provide better frequency stabilization with larger average inter-event time and lesser triggering number. Theoretical proof of stability is established through the application of a Lyapunov function, while its verification is conducted via simulation in MATLAB. [ABSTRACT FROM AUTHOR]

This article proposed the architecture of a stand-alone photovoltaic connected system (SPVS) with energy storage. An SPVS with energy storage requires power management for various operating modes. A coordinate controller is often necessary to manage the change in control architecture depending on the operating mode. This proposed system contains a boost converter (BC) and a bidirectional switched quasi-Z-source DC-DC converter (BSQZSDC). The BC is used for two purposes. The first is extracting the maximum power from the PV. The second is to control the DC link voltage when the SPVS is not in MPPT mode; dual-loop PI controllers are used for this. The BSQZSDC is used for energy management and regulates DC link voltage when SPVS operates in MPPT mode. This paper addresses about the effective control approach that BSQZSDC used, i.e., the double-integral sliding mode control, to regulate the DC link voltage and battery current in various operating modes. Experimental results were carried out to depict that the controller reasonably achieves the control objectives and proper energy management. [ABSTRACT FROM AUTHOR]

To improve motion accuracy through functional electrical stimulation (FES) of forearm muscles, feedback control laws are applied to the index finger's metacarpophalangeal (MP) joint. This paper introduces a proxy-based super-twisting algorithm (PSTA) for precise servo control of MP joints via FES. The PSTA combines first-order sliding mode control with a second-order super-twisting algorithm, effectively preventing windup during FES saturation and ensuring robust, accurate control. An implicit Euler method minimizes numerical chattering in the digital implementation. Experiments with Arduino and volunteers confirm the algorithm's effectiveness. [ABSTRACT FROM AUTHOR]

This paper proposes the finite-time consensus problem for heterogeneous multi-agent systems (HMASs) with second-order linear and nonlinear agents, where the communication between agents is described by directed graphs. Firstly, the integral sliding mode control (ISMC) protocol is designed, and then it is used for finite-time consensus tracking of HMASs. In the next place, by applying graph theory, Lyapunov techniques, and other mathematical methods, it is shown that each agent in heterogeneous system can achieve consensus in finite-time if certain conditions are fulfilled, most notably by using Lyapunov stability theory to obtain sufficient conditions for finite-time consensus. Eventually, simulations are utilized to demonstrate the validity of the presented theoretical results. [ABSTRACT FROM AUTHOR]

This paper focuses on the speed regulation of permanent magnet synchronous motors (PMSM) in electric vehicle application using sliding mode control (SMC). Harris hawks optimizations (HHO) based sliding mode controller is adopted to increase the dynamic response of the PMSM motor, thereby enhancing vehicle performance. For the independent control of torque and flux, field oriented-control (FOC) is used to drive the PMSM. In this work, the speed reference provided for the controller is based on an electric car driving cycle that replicates real-world driving conditions. The optimal selection of sliding mode controller parameter enhances the dynamic characteristics of the speed regulation in electric vehicles, which is validated using the hardware in the loop (HIL-402) device. The HHO based sliding mode controller has superior performance in terms of robustness against load disturbances, fast convergence, and tracking accuracy.

Abstract Achieving accurate position tracking for robotics and industrial servo systems is an extremely challenging task, particularly when dealing with control saturation, parameter perturbation, and external disturbance. To address these challenges, a predefined time convergent sliding mode adaptive controller (PTCSMAC) has been proposed for a permanent magnet linear motor (PMLM). A novel sliding mode surface (SMS) with predefined time convergence PDTC has been constructed, which ensures that the error converges to zero within the prescribed time. The system not only meets the expected performance standards but also has a uniformly bounded motor speed. The trajectory tracking error in SMS is proven to converge to zero within the predefined time. This predefined time stability of the closed-loop system has been demonstrated by using the Lyapunov stability criterion with PDTC. The convergence time (CT) can be arbitrarily set, and the upper bound of it is not affected by the initial value and control parameters of the system. A new updated version of extreme learning machine (ELM) is introduced to approximate the uncertain part of the system based on PDTC. The ELM is also provided with the hyperbolic tangent function to estimate the saturation constraint. This is done by converting the function into a linear function concerning the unconstrained control input variable. Then, based on established stability, a novel sliding mode adaptive controller (PTCSMAC) with predefined time convergence is designed. The convergence time (CT) of the controller is unaffected by the initial conditions as well as the control parameters. The rigorous numerical simulations on the PMLM model with complex disturbances verify the strong robustness and high-precision tracking characteristic of the proposed control law.

The article concentrates on exploring the issue of privacy‐preserving sliding mode consensus of multi‐agent systems (MASs) with disturbance. An encryption and decryption algorithm has been proposed to address data security and privacy issues during data transmission. To optimize network resource allocation, a dynamic event‐triggering mechanism has been introduced, which reduces the number of encrypted data while saving the computation cost. The consensus performance based on the sliding mode control strategy is achieved when the reachability of the slide‐mode surface is guaranteed, and then the slide‐mode controller is developed. Finally, an empirical demonstration through a numerical example validates the efficacy of the proposed strategy. [ABSTRACT FROM AUTHOR]

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Robot manipulators as an indispensable part of automatic operation are becoming increasingly important in intelligent manufacturing systems, such as grinding and assembly. Although control methods of robot manipulators have been extensively studied, high-precision robots still face new challenges from uncertainties caused by changes in the environment and enhancement of interference. As a consequence, the neural network-based observer is utilized to reduce the influence of uncertainties and external disturbances. In this work, a new kind of nonlinear disturbance observer is designed which could well function with observed states. To improve the control efficiency and response characteristic, a kind of new integral sliding manifold is devised and the control input is generated via backstepping techniques. The stability is proved with Lyapunov theory, and the experimental results are given to demonstrate the effectiveness of the proposed controller. [ABSTRACT FROM AUTHOR]

The control effectiveness of the all-electric tank stabilizers directly affects the firing accuracy of the tank gun. In order to improve the firing accuracy of the moving tank, this paper proposes a sliding mode control (SMC) strategy using neural network feed-forward compensation for the tank bidirectional stabilizers. SMC technology can quickly and effectively deal with uncertainties, unmodeled terms, and external disturbances in complex tank systems. Neural networks possess the advantage of approximating arbitrary continuous functions in finite time, realizing the estimation of SMC control errors with feed-forward compensation. The Lyapunov stability analysis proves that the designed controller can achieve asymptotic stabilization in finite time. Finally, both co-simulation and physical experiments are conducted. The results show that the proposed control strategy possesses better tracking speed and tracking accuracy compared to the conventional controller and exhibits strong robustness. [ABSTRACT FROM AUTHOR]

This paper proposes a composite sliding mode control (SMC) to optimize the tracking performance and the anti-disturbance performance of permanent magnet synchronous machine (PMSM) speed regulation systems. The differential term in the control law can magnify the measurement noise, resulting in more discontinuity. To filter out the high frequency noise and make the control law smoother, the first-order differentiator (FOD) is employed to estimate the speed error and its derivative. Since the feedforward compensation can improve the robustness of the system, a disturbance observer (DOB) based on the sliding mode observer (SMO) is designed to reinforce the dynamic performance under disturbance variation. Under the effect of the feedforward compensation, chattering can be further weakened by decreasing the switching gain appropriately. Finally, the effectiveness of the proposed methods is confirmed by various experimental results. • Compared to existing nonlinear controllers, the proposed methods are easy to understand and implement. Meanwhile, they possess strong anti-disturbance performance and tracking performance. • The amplification of measurement noise is effectively mitigated through the FOD, leading to a smoother control law. As a result, chattering is significantly attenuated. • The feedforward compensation via the SMO is adopted to improve the anti-disturbance performance, and accordingly, chattering is further reduced by decreasing the switching gain. [ABSTRACT FROM AUTHOR]

This paper proposes a novel fault-tolerant synchronous sliding mode control for a 4-DOF parallel manipulator against uncertainties such as modelling error and actuator faults. The proposed control is developed with the consensus approach, sliding mode control, and extended state observer to manage the tracking objective and guarantee the synchronous requirements. The consensus approach combines the tracking and synchronous errors, which helps to integrate both the tracking and synchronous requirements into cross-coupling errors. Firstly, the kinematics and dynamics of the parallel manipulator are described according to the geometric and Euler Lagrange approaches with the challenges. Secondly, the Lyapunov approach is implemented to verify the stability and robustness of the proposed control in theory. Then, some simulations are conducted in MATLAB Simulink with the robotic dynamics generated by converting the design model in SOLIDWORKs into SIMSCAPE. The comparisons between the proposed control and other controllers are made by creating simulations to evaluate the advantages of the proposed approach. [ABSTRACT FROM AUTHOR]

Achieving accurate position tracking for robotics and industrial servo systems is an extremely challenging task, particularly when dealing with control saturation, parameter perturbation, and external disturbance. To address these challenges, a predefined time convergent sliding mode adaptive controller (PTCSMAC) has been proposed for a permanent magnet linear motor (PMLM). A novel sliding mode surface (SMS) with predefined time convergence PDTC has been constructed, which ensures that the error converges to zero within the prescribed time. The system not only meets the expected performance standards but also has a uniformly bounded motor speed. The trajectory tracking error in SMS is proven to converge to zero within the predefined time. This predefined time stability of the closed-loop system has been demonstrated by using the Lyapunov stability criterion with PDTC. The convergence time (CT) can be arbitrarily set, and the upper bound of it is not affected by the initial value and control parameters of the system. A new updated version of extreme learning machine (ELM) is introduced to approximate the uncertain part of the system based on PDTC. The ELM is also provided with the hyperbolic tangent function to estimate the saturation constraint. This is done by converting the function into a linear function concerning the unconstrained control input variable. Then, based on established stability, a novel sliding mode adaptive controller (PTCSMAC) with predefined time convergence is designed. The convergence time (CT) of the controller is unaffected by the initial conditions as well as the control parameters. The rigorous numerical simulations on the PMLM model with complex disturbances verify the strong robustness and high-precision tracking characteristic of the proposed control law. [ABSTRACT FROM AUTHOR]

This paper focuses on the speed control of a permanent magnet synchronous motor (PMSM) for electric drives with model uncertainties and external disturbances. Conventional sliding mode control (CSMC) can only converge asymptotically in the infinite domain and will cause unacceptable sliding mode chattering. To improve the performance of the PMSM speed loop in terms of response speed, tracking accuracy, and robustness, a hybrid control strategy for a fixed-time-convergent sliding mode controller (FSMC) with a fixed-time-convergent sliding mode observer (FSMO) is proposed for PMSM speed regulation using the fixed-time control theory. Firstly, the FSMC is proposed to improve the convergence speed and robustness of the speed loop, which can converge to the origin within a fixed time independent of the initial conditions. Then, the FSMO is used as a compensator to further enhance the robustness of the speed loop and attenuate sliding mode chattering. Finally, simulation and experimental results show that the proposed method can effectively improve the dynamic performance and robustness of the PMSM speed control system. [ABSTRACT FROM AUTHOR]

This article addresses a trajectory tracking control problem concerning an autonomous underwater vehicle's pitch and yaw channel dynamics in the presence of model uncertainties, underwater disturbances, and input saturation. Three different observers are introduced to estimate unknown state variables: a Luenberger‐type cubic observer, a sliding mode observer, and a high‐gain observer (HGO). Initially, a backstepping controller is employed to tackle the tracking problem, extending it to incorporate backstepping sliding mode control (SMC). The mentioned observers are utilized in both aspects of the controller design. Our proposed control law assesses trajectory tracking performance by introducing virtual control inputs, with the sliding surface designed to guide the current state variables toward approximating the virtual state variables. By combining backstepping and SMC, ensure that the state variables of the closed‐loop system converge to the desired state using the HGO. A rigorous analysis is incorporated to validate the robust performance of our proposed control law under conditions of model uncertainties and underwater disturbances. Furthermore, the control law is extended for anti‐windup compensation, mitigating adverse effects on stern and rudder plane saturation levels. Lyapunov stability theory is adopted to establish the stability of the closed‐loop system. Our simulation results convincingly demonstrate the effectiveness of the HGO‐based backstepping SMC law compared to alternative control approaches. [ABSTRACT FROM AUTHOR]

Wind energy systems are pollution free and clean form of the renewable energy production. The dynamic model of a wind turbine system based on a doubly fed induction generator (DFIG) is exposed to external disturbances, uncertainties, and nonlinear dynamics. In this paper to ensure the system robustness against external disturbance and uncertainty in system parameters, a novel optimized fractional order robust adaptive sliding mode controller is proposed by utilizing a disturbance observer. The controller's main goal is to track the maximum power point of the wind turbine. In order to show the superiority of the proposed method, the results under normal conditions and in the presence of disturbance and uncertainty have been compared with the classical sliding mode control (SMC) and adaptive sliding mode control (ASMC). The parameters of all three controllers have been optimized by ant colony optimization (ACO) algorithm. The proposed method does not need the knowledge of the upper bounds of model uncertainty and disturbance. Also by using the fractional order operators in the control signal of the proposed method, its robustness against model uncertainty and disturbance is increased and it can extract the maximum power than the other compared methods. [ABSTRACT FROM AUTHOR]

This paper proposes a chattering reduction using improved switching functions in the sliding mode control (SMC) method for battery chargers of personal mobility devices (PMDs). The battery charger of PMDs requires a controller to convert various voltage levels. The PI controller is commonly used, however, tuning the gain is necessary to improve responsiveness, which can result in overshoot. The SMC method has robust characteristics, being resilient to disturbances and ensuring stability without causing overshoot compared a PI controller. The switching function is important in the main operations of the SMC. The gain and type of the switching function can significantly influence the response at which the control variable converges to the origin. In addition, the occurrence of chattering, which can adversely affect the lifespan and stability of battery charger of PMDs. Therefore, this paper compares different switching functions used in the SMC method and identify the most suitable switching function for battery charger of PMDs. The validity of chattering reduction using improved switching functions in the SMC method for battery chargers of PMDs is verified by the simulation and experimental results.

Sliding mode control is a promising approach for designing controllers for systems with empirical characteristics. This is a favored nonlinear control strategy that effectively addresses the uncertainties present in derived mathematical models. To further enhance the stability of such systems, an Adaptive Neuro Fuzzy Inference System is employed by adapting to dynamic changes and inconsistent correlations between excitation and response. In this study, Sliding Mode Control was deployed in the feedback loop, effectively serving as a state feedback controller based on a nonlinear control law. As a two-parameter control approach, Sliding Mode Control requires careful tuning to achieve optimal performance. The integration of the Adaptive Neuro-Fuzzy System aims to bestow the two parameters of Sliding Mode Control with the ability to rapidly reduce errors to zero, thereby enhancing overall control efficiency. The research focuses on utilizing an Adaptive Neuro Fuzzy Inference System to implement Sliding Mode Control for a DC servo system while emphasizing state feedback control. The Harmony Search Optimization method is employed to optimize controller parameters effectively. The results of the research demonstrate the achievement of a best-fit value, where the minimal standard error and Best fitness are considered. This highlights the successful integration of the proposed control strategy and validates its effectiveness in providing accurate and reliable control of the real-time DC servo system.

Three-phase, three-level Vienna rectifiers are widely used in power supplies for the advantages of high power density, low switching voltage stress and low grid side current harmonics. However, due to the presence of positive and negative sequence components under the unbalanced weak power grid, the control structure using the traditional proportional integral (PI) control is complicated and requires decoupling and multiple coordinate transformations, and it has longer dynamic response time. This paper presents an unbalanced current control strategy that combines improved sliding mode control (SMC) with new reaching law and multi proportional resonance (MPR) control of Vienna rectifier under unbalanced weak power grid. This paper establishes the mathematical model of Vienna rectifier under unbalanced weak current network. In the $\alpha \beta $ coordinate system, dual second-order generalized integrator (DSOGI) is used to separate the positive and negative sequence components of the voltage. Suitable sliding mode surfaces and sliding mode convergence laws were designed. Finally, the results of simulations and experiments were used to verify the effectiveness of the proposed method.

This paper proposes a control method for a Rear Wheel Steering (RWS) system aimed at improving both the sway stability and maneuverability of vehicles equipped with trailers. A total of three control methods were designed and their performance was compared. The first method involves controlling the yaw rate of the tractor similar to conventional lateral stability control. The second method directly controls the hitch angle, utilizing the Sliding Mode Control (SMC) method. The third method controls the yaw rate similar to the first method. However, the approach to determining the target yaw rate differs from that of the first method. Each control method consists of the same three modules: the target motion module, the controller module, and the distributor module. The performance of these control methods was validated through simulations using MATLAB/Simulink and CarSim vehicle dynamics software. Simulation results showed that while the first method improved sway stability compared to no control, it had limitations compared to other methods. The second method excelled in sway stability but compromising maneuverability, resulting in unfavorable trajectory tracking in simulations. The third method demonstrated superior performance in both sway stability and maneuverability.

With the increasingly widespread application of permanent magnet synchronous motors (PMSMs), it is required that PMSMs can still maintain high efficiency and high reliability in complex environments. Due to the nonlinearity of PMSMs and the influence of external disturbances, its precise control is still a challenge. As a modern control scheme, sliding mode control can improve the control PMSM drive system. It has been successfully applied in the control of PMSMs and has become a hot spot in the motor drive system. This paper provides an overview of the current research status of sliding mode control strategies based on PMSMs and introduces the design of sliding mode controllers, as well as the development and application of high-order sliding mode control. The method of suppressing the chattering problem is summarized, and the deficiencies of it are put forward. Finally, the development trend of sliding mode control technology is discussed, and the future development direction of SMC for PMSM is prospected.

Medium Voltage DC (MVDC) integrated power systems are anticipated to feed the submarines and surface combatants. The MVDC based power systems use dc/dc converters tightly regulated via high bandwidth controllers act as constant power loads (CPL’s). The negative incremental impedance of the CPL’s may result in voltage instability in the system under disturbance. Thus for the efficient and robust control of the MVDC based power system, this paper proposes a high order sliding mode control (HOSMC) paradigm based on model-free adaptive super twisting sliding mode control (ASTA-SMC). This paper initially designs a first-order sliding mode control (FOSMC) and super twisting sliding mode control (STA-SMC) based on HOSMC DC link voltage controllers. The difficult task of gain tuning in timely varying conditions is resolved by incorporating adaptive control to STA-SMC. The proposed controller is validated and compared with pre-presented control schemes under two test cases using simulation and experimental workbench carried out in dSPACE based hardware in the loop (HIL) workbench. The adaptive STA-SMC (ASTA-SMC) is compared with FOSMC and feedback linearization-based control schemes. The stability of ASTA-SMC in finite time is validated using the Lyapunov stability theorem.

This paper presents novel chattering-free robust control strategies for addressing disturbances and uncertainties in a two-degree-of-freedom (2-DOF) unmanned aerial vehicle (UAV) dynamic model, with a focus on the highly nonlinear and strongly coupled nature of the system. The novelty lies in the development of sliding mode control (SMC), integral sliding mode control (ISMC), and terminal sliding mode control (TSMC) laws specifically tailored for the twin-rotor MIMO system (TRMS). These strategies are validated through both simulation and real-time experiments. A key contribution is the introduction of a uniform robust exact differentiator (URED) to recover rotor speed and missing derivatives, combined with a nonlinear state feedback observer to improve system observability. A feedback linearization approach, using lie derivatives and diffeomorphism principles, is employed to decouple the system into horizontal and vertical subsystems. Comparative analysis of the transient performance of the proposed controllers, with respect to metrics such as settling time, overshoot, rise time, and steady-state errors, is provided. The ISMC method, in particular, effectively mitigates the chattering issue prevalent in traditional SMC, improving both system performance and actuator longevity. Experimental results on the TRMS demonstrate the superior tracking performance and robustness of the proposed control laws in the presence of nonlinearities, uncertainties, and external disturbances. This research contributes a comprehensive control design framework with proven real-time implementation, offering significant advancements over existing methodologies.

The dynamic model of mobile wheelchair technology requires developing and implementing an intelligent control system to improve protection, increasing performance efficiency, and creating precise maneuvering in indoor and outdoor spaces. This work aims to design a robust tracking control algorithm based on a reference model for operating the kinematic model of powered wheelchairs under the variation of system parameters and unknown disturbance signals. The control algorithm was implemented using the pole placement method in combination with the sliding mode control (PP-SMC) approach. The design also adopted a neural network approach to eliminate system uncertainties from perturbations. The designed method utilized the sinewave signal as an essential input signal to the reference model. The stability of a closed-loop control system was achieved by adopting the Goa reaching law. The performance of the proposed tracking control system was evaluated in three scenarios under different conditions. These included assessing the tracking under normal operation conditions, considering the tracking performance by changing the dynamic system's parameters and evaluating the control system in the presence of uncertainties and external disturbances. The findings demonstrated that the proposed control method efficiently tracked the reference signal within a small error based on mean absolute error (MAE) measurements, where the range of MAE was between 0.08 and 0.12 in the presence of uncertainties or perturbations.

The systems that use parallel kinematic structures in additive manufacturing technology are particularly notable for their ability to provide exceptional precision and efficiency in the fabrication of intricate geometrically shaped items. This study introduces a novel system paradigm with five degrees of freedom, specifically developed to tackle existing additive manufacturing issues. In the proposed design, by incorporating rotational motions along the x and z axes, contributions were added to the efficiency of typical three-degrees-of-freedom (3-DOF) systems, resulting in a total of five degrees of freedom. In this way, it is aimed at increasing product durability, improving surface integrity, and saving production time. In this study, the conceptual design of the system was defined. Mathematical analyses were then used to determine the kinematic and dynamic models of the system, and a proposed model-based control technique was revealed. To evaluate the axis movement performance of the system, two different control techniques were used, and real-time test studies were conducted. The first control technique was the proportional–integral–derivative (PID) controller, and the second method was the sliding mode control (SMC) method, which was used to increase the performance of the system during trajectory tracking. The experimental results showed that the SMC method provides a reasonably good trajectory tracking response and a steady-state error compared to the classical PID controller. [ABSTRACT FROM AUTHOR]

In this study, dissipative filtering of Markovian jumping systems (MJSs) is investigated using the sliding mode control (SMC) method. A novel dynamic model considering linearity and nonlinearity was proposed, and an adaptive sliding motion controller was established to study the dissipation and mean-square exponential stability. First, MJSs with time-varying delays are proposed, which involve known and unknown nonlinear functions. Subsequently, a novel sliding mode surface (SMS) function was constructed to ensure that the trajectory of the sliding motion dynamics could move along the SMS. In addition, an appropriate SMC rule was presented to guarantee SMS accessibility. Second, the filter was obtained through dissipation theory, which ensures that the filtering error system is extended-dissipative and the mean-square is exponentially stable. Finally, the effectiveness of this method was verified using a practical example. [ABSTRACT FROM AUTHOR]