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This article investigates the robust consensus problem for nonlinear multiagent systems against time‐varying false data injection attacks on actuators and sensors. First, the root‐mean‐square (RMS) theory is used to extend the assumption of the slow‐varying or constant attack signals to the case of time‐varying attack signals. Second, a novel distributed multivariate observer (DMO) is designed to estimate the followers' system states and the time‐varying attack signals on actuators and sensors. With the help of the outputs of DMO, a distributed robust consensus control arithmetic is proposed, which can compensate for actuator attacks and isolate sensor attacks so that exponential consensus and robust consensus are achieved. In particular, the robust performance of estimation errors and consensus errors is ensured by establishing the RMS gain index via linear matrix inequality, in which the zero initial conditions of estimation errors and consensus errors are not required. Finally, two simulation examples, including a network of four aircraft longitudinal dynamic systems, are given to verify the effectiveness of the proposed arithmetic. [ABSTRACT FROM AUTHOR]

The prescribed performance event-triggered fault-tolerant control (FTC) problem is considered for a class of uncertain pure-feedback nonlinear systems with actuator failures. Contrary to the existing results, the novel decoupling condition and the universal construction mode of error transformation are first given. Based on this, a new radical constrained function is used to low-complexity controller design without involving the Nussbaum gain scheme or adaptation parameter updated structure, in spite of nonlinear coupling and event triggering input. It is proved that the desired prescribed accuracy of the closed-loop output tracking can be achieved and the number of event-trigger showed a significant reduction. The effectiveness of theory results is verified by simulation on a numerical example. [ABSTRACT FROM AUTHOR]

This article investigates the distributed robust estimation problem for false data injection (FDI) attacks in nonlinear multi‐agent systems with directed graphs. To approximate the realistic attack scenario, the case where both the actuator network channel and sensor network channel suffering from FDIs are considered, and the attack signals contain time‐varying circumstances. A novel distributed robust‐multivariate‐observer (DRMO) strategy is developed such that the online estimation of FDI attack dynamics can be realized with the partially unknown nonlinear dynamics, attack transient increments, and disturbances impact being eliminated. The designed DRMO scheme only depends on the received compromised/uncompromised measurement output information on the account that whole state information cannot be measured directly. Finally, two simulation examples, including a network of four one‐link flexible joint manipulator systems with comparisons to existing methods, are given to show the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

For output-constrained switched systems, uniformly local stabilization problem via state feedback is addressed. A unified tool, a common tangent-type barrier Lyapunov function (Tan-BLF), is developed to deal with the stabilization problem of switched systems and to cope with constraints imposed on system output with or without. Then, combining adding a power integrator technique (APIT) and the developed common barrier Lyapunov function, state-feedback stabilizing laws are designed systematically to make the resultant closed-loop switched systems asymptotically stable while preventing the violation of output constraints. The efficiency of the proposed method is illustrated by numerical results. [ABSTRACT FROM AUTHOR]

This article investigates the predefined-time stabilization problems of Takagi–Sugeno (T–S) fuzzy systems. For addressing the considered problems, a class of novel integral sliding mode surface is first designed based on the time-regulator function, on which the system states are forced to converge to the origin in a predefined time after the sliding mode surface is reached. Further, the proposed sliding surface is employed to construct predefined-time integral sliding mode controller for the time delayed and disturbed T–S fuzzy system. The settling time appears as the sum of two predefined-time parameters in the controller design, which, respectively, adjusts the convergence time for reaching the sliding mode surface and the convergence time for arriving the origin from the sliding mode surface. The sufficient conditions for maintaining the predefined-time stability of the T–S fuzzy systems are obtained through systematic Lyapunov stability analysis. Finally, a numerical simulation example on delayed and disturbed Chua circuit is presented to verify the effectiveness of the proposed predefined-time integral sliding mode controller. [ABSTRACT FROM AUTHOR]

This article focuses on the design problem of fault detection (FD) observer for a class of continuous-time nonlinear systems. The $\mathcal {H_{-}}$ index is employed to measure the worst cast fault sensitivity. First, the nonlinear systems are represented by the Takagi–Sugeno (T–S) fuzzy dynamic models. Then, a novel fuzzy Lyapunov function (FLF) analyzing approach is proposed to reduce the conservatism in stability analysis and $\mathcal {H_{-}}$ index estimation for the T–S fuzzy model. In particular, employing this new type of the FLF, the stability analysis of the T–S fuzzy systems perfectly overcomes the difficulty of evaluating the upper bound of the time derivative of the membership function. Based on the descriptor system approach, some new sufficient conditions on the existence of fuzzy FD observers are obtained in terms of linear matrix inequalities (LMIs). Finally, illustrative examples are given to show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper is dedicated to event-triggered data-driven control of nonlinear systems with unknown disturbance via model free iterative learning approach. An extended state observer is employed to reconstruct the disturbance in system output. An event-triggered model free iterative learning control strategy is constructed by system input, system output and the reconstructed disturbance. Sufficient conditions are proposed to make the resultant tracking error system be uniform ultimate bounded. Simulation examples are provided to validate the effectiveness of the proposed scheme. • An extended state observer is employed to estimate the unknown disturbance in system output. • An event-triggered model free iterative learning control scheme is presented by integrating tracking error, input error and the estimated disturbance. • Sufficient conditions are proposed to make the resultant event-triggered model free iterative learning tracking error system be uniform ultimate bounded. [ABSTRACT FROM AUTHOR]

In this paper, the collaborative control of multiple nonlinear Euler-Lagrange systems with actuator faults and stochastic semi-Markov jump networks (SMJNs) is concerned. In order to fulfil high reliability and low consumption, several novel event-triggered fault-tolerant control (ETFTC) algorithms are established to simultaneously eliminate the undesirable faults and save control resources, where only quantised partial-state signal of neighbours is required for the control process. Moreover, some ubiquitous constraints, such as unknown control directions and time-varying communication delays, are also comprehensively considered and effectively excluded so as to further enhance the control reliability. Meanwhile, some sufficient criteria on the algorithm synthesis and stability analysis without involving Zeno behaviour are successfully built with the aid of Lyapunov–Krasovskii functional. Finally, some illustrative simulations are performed to validate the feasibility and effectiveness of the derived ETFTC algorithms. [ABSTRACT FROM AUTHOR]

This article focuses on the design of fuzzy secure control for a class of coupled systems, which are modeled by a nonlinear $N$ -dimensional ($N$ -D) parabolic partial differential equation (PDE) subsystem and an ordinary differential equation (ODE) subsystem. Under stochastic deception attacks, a fuzzy secure control scheme is designed, which is effective to tolerate the attacks and ensure the desired performance for the considered systems. A new fuzzy-dependent Poincare–Wirtinger’s inequality (PWI) is proposed. Compared with the traditional Poincare’s inequality, the fuzzy-dependent PWI is more flexible and less conservative. Meanwhile, an augmented Lyapunov–Krasovskii functional (LKF) is newly constructed, which strengthens the correlations of the PDE subsystem and ODE subsystem. Then, on the ground of the fuzzy-dependent PWI and the augmented LKF, new exponential stabilization criteria are set up for the PDE-ODE coupled systems. Finally, a hypersonic rocket car is presented to verify the effectiveness and less conservatism of the obtained results. [ABSTRACT FROM AUTHOR]

The output constraints are widespread in physical systems. Violation of output constraints may result in system damage and performance degradation. This article investigates the design issue of adaptive fuzzy second-order sliding-mode (SOSM) controller, which aims to handle a class of nonlinear systems with output constraints. The unknown bounds of uncertainties are approached dynamically by fuzzy logic systems. Through designing a new barrier Lyapunov function, the output constraint problem has been well solved. Then, by integrating adding a power integrator technology and adaptive fuzzy control, a novel adaptive fuzzy SOSM controller is proposed. It is proved that the proposed method makes the output variable not violate the specified constraint region. At the same time, it can be shown, based upon the Lyapunov approach, that the finite-time stability of the resulting closed-loop system under output constraint is ensured. Finally, a numerical example and a practical pendulum system are presented to demonstrate the validity of the proposed SOSM control strategy. [ABSTRACT FROM AUTHOR]

This article concentrates on the model-based fuzzy $l_{2}-l_{\infty }$ filtering problem of a discrete-time semi-Markov jump nonlinear system. The random jumps in the studied system are governed by the discrete-time semi-Markov process. Therefore, the storage characteristics of the transition probability between systems are fully considered. To analyze the $\sigma$ -mean-square stability of the filtering error system, a mode-dependent filter, which is based on the discrete-time fuzzy semi-Markov jump model, is constructed to estimate the state of the system. Thereafter, based on the Lyapunov stability theory and the discrete-time semi-Markov kernel concept, a set of sufficient criteria to ensure the $\sigma$ -mean-square stability and $l_{2}-l_{\infty }$ performance are derived. In addition, by using the Takagi–Sugeno fuzzy model, the nonlinear problem is effectively solved. Two illustrative examples, including a numerical example and a tunnel diode circuit example, are demonstrated to reveal the practicability of the developed filtering strategy. [ABSTRACT FROM AUTHOR]

This article investigates the problem of quantized fuzzy control for discrete-time switched nonlinear singularly perturbed systems, where the singularly perturbed parameter (SPP) is employed to represent the degree of separation between the fast and slow states. Taking a full account of features in such switched nonlinear systems, the persistent dwell-time switching rule, the technique of singular perturbation and the interval type-2 Takagi–Sugeno fuzzy model are introduced. Then, by means of constructing SPP-dependent multiple Lyapunov-like functions, some sufficient conditions with the ability to ensure the stability and an expected $H_{\infty }$ performance of the closed-loop system are deduced. Afterward, through solving a convex optimization problem, the gains of the controller are obtained. Finally, the correctness of the proposed method and the effectiveness of the designed controller are demonstrated by an explained example. [ABSTRACT FROM AUTHOR]

This article investigates the event-triggered adaptive fuzzy fixed-time secure control problem for a class of nonlinear cyber-physical systems subject to unknown deception attacks and backlashlike hysteresis. Based on an improved fractional-order command filtered backstepping method, fuzzy approximation technique, and Nussbaum gain technique, a novel adaptive practical fixed-time secure control scheme is proposed. Theoretical analyses prove that the fixed-time stability of the resulting control system and boundedness of all signals in the closed-loop system can be guaranteed by using the presented resilient controller. Especially, the given convergence time is independent of the initial states of the system and better system performance consisting of higher control accuracy and faster convergence rate can be ensured. Finally, a chemical reaction system is carried out to show the validity and superiority of the developed secure control scheme. [ABSTRACT FROM AUTHOR]

In this study, the Takagi–Sugeno (T–S) fuzzy impulsive control problem is investigated for a class of nonlinear positive systems with time delay. The time delay under consideration is both in the continuous-time dynamics and at the impulsive instants, which can model practical systems more accurately. An impulse-time-dependent copositive Lyapunov function (IDCLF) is constructed, and the Razumikhin technique is adopted to develop conditions that ensure the globally exponential stability of T–S fuzzy positive systems with delayed impulses. The size constraint between the impulse delay and the bound of impulsive intervals is removed. A T–S fuzzy impulsive controller is designed in terms of the solutions to certain vector inequalities that are readily solvable. Numerical examples and a practical example of lipoprotein metabolism and potassium ion transfer model are given to demonstrate the effectiveness, advantages, and practicality of the proposed results. [ABSTRACT FROM AUTHOR]

This article studies the adaptive finite-time quantized tracking control problem for a class of full state-constrained nonlinear systems with unknown control directions based on a modified fractional-order dynamic surface control (FODSC) technique. First, fractional calculus is introduced to filter design to avoid the issue of the “explosion of complexity” exposed in the traditional backstepping technique. To facilitate the control design, barrier Lyapunov functions and Nussbaum gain technique are utilized to handle full state-constrained problem and the unknown control directions, respectively. In addition, the fuzzy logic systems are employed to approximate the unknown nonlinearity of the system. By integrating with the approximation errors and compensating signals, a composite adaptive quantized controllers is designed to guarantee all the signals of the closed-loop systems are bounded and tracking error converges to an arbitrarily small neighborhood of the zero within a finite time. Finally, a mechanical horizontal platform model and a Brusselator model are carried out to verify the effectiveness of the presented control method. [ABSTRACT FROM AUTHOR]

In this article, the issue of positive $\mathcal {L}_{1}$ filter design is investigated for positive nonlinear stochastic switching systems subject to the phase-type semi-Markov jump process. Many complicated factors, such as semi-Markov jump parameters, positivity, T–S fuzzy strategy, and external disturbance, are taken into consideration. Practical systems under positivity constraint conditions and unpredictable structural changes are characterized by positive semi-Markov jump systems (S-MJSs). First, by the key properties of the supplementary variable and the plant transformation technique, phase-type S-MJSs are transformed into Markov jump systems (MJSs), which means that, to an extent, these two kinds of stochastic switching systems are mutually represented. Second, with the help of the normalized membership function, the associated nonlinear MJSs are transformed into the local linear MJSs with specific T–S fuzzy rules. Third, by choosing the linear copositive Lyapunov function (LCLF), stochastic stability (SSY) criteria are given for the corresponding system with $\mathcal {L}_{1}$ performance. Some solvability conditions for positive $\mathcal {L}_{1}$ filter are constructed under a linear programming framework. Finally, an epidemiological model illustrates the effectiveness of the theoretical findings. [ABSTRACT FROM AUTHOR]

This article studies the robust adaptive asymptotic tracking control problem for uncertain nonlinear systems with event-triggered inputs. Contrary to the existing results, a novel nonaffine nonlinear control input separated design scheme is developed based on the Taylor decoupling technique instead of the previous approximation ways. Correspondingly, the augmented dimension parameter updated laws and the unknown bound estimation of the compounded disturbance with a positive continuous integrable function are skillfully introduced. Also, by introducing a suitable decreasing function of tracking error variables, an improved adaptive event-triggered mechanism is constructed to achieve the asymptotic tracking and the communication load can be effectively alleviated. Moreover, it is shown that all the signals in the closed-loop system are uniformly bounded and the tracking errors converge to zero in a preset compact set. Finally, the validity of the proposed method is illustrated by simulation on an inverted pendulum model. [ABSTRACT FROM AUTHOR]

This article studies the issue of command filter-based adaptive fault-tolerant control for a class of nonlinear systems subject to unknown control directions and disturbance. First, the neural network is employed to deal with the nonlinear functions, and the explosion of the complexity problem is handled by the command filter approach. Second, the bound estimation method and the Nussbaum function are utilized to compensate for the influence of the actuator faults and the unknown directions, respectively. Finally, the tracking error signals are guaranteed to converge into bounded compact sets around the origin, and all closed-loop signals are bounded. The effectiveness of the proposed method is illustrated by three simulations. [ABSTRACT FROM AUTHOR]

This article investigates the adaptive resilient control problem for a class of nonlinear time-delay systems (TDSs) with unknown state-dependent deception attacks. For the purpose of overcoming the issue of "explosion of complexity" existing in the traditional backstepping control design and improving filter performance, an improved fractional-order command filtered backstepping technique is adopted to obtain the filtered signals of the virtual control laws. Furthermore, the corresponding auxiliary system and attack compensator are constructed to compensate the effects of input delay and unknown sensor deception attacks. Stability results prove that all the signals in the closed-loop systems are semi-globally uniformly ultimately bounded (SGUUB) by using the proposed adaptive resilient controller. Finally, two simulation examples are provided to show the effectiveness of the developed control method. [ABSTRACT FROM AUTHOR]

In this article, the global stabilization issue is discussed for a class of stochastic continuous time‐delay nonlinear systems suffered from unknown control directions and disturbance. Instead of designing the adaptive law online, a control gain is invoked to adapt for the formidable scene of merely continuous but nonsmooth caused by the low‐order, and to deal with the negative effects of disturbance and multiple unknown nonlinear functions where both input and state time delays are taken into account. Then, by utilizing the homogenous domination approach, a delay‐independent controller is designed with a sign function to compensate for the negative impact generated from disturbance and maintain the global asymptotic stability of the closed‐loop system. Finally, a stochastic simulation is supplied to show the validity of the control scheme. [ABSTRACT FROM AUTHOR]

This article studies the distributed adaptive leader-following control for high-order time-varying nonlinear multiagent systems (MASs) with uncertain parameters. The state feedback protocol and output feedback protocol are proposed, respectively, to render all states consensus errors to converge to zero asymptotically. First, the hierarchical decomposition algorithm is used to construct a refreshed communication graph to address the mutual dependence problem of controllers. Then, by introducing a local neighborhood consensus errors-based transformation, the leader-following consensus problem is converted into the stabilization problem for the consensus error system. Using the backstepping method and tuning function technique, the distributed adaptive state feedback controller is designed to render all followers’ states to track the leader’s ones. Further, by constructing the reduced-order dynamic gain k-filter to estimate unmeasured states, a distributed adaptive output feedback controller is designed. In both controller design methods, the traditional Lipschitz condition need not be satisfied any more for all time-varying nonlinear functions, and different from most of the existing results on the high-order nonlinear MASs, full states consensus can be obtained. Finally, a general numerical example is given to illustrate the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

In this article, an adaptive fuzzy control design strategy is presented for $p$ -norm nontriangular stochastic high-order nonlinear systems with asymmetric output constraints and unknown nonlinearities. To prevent the violation of the asymmetric output constraint, a novel barrier Lyapunov function (BLF) is constructed. Then, combining the constructed BLF with adding a power integrator approach, the adaptive fuzzy control algorithm is developed by the backstepping technique. Simultaneously, the rigorous proof displays that the designed controller can ensure that all variables of the closed-loop system are bounded in probability with the achievement of the output constraint. Eventually, the theoretical result is further demonstrated via the simulation results. [ABSTRACT FROM AUTHOR]

In this article, the distributed output-feedback adaptive fuzzy leader-following consensus is investigated for a class of high-order stochastic nonlinear multiagent systems (MASs) with unknown control gains and uncertain interactions from other agents. First, a novel dynamic gain filter is constructed to compensate unmeasured states and compared with the existing results, the number of dynamic variables is greatly reduced. Then, the tuning function method is used to construct adaptive laws to compensate unknown parameters. The uncertain interaction functions are decomposed and approximated by the fuzzy logic systems. Next, using the backstepping method, the dynamic gain filter-based distributed adaptive fuzzy leader-following protocol is designed, which only needs the dynamic variables’ information of neighbors, and the problem on computing the mutually dependent inputs in some existing results is completely avoided. Finally, the numerical simulation results are given to illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The topic of adaptive event‐triggered control for multi‐input‐multi‐output nonlinear systems with asymmetric state constraints is considered in this article. First, by introducing unified barrier functions method, the initial system is transformed to a non‐constraints system, which brings that the requirement of feasibility conditions could be eliminated and the constraint functions could be relaxed effectively. Then, an adaptive tracking controller is designed by combining some excellent technology, where command filter is utilized to overcome the explosion of complexity, neural network is introduced to approximate unknown nonlinear function, and event‐triggered mechanism is proposed to save communication resources. The designed control scheme can make the outputs of the system to track the target trajectories within a small bounded error range, all signals in the closed‐loop system are bounded, and all states do not escape the state constraints. Finally, practical and comparative examples are given to verify the effectiveness of the method. [ABSTRACT FROM AUTHOR]

In this article, an adaptive fuzzy tracking control scheme is developed for a class of uncertain switched nonlinear systems with input saturations and full-state constraints. First to surmount the design difficulty with respect to a saturation nonlinearity controller, a nonlinear smooth function approximating the nondifferential saturation function is introduced to establish a standard switched adaptive tracking control strategy based on the mean-value theorem and the input compensation technique. Then, invoking fuzzy-logic systems (FLSs), a novel analysis method of average dwell time for switched nonlinear systems with full-state constraints is proposed by using an artful logarithmic inequality. Furthermore, the designed adaptive controller can ensure that all the states of uncertain switched nonlinear systems are not to violate the set constraint bounds by employing barrier Lyapunov functions (BLFs), and that the system output tracking error can converge to a desired neighborhood of the origin within a suitable compact set. Finally, the simulation results are given to demonstrate the validity of the presented approach. [ABSTRACT FROM AUTHOR]

This article studies the adaptive backstepping control problem for a class of fractional-order (FO) nonlinear systems subject to input quantization and unknown control directions by combining with an indirect FO Lyapunov stability method, and a command filter-based FO dynamic surface control (FODSC) technique. First, a modified FODSC method is utilized to reduce the computational complexity existing in the conventional recursive procedure in which an FO command filter is designed to obtain the command signals and their FO derivatives. Furthermore, the Nussbaum function and neuro-fuzzy networks (NFNs) are adopted to deal with the problem of the unknown control directions and unknown nonlinear functions existing in the system. Moreover, by introducing the compensation and prediction mechanism to controller design, the adaptive controllers, and adaptive laws are constructed to ensure that all the signals of the controlled systems are bounded. Finally, two examples are given to show the validity of the developed control method. [ABSTRACT FROM AUTHOR]

This article addresses the problem of finite-time stabilization for a class of high-order nonlinear stochastic systems with asymmetric output constraints. A novel barrier Lyapunov function (BLF) is first presented to handle such asymmetric constraints. Further, based on the proposed BLF and the adding a power integrator technique, a controller design approach is developed by the backstepping method. It can be rigorously proved that the designed controller can not only make the system states finite-time converge to the origin in probability but also ensure that the constraint on system output is not violated. Another novelty of this approach is that it is a unified tool owing to its simultaneous application to the systems without output constraints. Finally, the validity of the proposed scheme can be verified by a simulation example. [ABSTRACT FROM AUTHOR]

This article investigates the memory adaptive event-triggered fault detection and isolation (FDI) problem for nonlinear networked control systems under periodic denial-of-service (DoS) attacks, where the nonlinear systems are described by Takagi–Sugeno (T–S) fuzzy models with unknown membership functions. First, a novel event-triggered mechanism is proposed to save communication resources. The triggering threshold is adaptively adjusted by multiple previous sampled data, not only depending on the latest triggering data. Second, taking DoS attacks, and event-triggered mechanism into consideration, a switching state-feedback controller is established, and the exponential stability is derived. Meanwhile, the controller, and the event-triggered mechanism are simultaneously developed based on a piecewise Lyapunov function. Then, a set of switching T–S fuzzy observers are constructed to realize FDI under DoS attacks. Besides, a switching variable method is introduced to address the asynchronous premise variables problem caused by the event-triggered mechanism. Finally, simulation cases are given to demonstrate the validity, and merit of the proposed FDI scheme. [ABSTRACT FROM AUTHOR]

In this article, the global adaptive fault-tolerant control is considered for a class of uncertain nonlinear systems with sensors, actuator faults, and disturbance. Different from the previous results, there are no a priori bounds of the sensor sensitivity, actuation effectiveness, and disturbance. A switching-type adaptive controller is designed where the controller parameter is tuned online by the proposed switching mechanism. It has also been proven that global stability can be achieved under the designed controller. Finally, a simulation example is provided to illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This article investigates the adaptive fuzzy control design for p-norm stochastic high-order lower triangular nonlinear systems with output constraints and unknown nonlinearities. First of all, a tan-type barrier Lyapunov function (BLF) is constructed to deal with the output constraint issue. Subsequently, an adaptive fuzzy control algorithm is developed by combining the constructed BLF with adding a power integrator technique. Simultaneously, the Lyapunov analysis shows that the designed controller can guarantee the boundness of all the variables in the closed-loop system in probability without violating the given output constraint. Finally, some comparative simulation results are provided to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This article is devoted to study the cluster synchronization for a kind of complex dynamical networks consisting of nonidentical nonlinear Lur’e systems. Different from general time delays, a proportional delay is taken into consideration in this article, which is a kind of unbounded time-varying delays and thus largely increases the difficulty in network synchronization. In consideration of the topology structures of the Lur’e networks, an effective impulsive pinning controller is proposed, which will be placed on the Lur’e systems having directed paths with those in the other clusters. Considering different functional roles that the impulsive effects play, sufficient criteria for the cluster synchronization of the nonidentically coupled Lur’e dynamical networks are obtained by applying the proportionally delayed impulsive comparison principle, the concept of average impulsive interval, and the extended parameters variation formula. Simultaneously, the exponential convergence rates are successfully estimated with respect to different functions of the impulsive effects. In the end of this article, three numerical simulations are proposed to denote the effectiveness of the control protocols and the theoretical results. [ABSTRACT FROM AUTHOR]

In this article, the dissipativity-based sampled-data control problem is studied for the fuzzy switched Markovian jump systems (FSMJSs). By considering the problem of the asynchronous switching caused by the subsystems’ switching occurred during the sampling intervals, constructing novel time-dependent Lyapunov functional, and using average dwell time (ADT) approach, sufficient mean-square exponential stability criteria, and strictly (Q, S, R)-γ-dissipativity criteria are proposed under the constraints that the maximum sampling period is no larger than the dwell-time between the transition rates switching instants. Meanwhile, a relationship between ADT and sampling period is revealed for FSMJSs. Based on the strictly (Q, S, R)-γ-dissipativity criteria, the sampled-data controller is designed for FSMJSs. A circuit simulation example is provided to illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this article, the $\mathcal {H}_{\infty }$ static output feedback tracking control problem is studied for discrete-time nonlinear networked systems subject to quantization effects and asynchronous event-triggered constraints. The Takagi–Sugeno (T–S) fuzzy model is utilized to represent the investigated nonlinear networked systems. A novel asynchronous event-triggered strategy is given to reduce the network communication burdens in both communication channels from the plant to the controller and from the reference model to the controller. The objective of this article is to design a quantized event-triggered tracking controller such that the resulting system is asymptotically stable and the given $\mathcal {H}_{\infty }$ tracking performance is guaranteed. The sufficient design conditions for the tracking controller are formulated in the form of the linear matrix inequalities (LMIs). Furthermore, a simulation example will be utilized to show the effectiveness of the developed design strategy. [ABSTRACT FROM AUTHOR]

This article is concerned with the fuzzy adaptive tracking control problem for a class of uncertain nonaffine nonlinear systems with full state constraints and event-triggered inputs. First, based on the mean-value theorem and the input compensation method, the control input signal of nonaffine nonlinear term is successfully decoupled, and the remained compound nonlinear function can be approximated by fuzzy logic systems. Then, an improved event-triggered control strategy including the fixed threshold, the event-trigger control input, and the decreasing function of tracking errors, is given to update the actual control input. Correspondingly, the computation burden of the communication procedure is effectively alleviated. In addition, the developed control scheme guarantees that all the states of the closed-loop systems are not to violate the predefined compact sets by constructing barrier Lyapunov functions. Also, the system output tracking error can converge to a desired neighborhood of the origin. Finally, the validity of the proposed approach is demonstrated by the simulation results. [ABSTRACT FROM AUTHOR]

This article investigates the adaptive output feedback resilient control problem for a class of incommensurate fractional-order (FO) nonlinear systems in the presence of time-varying delays and actuator faults by combining with an adaptive backstepping technique and a modified FO dynamic surface control (FODSC) method. Considering that the information of system states is not fully available, a hybrid fuzzy observer is designed to estimate the unmeasurable system states, where the neuro-fuzzy network system is introduced to handle the unknown nonlinear functions existing in the system. Furthermore, in order to overcome the problem of the explosion of complexity caused by traditional backstepping design procedure, an FO filter is constructed to pass the virtual control signal based on the FODSC scheme. Moreover, according to an indirect Lyapunov stability method, an adaptive hybrid fuzzy output feedback controller is designed to guarantee that all the signals of the closed-loop systems are bounded. Finally, three examples are given to verify the validity and superiority of the presented control scheme. [ABSTRACT FROM AUTHOR]

This paper concerns a positive $\mathcal {L}_{1}$ observer for positive nonlinear semi-Markovian switching systems (MSSs) via the expansion of Taylor formula and the fuzzy Lyapunov function approach, in which semi-Markovian switching parameters, positivity, Takagi–Sugeno (T–S) fuzzy, and external disturbance are all considered in a unified framework. A fuzzy Lyapunov function approach with less conservativeness is introduced into the research of positive systems. In the system under consideration, positive S-MSSs with the semi-Markovian process can describe more complex systems in a practical control process. The main motivation of this paper is that the practical system subject to positivity and abrupt changes can be described by positive nonlinear S-MSSs, which always needs to consider the external disturbance. First, by using the normalized membership function approach, positive nonlinear S-MSSs can be represented by local positive T–S fuzzy S-MSSs. Second, by constructing the fuzzy Lyapunov function, some sufficient conditions are proposed for stochastic stability and $\mathcal {L}_{1}$ -gain performance analysis, respectively. Then, a positive $\mathcal {L}_{1}$ observer in a novel standard linear programming condition is designed to guarantee the resulting closed–loop augmented system is positive and stochastically stable with a required $\mathcal {L}_{1}$ -gain performance. Finally, a practical example about the epidemiological model is introduced to show the effectiveness of the main theory. [ABSTRACT FROM AUTHOR]

In this paper, the quantized static output feedback dissipative tracking control problem is considered for a class of discrete-time nonlinear networked systems based on Takagi–Sugeno fuzzy model approach. The measurement output of the system, the output of the reference model, and the control input signals will be quantized by static quantizers before them being transmitted to the controller and the plant, respectively. The attention of this paper is focused on the design of the static output feedback tracking controller to asymptotically stabilize the nonlinear networked system and achieve strictly dissipative tracking performance subject to the quantization effects. Sufficient conditions for the existence of the static output feedback strictly dissipative tracking controller are expressed in terms of linear matrix inequalities. Two simulation examples are provided to show the effectiveness of the developed design method. [ABSTRACT FROM AUTHOR]

Summary: In this article, the global finite‐time adaptive control problem is considered for high‐order nonlinear systems in the presence of unknown control coefficients, actuator fault, and external disturbance. Different from the previous results, a tune parameter is introduced to directly compensate the unknown control coefficients rather than the traditional Nussbaum‐gain function. Without requiring a priori knowledge of the uncertainties, a switching‐type adaptive controller is proposed by adding a power integrator method. Based on the modified switching mechanism, the controller parameter can be tuned online such that global finite‐time stability can be achieved. Finally, a simulation example combined with comparison is provided to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Summary: In this article, the problem of command filter‐based adaptive event‐triggered neural network control is considered for a class of uncertain nonlinear systems with time delay. Lyapunov‐Krasovskii functionals and command filtered technology are utilized to address the problem of unknown time‐varying delays and explosion of complexity, respectively. Furthermore, by fusing the event‐triggered mechanism, an adaptive tracking controller is designed. The proposed controller not only ensures that the system output eventually follows the desired reference signal in the sufficiently small neighborhood of zero but also reduces the communication resources from the controller to the actuator. Finally, the effectiveness of the proposed control method is verified by a simulation example. [ABSTRACT FROM AUTHOR]

This paper addresses the adaptive fault-tolerant control (FTC) problem of uncertain switched nonaffine nonlinear systems with actuator failures and time delays. Unlike the literature employing the FTC methods, the novel nonlinear fault compensate function with adjustable parameter factor, whose norm is used for approximation with fuzzy logic systems, is constructed based on the mean value theorem. Accordingly, a standard transformation scheme from the multi-input and single-output nonaffine nonlinear system to the corresponding affine nonlinear system is first to be given; then, the designed adaptation mechanism with state-dependent switching strategy can effectively eliminate the effects of multiple time delays and actuator faults, including outage and stuck modes. Furthermore, by using the Lyapunov–Krasovskii stability analysis method, it is proved that the proposed adaptive switched controller can guarantee the states of the overall closed-loop systems to asymptotically converge to zero. Finally, the simulation results are displayed to verify the feasibility of the presented approach. [ABSTRACT FROM AUTHOR]

In this article, the adaptive fault-tolerant tracking control problem of nonaffine stochastic nonlinear systems with actuator failures and full-state constraints is studied. To surmount the design difficulty from nonaffine nonlinear term with multi-input and single-output (MISO) faulty modes, a novel nonlinear fault compensation function with adjustable parameter factor is first introduced to establish a standard adaptive fault-tolerant control (AFTC) strategy based on the mean-value theorem. Then, the remaining nonlinear function, including the partial loss of effectiveness, outage, and stuck cases, together with the constructed compound nonlinear function can be approximated by using the suitable fuzzy-logic system (FLS). Moreover, it is shown that all the states of nonaffine stochastic nonlinear systems are not violating the preset constraint bounds by employing the barrier Lyapunov functions (BLFs). Also, the given adaptive controller can guarantee all the closed-loop signals are uniformly ultimately bounded (UUB) in probability in the sense of fourth-moment within the appropriate compact sets. Finally, two simulation examples are given to demonstrate the validity of the proposed method. [ABSTRACT FROM AUTHOR]

Summary: In this paper, globally asymptotical stabilization problem for a class of planar switched nonlinear systems with an output constraint via smooth output feedback is investigated. To prevent output constraint violation, a common tangent‐type barrier Lyapunov function (tan‐BLF) is developed. Adding a power integrator approach (APIA) is revamped to systematically design state‐feedback stabilizing control laws incorporating the common tan‐BLF. Then, based on the designed state‐feedback controllers and a constructed common nonlinear observer, smooth output‐feedback controllers, which can make the system output meet the predefined constraint during operation, are proposed to deal with the globally asymptotical stabilization problem of planar switched nonlinear systems under arbitrary switchings. A numerical example is employed to verify the proposed method. [ABSTRACT FROM AUTHOR]