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The paper studies the design of interval observer–based event-triggered H ∞ controller for switched systems with frequent asynchronism. We first propose an interval observer–based event-triggered mechanism, which is used to transmit the observer states and the activated mode information for controller updating. Then, we design an interval observer–based event-triggered H ∞ controller for the considered systems. By using the controller mode–dependent Lyapunov function method, sufficient conditions for the globally exponential stability of the closed-loop switched systems are obtained under average dwell time switching law. Moreover, we prove that the interevent interval length is a positive constant, which can exclude the Zeno behavior. Compared with the literature, the paper removes the strict requirement of at most one switch between two event-triggered instants, that is, frequent switches within an interevent interval are allowed. Finally, a numerical example is given to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper considers the adaptive guaranteed cost tracking (AGCT) control problems for two classes of high-order nonlinear systems with unknown parameters. A new local smooth nonlinear function (LSNF) is introduced first, which provides an important mathematical tool for our controller design. Then, based on the LSNF and the high-order fully actuated (HOFA) system approaches, the AGCT controller is designed for HOFA system with unknown parameter, which guarantees that all of the states of the closed-loop HOFA system are globally bounded, and the tracking error is asymptotically convergent. Moreover, the upper bound of cost function (UBCF) characterizing the tracking performance can be arbitrarily preseted, and is completely independent of the system initial value and the unknown parameter, which significantly improves the tracking performance, and is difficult to achieve by using existing guaranteed cost control (GCC). Furthermore, an extra result, the AGCT controller for a class of strict-feedback systems with high-order form and unknown parameters, is obtained in this paper, which also guarantees that the system tracking error is globally asymptotically convergent with the arbitrarily preseted UBCF characterizing the tracking performance. Three simulation examples, including an inverted pendulum, are presented to show the effect and the superiority of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, an optimal extended state observer (ESO) is designed for nonlinear integral chain system. For the first time, in this paper, proportional–integral (PI) extremum seeking control (ESC; PIESC) approach is applied to design a perturbation observer by minimizing the estimation error. The PI type structure of the ESC provides fast transient response for the closed-loop system to attain optimum equilibrium point. A mathematical proof is presented to show that the average error dynamic asymptotically converges to zero while the estimation error is minimized. The simulation results verify that the estimation error achieved by the proposed PIESC-based ESO (PIESC-ESO) is found significantly less than that achieved by the classic ESO and PSO-based ESO. Moreover, if slow changes occur within the system or external to it, the PIESC-ESO is still able to modify the observer gains such that the estimation error is minimized again. Therefore, this may help PIESC-ESO to be used in practical applications. [ABSTRACT FROM AUTHOR]

This paper tackles the problem of trajectory tracking for wheeled mobile robots subject to time-varying input delay and bounded external disturbances. First, we establish a dynamic model for a wheeled mobile robot under sliding and skidding conditions, and determine the maximum allowable input delay that maintains system stability using Razumikhin-type stability analysis without prior knowledge of the variation in delay. The proposed adaptive robust controller combined with super-twisting sliding mode control is resilient to disturbances such as input delay, system uncertainty, and parameter variation. The proposed adaptive law enables real-time modification of switching gain based on tracking error without predefined knowledge of uncertainty bounds. Compared with traditional sliding mode control strategies, the super-twisting algorithm can eliminate chattering phenomenon while combined robust methods further reduce modeling uncertainties' influence on system performance. Finally, we select an appropriate Lyapunov function to analyze and prove uniformly ultimately bounded of the closed-loop system. MATLAB simulation comparison results demonstrate that this approach achieves high tracking accuracy, faster response speed, and robustness. [ABSTRACT FROM AUTHOR]

This paper studies the event-triggered control for uncertain switched systems under injection attacks. An adaptive event-triggered control method for neural network–approximated switched systems (NNA-SSs) is proposed. The main works are as follows: First, a neural network is introduced to approximate the uncertain nonlinear item of the systems. Second, the observer-based adaptive event-triggering (OB-AET) strategy is designed to efficiently utilize communication and computing resources. Furthermore, the closed-loop switched systems considering injection attacks are established. By utilizing the Lyapunov function method and average dwell time technique, sufficient conditions for the exponential stability of the closed-loop switched systems are given. Accordingly, the gains of the state feedback controllers and observers are solved. Finally, simulation examples are given to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper studies the exponential finite-time formation problems for a group of locomotive agents that maintain order on a circle. In an ideal environment, that is, without external disturbances, a combined protocol with linear continuous-time states and their nonlinear continuous functions is proposed. Each agent can adjust the movement speed itself by changing the exponent of the nonlinear function. The obtained closed-loop system will converge with an exponential speed when the initial states of the agents are far from the target location, and with a finite-time speed nearby. For the case with external disturbances, a combined protocol with linear continuous-time states and their sign functions is presented. Due to the discontinuity of the sign functions, the Filippov solutions are employed. The exponential finite-time circle formation will be achieved even in the existence of external disturbances. Moreover, the above result is extended to the application in circle containment, where the defenders will form a circle formation to surround the swarm of protectees. Finally, several computational simulations illustrate the validity of the proposed protocols. [ABSTRACT FROM AUTHOR]

For systems with higher control accuracy requirements, the requirements for convergence time are also higher, such as requiring the system to maintain stability in a finite time. This paper studies the finite-time control for input-saturated system based on the event-triggered strategy and the parametric Lyapunov equation. A finite-time state feedback controller and a finite-time output feedback controller are designed by introducing a time-varying parameter which can be obtained by solving a differential equation. The proposed methods make the closed-loop system stable in finite time and save the system resources. The designed controller overcomes the problem of slow convergence speed caused by low-gain feedback control. The numerical simulation results demonstrate the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

This paper is devoted to adaptive trajectory tracking of quadrotor systems with full-state constraints and random disturbances. The command-filtering technology combined with error compensation mechanisms is proposed to deal with the "explosion of complexity" problem in traditional backstepping design and reduction of the filtering errors. The Barrier Lyapunov functions (BLFs) are constructed to ensure that all system states do not violate the boundary of its constraints. The command-filtered adaptive fuzzy controller is designed such that the state constraints are not breached almost surely, all signals in the closed-loop system are bounded almost surely, and the first-order moment of the tracking error converges to an arbitrarily small neighborhood of zero by parameters tuning. Finally, the effectiveness of the proposed control method is illustrated by simulation results. [ABSTRACT FROM AUTHOR]

This paper proposes an event-triggered model predictive-preview control strategy for autonomous vehicle trajectory tracking. First, the dynamic equation is established based on the preview road curvature and the vehicle's 2 degree-of-freedom relationship. A model predictive tracking controller is designed by predicting the system dynamics in the future. Second, to reduce the computational burden of the controller, the triggering conditions are designed according to the system's stability and feasibility. The proposed event-triggered model predictive-preview control strategy not only makes the autonomous vehicles maintain tracking accuracy but also reduces the number of online optimization. Then, asymptotically stable of closed-loop systems are proved by using Lyapunov's theorem. Finally, simulation experiments show that the proposed strategy has some advantages over traditional model predictive control in terms of improving vehicle tracking accuracy and reducing algorithm complexity. [ABSTRACT FROM AUTHOR]

This paper proposes a novel approach to design a centralized model matching integer/fractional-order (FO) controller for multivariable processes. As a first step, for a linear time-delay process, a desired closed-loop reference model is formulated with the inclusion of a linear quadratic regulator with integral controller. The reference model is formulated with the objective of embodying the desired closed-loop specifications. The second step involves equating the closed-loop system with the reference model, leading to a synthesis equation that yields a higher-order controller. In the third step, the lower-order approximant of the controller is obtained by matching a set of approximate generalized time moments/approximate generalized Markov parameters of the higher-order controller to that of its lower-order approximate at a few expansion points in the s-plane. The selection of an optimal set of expansion points is formulated in an optimization problem frame with the aim of minimizing the area between responses of the desired and designed closed-loop systems, keeping the stability of the designed closed-loop system as a constraint. The efficacy of the proposed approach is illustrated by the design of different controllers for time-delay-dominated nonsquare process and FO square process. Comparative analysis is carried out using time-domain performance indices by introducing parameter uncertainty and disturbance signals. To demonstrate the applicability of the proposed method, a real-time investigation is carried out with the design and implementation of a controller for interacting hybrid (conical and spherical) tank process setup. [ABSTRACT FROM AUTHOR]

Unknown actuator failures are inevitable in practical systems. At the same time, time delay exists in many physical actuators, and the system performance will be affected by such actuator delay and faults. However, the results of studies that attempt to compensate for unknown failures of actuators with time delay are still very limited. In this paper, such a problem is studied, and an adaptive control scheme is proposed based on backstepping approaches. First, the input delay of actuator faults and output disturbances are transformed into unknown effects on the output signal. In the backstepping recursive design, these unknown effects will accumulate to the last step of the controller design. Then, a new Lyapunov function is constructed by introducing auxiliary signals to prove the stability of the system. It is shown that the proposed control scheme can compensate for the effects caused by unknown actuator failures and input delays. The stability of the closed-loop system can be guaranteed by this adaptive controller. Finally, simulation studies are used to verify the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

This paper is concerned with the event-triggered control of switched two-dimensional (2D) continuous-discrete systems in Roesser model. A more general event-triggered scheme is proposed to reduce unnecessary resource waste and data redundancy, where a weighing coefficient and multiple parameter matrices are used. Based on the proposed event-triggered mechanism, a state feedback controller and a state-dependent switching signal are proposed. By using the multiple Lyapunov function method, sufficient conditions for the exponential stability of the closed-loop system are derived in terms of linear matrix inequalities. Finally, two examples are provided to illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, a fixed-time sliding mode control scheme is developed to fulfill the trajectory tracking task of a marine surface vehicle with unknown dynamics. To restrain the adverse effects of the unknown dynamics including the parameter inaccuracy and exogenous disturbances, a fixed-time disturbance observer is designed to estimate the lumped uncertainties using the bi-limit homogeneous theory without requiring any knowledge of the model uncertainties. Then, a nominal tracking controller is proposed to stabilize the error dynamic model in the sense of fixed-time Lyapunov stability, based on which a novel integral-type sliding mode manifold with bi-limit homogeneity is constructed to drive tracking error convergence in fixed time. To enhance the robustness of the vessel control system, a disturbance observer–based fixed-time integral sliding mode tracking controller is finally proposed, and the chattering phenomenon is effectively alleviated by direct estimation compensations. The analysis of Lyapunov stability indicates that the closed-loop system is fixed-time stable. Numerical simulations on a model vessel are carried out to validate theoretical results of the proposed control scheme. [ABSTRACT FROM AUTHOR]

This paper investigates the adaptive control for a class of constrained stochastic nonlinear systems with parametric uncertainty and input saturation. Based on a novel radial basis function neural networks (RBF NNs), the nonlinearities are tackled without the prior knowledge of NN nodes and weights. The approximate coordinate coordination is combined with an auxiliary system to attenuate the effects generated by input saturation. Then, an opportune backstepping design procedure is presented using the barrier Lyapunov function (BLF) and RBF NN. Based on this design procedure, an adaptive state–feedback controller is constructed, which makes the closed-loop system semi-globally uniformly ultimately bounded, the tracking error bounded in a compact set of the origin, and the full-states not violated. Finally, a stochastic single-link robot arm system is simulated to demonstrate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

In this paper, a control-error-based decentralized neural network (NN) direct adaptive controller is presented for uncertain interconnected nonlinear systems, in strict-feedback form, subject to input saturation and external disturbances with unavailable states for measurement. Different from the existing results in the literature, the proposed approach is based on the control error instead of the tracking error resulting in a separation-like principle. Furthermore, the explosion of complexity due to back-stepping recursive design is completely avoided along with discarding all restrictive assumptions imposed on the unmatched interconnections. Actually, NNs are used to approximate the unknown ideal control laws, and auxiliary control terms are appended to deal with approximation errors and enhance the stability of the closed-loop system. Besides, fuzzy inference systems are introduced to estimate the unknown control errors, leading to simplified derivation of adaptive laws. Thanks to the strictly positive real (SPR) property, the tracking errors are proved to converge asymptotically to zero using Lyapunov theory, which is superior to bounded stability results usually found in the literature. Simulation results show the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper is focused on asymptotic tracking control of electro-hydraulic actuator (EHA) systems subject to matched and mismatched time-varying disturbances. To counteract the matched disturbance, a novel extended state observer (ESO) is proposed to achieve asymptotic convergence of the estimation error, by incorporating the strictly positive real (SPR) Lyapunov design method and a Nussbaum function. To further suppress the mismatched disturbance, an adaptive robust integral of the sign of the error (RISE) controller is formulated in the backstepping framework based on the proposed ESO. Asymptotic tracking performance is theoretically achieved via closed-loop system stability analysis. The efficacy of the proposed control scheme is verified through comparative experiments executed on an EHA test rig. In this study, a priori bounds of the disturbances and their higher-order derivatives are no longer needed, and only one auxiliary error signal is introduced. This approach loosens the restrictions on the disturbances and reduces the design conservativeness, thus making it promising in practice. [ABSTRACT FROM AUTHOR]

In this paper, a recursive d -step-ahead predictive control scheme based on multi-dimensional Taylor network (MTN) is proposed for the real-time tracking control of multiple-input multiple-output (MIMO) nonlinear systems with input time-delay. The MTN predictive model is designed using a recursive approach to compensate the influence of time-delay, and an extended Kalman filter (EKF) is applied as its learning algorithm. An MTN controller is developed based on a proportional–integral–derivative (PID) controller where the closed-loop errors between the reference input and the system output are set as the MTN controller's inputs. Then, a back propagation (BP) algorithm, designed to update its weights according to errors caused by system uncertainty, is used as a learning algorithm for the MTN controller. Meanwhile, the convergence of the MTN predictive model and the stability of the closed-loop system are evaluated. Two numerical examples and a practical example – continuous stirred tank reactor (CSTR) process are presented to verify the superiority of the proposed scheme. The experimental results and the computational complexity analysis show that the proposed scheme is effective, promising its desirable robustness, anti-disturbance, tracking and real-time performance. [ABSTRACT FROM AUTHOR]

This paper researches the interval observer–based event-triggered control of switched linear parameter-varying (LPV) systems, which involve unknown external disturbance and measurement noise. First, we offer an event-triggering condition and a controller which are correlated with state estimations. Then, by analyzing the relationship between switching sequences and sampling sequences, we model the resulting systems as switched time-delay systems. It deserves to note that the mismatches of the switching signal for the controllers and the systems may occur due to the sampling of switching signal. Using the merging switching signal technique and the multiple Lyapunov–Krasovskii functional method, and thinking over both synchronous and asynchronous switching of the systems and the controllers, we acquire relevant conditions which are used to realize the stability of the whole switched LPV closed-loop systems under the mode-dependent average dwell time (MDADT) switching. Next, we give a specific algorithm to design the controller gains. Finally, a numerical example is provided to verify the superiority of the outcomes. [ABSTRACT FROM AUTHOR]

Driven by the increasing industrial demands for process safety and product quality, this paper is devoted to operational performance monitoring and performance degradation recovery for closed-loop control systems under abnormal working conditions. To this end, a new operational performance indicator is designed and its benchmark with an explicit sensitivity criteria for selecting historical data, to detect the system degradation timely and accurately. Then, by embedding the operational performance indicator as a trigger condition, a data-driven performance degradation recovery method with the aid of iterative adaptive dynamic programming (ADP) algorithm is investigated. This implementation shows that iterative ADP can be applied efficiently by utilizing both value iteration and measurement data to recover the anomaly induced system performance degradation. Finally, a case study on the continuous stirred tank reactor system is provided to validate the effectiveness of these proposed methods. [ABSTRACT FROM AUTHOR]

In this paper, trajectory tracking control of an underwater vehicle in three-dimensional (3D) space has been addressed. The assumed underwater vehicle has 6 degrees of freedom and the aim is to control all system rotations and displacements. In this paper, a finite-time sliding mode controller as a robust control method is proposed for an underwater vehicle with 6 degrees of freedom in 3D space using the method without simplifications or decouplings. Therefore, both system positions and orientations are controlled in the presence of disturbances and uncertainties. In previous research works, control of two-dimensional underwater vehicles is commonly studied. In this paper, a novel stable control algorithm is proposed for an underwater vehicle with 6 degrees of freedom. The stability of the closed-loop system is analyzed using the Lyapunov theory. The designed algorithm can cover 3D complicated tasks. Also, the designed algorithm as a robust control approach can attenuate external disturbances. The performance and stability of this approach are compared with the sliding mode controller. The numerical comparison results show that the proposed approach is effective and applicable in practice. [ABSTRACT FROM AUTHOR]

In this paper, to address the periodic control problem facing high-precision observation for multibody rotating scan optical spacecraft connected with active magnetic bearing (AMB), the Unscented Kalman Filter (UKF)–based iterative learning controller (UILC) is proposed. In the UILC, an adaptive backstepping controller (ABC) is deployed in the main loop to make the system state converge, and an UKF module is substituted for the memory module to use feedback information in real time and eliminate error propagation between adjacent periods. In the paper, the 9 degrees of freedom (DOF) error discrete dynamics are first derived to facilitate the convergence proved in the discrete domain. Then, the convergence analysis of the closed-loop system is investigated, and the state error supremum of closed-loop system in the mean square is indicated. Finally, for a comparison with the classical iterative learning controller (ILC), a series of numerical simulations are performed. As indicated by the simulation results, the UILC is capable of eliminating periodic deviation and error propagation during the adjacent periods. [ABSTRACT FROM AUTHOR]

This paper introduces an H ∞ robust constrained event-triggered fuzzy controller for discrete-time nonlinear systems in the presence of system parameter uncertainties, the parameter uncertainties of the output matrices and the disturbances, simultaneously. To reduce the communication resources and improve the robust performance, the event-triggered mechanism is incorporated with the H ∞ robust fuzzy controller design. Moreover, by employing the fuzzy modeling of the actuator saturation and a nonquadratic Lyapunov function (NQLF), the ultimate bounded stability (UBS) of the closed-loop system is guaranteed subject to the amplitude limitations of the control signal. This means, a new linear matrix inequality (LMI) problem is derived to ensure the robustness and constraints in an offline scheme based on the event-triggered strategy. Besides, to meet the practical problem to further improve the controlled system performance, the control input rate constraint is also considered and a new LMI condition is provided with no online computational burden. Therefore, the computational burden of the proposed controller is greatly reduced with less conservatism. Two simulation examples including a numerical dynamic system and a truck–trailer system are employed to illustrate the less conservatism and computational complexity of the proposed method compared with the existing approaches. [ABSTRACT FROM AUTHOR]

To overcome the mutual constraints between the system chattering and the arrival time in conventional sliding mode control in this paper, a tangent excitation function (tansig) type nonlinear extended state observer (NLESO)-based integral terminal sliding mode control is proposed to solve the trajectory tracking control task of the modular robot manipulators (MRMs) possessing strong coupling and complex time-varying properties. Through the joint torque feedback technology, the MRM system dynamic model is formulated; on this basis, the proposed NLESO based on tansig is utilized to estimate and compensate the system uncertain information, which are consisted of the friction, interconnected dynamic coupling, and external disturbance. The proposed NLESO can simplify the traditional extended state observer design parameters for theoretical analysis and practical application. The proposed tansig-type NLESO-based integral terminal sliding mode control integrated adaptive term exponential reaching law for MRMs is designed to diminish the arrival time when the system state converges to the equilibrium point. The presented algorithm improves the robotic system antidisturbance ability. Furthermore, the Lyapunov theory is utilized to verify stability of the proposed NLESO and closed-loop robotic system. Finally, the availability of the proposed algorithm is demonstrated by experiments. [ABSTRACT FROM AUTHOR]

This paper studies a novel method of the dynamic event-triggered mechanisms and the predictive control scheme for discrete-time networked linear systems subject to network delays and DoS attacks in both sensor-to-controller (S − C) and controller-to-actuator (C − A) channels. First, by assuming maximum allowable duration of DoS attacks, predictive control scheme is used to proactively offset the adverse impacts of communication constraints. Second, to further save communication resources, dynamic event-triggered mechanisms are configured on sensor and controller sides, respectively. Next, sufficient condition is derived for discrete-time networked linear systems under predictive control and dynamic event-triggered mechanisms, which guarantees the resulting closed-loop system's asymptotical stability. Finally, a simulation example is used to confirm the availability and applicability of the proposed method. [ABSTRACT FROM AUTHOR]

This paper focuses on the mixed H ∞ and passive resilient control problem for uncertain discrete-time networked control systems subject to time delays. The measurement output is considered to be quantized by the dynamic quantizer before transmission through an unreliable communication channel, where the deception attacks may occur randomly. To further reduce the communication burden, the Round-Robin (RR) protocol is adopted to schedule sensors in a predetermined transmission order. Meanwhile, a new performance index is developed to solve restriction of the same dimension of control output and the exogenous disturbance. The S-procedure combined with a two-step uncertainties elimination method is adopted to deal with the nonlinear product terms involving multiple uncertainties. Furthermore, a decoupling method is introduced for static output feedback controller design. Sufficient conditions of the resilient controller and the dynamic quantizer are provided, which can improve the robustness of resulting closed-loop system and guarantee its stochastic stability and the specified mixed H ∞ and passivity performance index. Finally, an example is given to illustrate the feasibility of the theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, a linear matrix inequality (LMI)-based design is proposed for the passivity-based output feedback control problem of fractional-order static neural networks (FOSNNs). Different from the current works, the studied model is the static fractional-order neural network. The novel convex Lyapunov function is constructed to obtain new conditions for the existence of output feedback controllers which guarantee the closed-loop systems are passive. In addition, we also extend the obtained results to generalized fractional-order neural networks. A numerical example is presented to verify the proposed results. [ABSTRACT FROM AUTHOR]

In this paper, an event-triggered control mechanism scheme based on dynamic surface control and adaptive dynamic programming (DSC-ETCADP) is proposed for optimal trajectory tracking of the unmanned surface vessel (USV) with input constraints. First, the control structure is designed using dynamic surface control (DSC) as feedforward control and adaptive dynamic programming as feedback control, which not only ensures the tracking of reference trajectory but also improves the control accuracy. Second, due to the data-driven nature of adaptive dynamic programming (ADP) and the ability to adjust parameters online, it can be solved by USV with unknown disturbance. Third, the event-triggered mechanism can save computation and reduce the number of executions of the controller, in addition to avoiding Zeno behavior. Finally, according to the Lyapunov stability theory, all signals in the closed-loop system are globally uniformly and ultimately bounded (UUB). The DSC-ETCADP scheme is compared with DSC method. Simulation results demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Time-delay systems are widely used in industrial applications, such as chemical process and aerospace. The predictor-based feedback method is one of the effective ways to deal with such systems. This paper studies the delay compensation problem for linear systems with multiple distributed input delays. A novel state vector associated with the future state of the system is constructed, which reduces the original linear time-delay system to a linear delay-free system. Memory feedback controller is then designed, and necessary and sufficient conditions for the stability of the closed-loop system are acquired in accordance with the stability of an integral delay system. To avoid the difficult implementation problem of memory feedback controller, the memoryless feedback controller is proposed instead to compensate the multiple distributed input delays. Finally, the proposed controllers are applied to the design of the linearized liquid-level control resonant circuit system. [ABSTRACT FROM AUTHOR]

This paper considers the problem on tracking control for the medium-scale unmanned autonomous helicopter (UAH) system under external disturbances, actuator faults, and full state constraints. In comparison with existing results, this paper does not only consider asymmetric state constraints but also jointly take the faults and disturbances into account on the UAH system, estimating and compensating for them separately, which can effectively enhance the tracking performance. First, the dynamics of nonlinear UAH system is divided into the position subsystem and the attitude one. Second, an improved barrier Lyapunov function (BLF) is constructed to handle the problem of asymmetric state constraints. Third, in order to estimate the external disturbances and actuator faults, two coupled generalized proportional integral observers (GPIOs) and two fault estimators are designed, respectively. Fourth, based on above estimations, improved BLFs, and backstepping method, two tracking control laws for the position and attitude loops are presented and an overall closed-loop system is established. Then, a sufficient condition ensuring uniform boundedness of tracking and estimation errors is derived. Finally, some simulating results demonstrate the effectiveness and advantage of the proposed control scheme. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of resilient adaptive event-triggered control (AETC) for networked stochastic control systems (NSCSs) in the presence of the external disturbance and the energy-constrained, nonperiodic denial-of-service (DoS) attacks. A novel adaptive event-triggered scheme (AETS) that considers the effect of the energy-constrained, nonperiodic DoS attacks on the communication network is proposed to reduce the usage of system resources and adapt the variation of the plant state, and the model of closed-loop control system is established in the framework of time-delay systems and switched systems. Then, based on the Lyapunov stability theory, the stability criterion and the co-design algorithm are derived, which are used to ensure that the closed-loop control system is stochastically exponentially stable (SES) with an H ∞ disturbance attenuation performance and to implement the co-design of state-feedback controller and proposed AETS, respectively. Unlike the network-based H ∞ control approach for NSCSs in the existing literature, the resilient adaptive event-triggered network-based H ∞ control approach proposed in this paper not only can considerably save the usage of system resources, but also can be resilient towards the energy-constrained, nonperiodic DoS attacks. Finally, a resilient AETC for the F16 aircraft system shows the effectiveness and superiority of proposed strategy. [ABSTRACT FROM AUTHOR]

Considering the problems of unknown external disturbances and parametric uncertainties in trajectory tracking of a quadrotor, a backstepping control method based on time-varying threshold event-triggered extended state observer (TETESO) and a nonlinear differentiator with lead compensation is proposed in this paper. First, to facilitate the controller design, the quadrotor system is divided into the position subsystem and the attitude subsystem, which are transformed into the original cascaded dynamics. Second, a TETESO which can observe the unmeasurable states and the total disturbance as well as reduce the unnecessary communication resources between sensor and observer is proposed. It is proved that the observation errors are bounded, and Zeno behavior is avoided. Third, a new controller synthesized by the proposed TETESO and the backstepping control method is designed for the position subsystem and the attitude subsystem. To address the "differential explosion" problem in the backstepping control method, a nonlinear differentiator with lead compensation is used to compute the derivative of desired attitudes in the controller. Moreover, the stability analysis of the closed-loop system is proved and the proposed controller can ensure the ultimate boundedness of all signals. Finally, the effectiveness and superiority of the proposed control method are verified by simulation. [ABSTRACT FROM AUTHOR]

In this paper, a new approach for stochastic logarithmic variable structure control has been proposed to create a compromise between reaching phase duration and response rate of the stochastic suspension system. The asymptotic stability with probability one for the closed-loop suspension system has been analyzed by Lyapunov method. Some practical considerations in proving theorems are uncertain parameter variations, environmental matched disturbances, actuator degradation, stochastic environmental mismatched disturbances, which is a representative of the change in road profile with time, and unmodeled dynamics. Finally, by regulating a specific parameter, the simulation results corroborate the advantage of the proposed controller in managing and reducing the sensitivity of the closed-loop system. Also, compared with other sliding surfaces of past researches, the designed sliding variable minimizes a certain performance function and therefore provides better performance for the closed-loop system, which is also verified in the simulation results. [ABSTRACT FROM AUTHOR]

In this paper, we present a parametric method to design proportional plus derivative (PD) state feedback for the problem of partial eigenstructure assignment (PESA) in a type of descriptor high-order linear time-invariant (LTI) systems. By dividing the original eigenstructure into replaced and remaining parts and using the solutions to the high-order generalized Sylvester equations (HGSEs), complete parameterized expressions of PD feedback controller and the replaced part of the right eigenvector matrix are established. With the proposed approach, the unsatisfactory eigenstructure in the open-loop system is changed into the expected eigenstructure in the closed-loop system, while the satisfactory part in the open-loop system is retained. Meanwhile, the regularity of the closed-loop system can also be well-guaranteed by the selection of arbitrary parameters. Finally, a numerical example and a flexible-joint robot system are presented to verify the feasibility and effectiveness of the proposed method, respectively. [ABSTRACT FROM AUTHOR]

In this paper, the adaptive output feedback asymptotic tracking problem is investigated for nonlinear systems with dead-zone input and unknown nonlinearities, where only system output is available. First, an observer is constructed to estimate unavailable states. Then, by the observer and barrier Lyapunov function, an adaptive output feedback controller is designed, which compensates the influence of dead-zone input and unknown nonlinearities. Furthermore, based on the proposed controller and tuning function, the global boundedness of all signals in closed-loop system is achieved, and the tracking error can asymptotically converge to zero. Particularly, it should be noted that there is no need to calculate the derivatives of virtual control laws in controller design, thus reducing the computational complexity. Finally, two numerical examples are taken to verify the effectiveness of the designed controller. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of semi-global finite-time stabilization by output feedback for a class of nonholonomic systems with both high-order and low-order nonlinearities. By using the homogeneous domination approach, a constructive design procedure for output feedback control is given. Together with a switching control scheme, the designed controller renders that the states of a closed-loop system are semi-globally regulated to zero in a finite time. A simulation example is provided to illustrate the effectiveness of the proposed approach. [ABSTRACT FROM PUBLISHER]

This paper focuses on the global stabilization problem of controlling direct current–direct current switched power converters in the presence of coil magnetic saturation. A finite-time controller is investigated for the modified nonlinear system model by utilizing an adding a power integrator technique. With the finite-time control scheme, not only a faster convergence rate is obtained, but also better suppression ability to the inevitable disturbances is achieved for the closed-loop system. Simulation comparison results show the effectiveness of the proposed method. [ABSTRACT FROM PUBLISHER]

This paper investigates the problem of adaptive control based on Barrier Lyapunov function for a class of full-state constrained stochastic nonlinear systems with dead-zone and unmodeled dynamics. To stabilize such a system, a dynamic signal is introduced to dominate unmodeled dynamics and an assistant signal is constructed to compensate for the effect of the dead zone. Dynamic surface control is used to solve the "complexity explosion" problem in traditional backstepping design. Two cases of symmetric and asymmetric Barrier Lyapunov functions are discussed respectively in this paper. The proposed Barrier Lyapunov function based on backstepping method can ensure that the output tracking error converges in the small neighborhood of the origin. This control scheme can ensure that semi-globally uniformly ultimately boundedness of all signals in the closed-loop system. Two simulation cases are proposed to verify the effectiveness of the theoretical method. [ABSTRACT FROM AUTHOR]

This paper addresses the observer-based control design for uncertain one-sided Lipschitz Markovian jump-delayed systems. By constructing the Lyapunov functional of the closed-loop augmented system, combining with the one-sided Lipschitz condition and quadratically inner-bounded condition, it is derived that the closed-loop augmented system is stochastic stable with an H ∞ performance level γ. With the help of some special derivations, bilinear matrix inequalities are successfully transformed into a group of linear matrix inequalities. The robust controller and observer gains are solved by linear matrix inequality (LMI) toolbox in MATLAB. [ABSTRACT FROM AUTHOR]

In this paper, a new adaptive fuzzy fixed-time control strategy is proposed for stochastic nonstrict nonlinear systems with Bouc–Wen type of hysteresis input and unmeasured state variables. The Bouc–Wen model is recognized as one of the most intractable mechanical hysteresis models. The established state observer is used to assess unmeasurable states, and the fuzzy logic systems are utilized to approximate the uncertain nonlinear functions in the system. Based on the state observer and backstepping method, a fixed-time controller is recursively designed to ensure that all closed-loop signals of the system are bounded and the tracking error converges to a small neighborhood of the origin within a fixed-time. Finally, the effectiveness of the control strategy is verified by two simulation examples. [ABSTRACT FROM AUTHOR]

Benefiting from the input-to-state stability (ISS) version of the Razumikhin stability theorem, this paper deals with the stabilization of continuous linear input-delay systems with state quantization and without any knowledge about the delay. An event-triggered delay independent truncated predictor feedback (ET-DITPF) controller with a switched feedback control law is proposed to guarantee the globally uniformly asymptotic stability (GUAS)/globally uniformly exponential stability (GUES) of the closed-loop system. As a prominent feature, this controller uses no information about the time delay (neither its value nor its upper bound). In the proposed event-triggered framework, a lower bound for each two consecutive events is derived to show the non-occurrence of the Zeno behavior. Numerical simulations confirm the effectiveness of the obtained theoretical results. [ABSTRACT FROM AUTHOR]

This paper addresses the design of a dynamic output feedback-based anti-windup compensator to mitigate the windup phenomenon for a discrete time-varying delayed system with input saturation to establish the asymptotic stability. Linear matrix inequalities–based stability conditions are derived locally and globally. The controller for the closed-loop system is designed to reduce the effect of external bounded disturbances by utilizing the linear matrix inequality approach. The novel triple Lyapunov–Krasovskii functional along with reciprocal convex inequality is used to solve the expressions contained in the forward difference of the functional and to maximize the basin of attraction. Finally, industrial examples are simulated to prove the effectiveness of the proposed criterion. [ABSTRACT FROM AUTHOR]

The overhead crane systems contain parameter uncertainties and external disturbances, which will affect the control performance of the systems. To overcome this problem, an interval type-2 Takagi–Sugeno (T-S) fuzzy linear quadratic regulator (LQR) approach is proposed for overhead crane system in this paper. First, an interval type-2 T-S fuzzy model is constructed based on the nonlinear dynamic model of the overhead crane system. The type-2 model can capture the system uncertainties. Second, the fuzzy LQR is designed on the basis of the fuzzy model and the asymptotic stability of the closed-loop system is analyzed using Lyapunov method. Finally, simulations and experiments are studied. The results show that the proposed method can give the overhead crane system faster trolley positioning speed, smaller load swing, and better anti-disturbance ability than the existing LQR control method. [ABSTRACT FROM AUTHOR]

In this paper, the containment control problem of a class of fractional-order nonlinear multi-agent systems is studied, in which the multi-agent system contains unmeasured states and system nonlinearity. An adaptive neural network backstepping controller combined with event-triggered mechanism is proposed to ensure all followers can converge to the convex hull spanned by the leaders. The command filter is introduced into the proposed fractional-order control system to obtain fractional derivatives for virtual control functions continuously and avoid "explosion of complexity." From the Lyapunov stability theory, all the signals can remain semi-global uniformly ultimately bounded in the closed-loop system. Numerical example and simulation results confirm the feasibility of the proposed control method. [ABSTRACT FROM AUTHOR]

In this study, a magnetic actuator is controlled to obtain a constant flow rate micropumping by a magnetic nanofluid flow inside a semicircular-shaped microchannel with a constant square cross-section. A closed-loop control strategy is developed to achieve adequate control by utilizing a model based on experimental data. A novel digital image processing–based real-time velocity estimation algorithm is proposed as feedback information in the closed-loop control system. This paper aims to evaluate the success of the proposed real-time velocity estimation algorithm. The results indicate that the proposed algorithm can supply the fluid velocity inside the microchannel with a maximum deviation of less than 4% in the current micropumping system. Three different controllers—that is, proportional (P), proportional–integral (PI), and proportional–integral–derivative (PID)—are also implemented to test the influence of the control logic used in the closed-loop control strategy. Compared with the previous study, the implementation of a closed-loop control strategy in the present work provided a constant flow rate pumping. The findings reveal that the PID controller can maintain a constant flow rate with transient time values around 186, 94, and 60 seconds for reference values of 100, 200, and 300 µm/s, respectively. In addition, the PID controller could supply a constant flow rate within the microchannel 51% longer than the PI controller. [ABSTRACT FROM AUTHOR]

In this paper, the H ∞ control problem for a class of two-dimensional (2-D) linear discrete-time systems with fading measurements is investigated, where the 2-D systems are described by a Roesser model. The Rice fading model is applied to describe the fading phenomenon and the coefficients of the model satisfy the independent identical Gaussian distributions. The main objective of this paper is to design a controller such that both the 2-D closed-loop system is exponentially mean-square stable and the prescribed H ∞ performance is guaranteed under the condition of applying the attenuation signals. By utilizing the Lyapunov stability theory and the linear matrix inequalities (LMIs) techniques, sufficient conditions are conducted to guarantee the desired tracking performance. Based on such conditions, the gain matrix of the proposed controller is obtained. Finally, the effectiveness of the proposed control schemes is illustrated with a numerical example and a Darboux equation example. [ABSTRACT FROM AUTHOR]

This paper studies a new procedure for robust tracking of nonlinear systems. This procedure is based on the combination of the sliding mode control and the funnel control, which in addition to the robust performance of the closed-loop system in the face of model uncertainties and/or external disturbances also leads to improvement of the characteristics of the transient responses. Using funnel control and the appropriate choice of the funnel can affect the convergence rate and overshoot. In this regard, a theorem has been presented and the effective performances of the suggested controller have been guaranteed in various respects based on exact mathematical analysis. Simulations have also been carried out to illustrate the efficiency of the proposed approach and to verify the theoretical achievements of the paper despite model uncertainties and external disturbances. [ABSTRACT FROM AUTHOR]

The tracking control problem for a group of nonlinear lower-triangular systems with multiple uncertainties is investigated in this work. Wherein, a novel performance constraint is first constructed to guarantee the fixed-time convergence of the output tracking error. Subsequently, a linear extended high-gain observer is employed to estimate the system uncertainties including the unmeasured states and the external disturbances. Based on the observer estimations, a novel output-feedback tracking control approach is formulated via using the backstepping technique, to ensure the boundedness of the closed-loop system. Compared with the existing works, the primary advantages of the proposed design are that (1) the problem of "explosion of terms" is avoided by eliminating the need for the derivative of the virtual control signals and (2) without the use of extra auxiliary techniques, the fixed-time convergence can be guaranteed, where the convergence time is independent of the system states and initial conditions. Then, the results about system stability are proved by the theoretical analysis. Moreover, an extension of the proposed approach to multi-input multi-output systems is deduced in this paper to further present its versatility. Finally, two groups of numerical examples are performed to validate the effectiveness of the proposed controller. [ABSTRACT FROM AUTHOR]

This paper addresses the resilient formation control problem for heterogeneous multiple unmanned aerial vehicles (multi-UAV) under false data injection (FDI) attacks and prescribed performance constraints. The case of both actuator and sensor attacks is considered simultaneously, and the multi-UAV can exchange the information through a directed communication network. A fuzzy adaptive observer (FAO) is first proposed to estimate the FDI attacks and the unmeasurable velocity information for each UAV. In order to transform the formation control of heterogeneous multi-UAV into a trajectory tracking control problem of individual UAVs, a bank of distributed estimators is designed to achieve the leader's states by only using local information among neighboring UAVs. Then, by incorporating a novel tracking error transform method and fractional-order sliding mode control technique, a resilient prescribed performance tracking controller without velocity measurements is constructed. Furthermore, it is proved that all signals of the closed-loop formation control systems are uniformly ultimately bounded (UUB) stable under FDI attacks. Finally, the simulation results are given to verify the effectiveness and superiority of the proposed control strategy. [ABSTRACT FROM AUTHOR]

In this paper, a model-free robust adaptive control scheme with finite-time convergence based on time-delay control is proposed for anti-sway and positioning control of two-dimensional underactuated overhead cranes. First, the whole overhead cranes system is simplified to an ultra-local model for time delay estimation (TDE). TDE brings a direct and effective model-free property but also an estimation error. Second, a sliding mode disturbance observer is designed to estimate and compensate for the TDE error. Third, sliding mode control (SMC) is used to enhance the robustness of the controller. An adaptive integral sliding surface is then designed to accelerate the sliding surface convergence rate and shorten the convergence time. To further optimize the selection of parameters, the parameter estimation is integrated to enhance the performance of model-free control. In the final analysis of the simulation, data yield that the introduction of parameter estimation increases the control performance by more than 20% on average, and the above facts verify the effectiveness of the scheme. Finally, the stability of the closed-loop control system is analyzed by using Lyapunov stability theory, and the effectiveness and robustness of the control scheme are verified through computer simulation results. [ABSTRACT FROM AUTHOR]

Interconnection and damping assignment passivity-based control (IDA-PBC) has been successfully applied to many mechanical, electrical, and electromechanical systems. For the control of such systems, existing IDA-PBC methods have concentrated on systems with underactuation degree one, such as the ball and beam system, the vertical takeoff and landing aircraft, and the pendulum on a cart. In this paper, we focus on the application of the IDA-PBC methodology to the regulation control of a three-dimensional (3D) overhead crane system with underactuation degree two. The goal of this study is to design and analyze a regulation controller that can drive the cart to the desired position precisely and eliminate the payload swing effectively. To achieve this challenging objective, we first find an ingenious way to solve partial differential equations for constructing a Lyapunov function candidate. Then, we devise a nonlinear controller on the basis of the constructed Lyapunov function and analyze the stability of the closed-loop system by using Lyapunov techniques and LaSalle's invariance principle. Finally, both simulation and experimental results demonstrate the proposed strategy can achieve excellent positioning accuracy and significant swing elimination, and a comparison study between the proposed method and the existing PBC method is included as well. [ABSTRACT FROM AUTHOR]