Dynamic output feedback controller design for affine T–S fuzzy systems with quantized measurements

This paper investigates the problem of event-triggered dynamic output feedback control for networked Takagi-Sugeno (T-S) fuzzy systems with asynchronous premise variables. Our attention is focused on the design of an event-triggered fuzzy dynamic output feedback controller that guarantees that the closed-loop system is asymptotically stable. First, with consideration of the limited bandwidth and restricted network resource, an event-triggered communication scheme is proposed to save the limited network resource. Second, different from the existing results in the literature, a fuzzy dynamic output feedback controller with asynchronous premise variables is constructed such that the premise membership functions are not necessarily the same as the networked T-S fuzzy systems. Then, by using the Wirtinger inequality and some slack matrices, a less conservative stability and stabilization conditions for the existence of fuzzy dynamic output feedback controller are derived in the form of linear matrix inequalities, which can be solved by the standard MATLAB toolbox. Finally, an example is given to demonstrate the effectiveness of the designed event-triggered fuzzy dynamic output feedback controller.

This paper considers the design problem of dynamic output feedback control for fractional-order (FO) Takagi-Sugeno fuzzy systems with uncertain parameters. Via the application of FO system stability theory, robust control method and the linear matrix inequality techniques, sufficient conditions are given for the stability analysis and the existence of the dynamic fuzzy output feedback controllers. The dynamic output feedback controller designed here guarantees the robust stability of the closed-loop system. Finally, a fractional order chaotic system simulation example is given to illustrate the effectiveness of the design approach here.

This paper is concerned with analyzing a novel model transformation of discrete-time Takagi-Sugeno (T-S) fuzzy systems with time-varying delays and applying it to dynamic output feedback (DOF) controller design. A new auxiliary model is proposed by employing a new approximation for time-varying delay state, and then delay partitioning method is used to analyze the scaled small gain of this auxiliary model. A sufficient condition on discrete-time T-S fuzzy systems with time-varying delays, which guarantees the corresponding closed-loop system to be asymptotically stable and has an induced l 2 disturbance attenuation performance, is derived by employing the scaled small gain theorem. Then the solvability condition for the induced l 2 DOF control is also established, by which the DOF controller can be found by solving a set of linear matrix inequalities (LMIs).

In this paper, the $\boldsymbol{L}_{\infty}$ control synthesis problem for linear systems subject to actuator saturation and persistent bounded disturbance is studied. An $\boldsymbol{L}_{\infty}$ dynamic output feedback controller, an anti-windup compensator and an event generator are simultaneously designed. First, by using the quadratic Lyapunov function technique, a sufficient condition on the existence of the $\boldsymbol{L}_{\infty}$ dynamic output feedback controller, an anti-windup compensator and an event generator is established via linear matrix inequalities (LMIs). Such an integrated controller is able to guarantee the regional stabilization and the $\boldsymbol{L}_{\infty}$ performance of linear systems with actuator saturation and external persistent bounded disturbance. Second, novel algorithms are developed to optimize the upper bound on the $\boldsymbol{L}_{\infty}$ performance, the event-triggered threshold and the domain of attraction. Moreover, an output-based event-triggered mechanism applying to the anti-windup dynamic output feedback control design is provided, which reduces the number of control actuation updates and information transmission with respect to the traditional time-triggered control scheme.

This paper is devoted to the problems of non-fragile H∞ and L2–L∞ control for a class of linear systems with time-varying state delay. The purpose is to design a dynamic output feedback controller with additive gain variations such that the closed-loop system is asymptotically stable while satisfying a prescribed H∞ (or L2–L∞) performance level. By using linear matrix inequality approach, a delay-dependent stability criterion is obtained by introducing a new type of Lyapunov–Krasovskii functional. Based on the obtained criterion, sufficient conditions for the existence of desired controllers are derived, and the corresponding stabilisation dynamic output feedback controller design algorithm is proposed. Numerical examples are included to illustrate the benefit and effectiveness of the proposed method.

For quasi-linear parameter varying (quasi-LPV) systems with bounded disturbance, a synthesis approach of dynamic output feedback robust model predictive control (OFRMPC) with the consideration of input saturation is investigated. The saturated dynamic output feedback controller is represented by a convex hull involving the actual dynamic output controller and an introduced auxiliary controller. By taking both the actual output feedback controller and the auxiliary controller with a parameter-dependent form, the main optimization problem can be formulated as convex optimization. The consideration of input saturation in the main optimization problem reduces the conservatism of dynamic output feedback controller design. The estimation error set and bounded disturbance are represented by zonotopes and refreshed by zonotopic set-membership estimation. Compared with the previous results, the proposed algorithm can not only guarantee the recursive feasibility of the optimization problem, but also improve the control performance at the cost of higher computational burden. A nonlinear continuous stirred tank reactor (CSTR) example is given to illustrate the effectiveness of the approach.

In this paper, the problem of L 2 -L ∞ dynamic output feedback controller design for the nonlinear switched system in the T-S fuzzy framework is investigated. First, the average dwell time approach is used to stabilize the nonlinear switched systems under an arbitrary switching law. Then, based on the piecewise Lyapunov function, the fuzzy-rule-dependent dynamic output feedback controller is designed to ensure that the overall closed-loop system is exponentially stable with a weighted :L 2 -L ∞ performance. Finally, the solvability condition of the desired output feedback controller is obtained by the linearization procedure technique, which can be calculated by available software.

In this paper, the event-triggered dynamic output feedback controller design problem is addressed for a class of discrete-time nonlinear systems in network environment. An augmented closed-loop system is constructed and the sufficient conditions to ensure the mean-square asymptotically stability of the closed-loop system with a Hankel-norm performance by considering the event-triggered condition and using the reciprocally convex technique. It is shown that the solution of the fuzzyrule-dependent dynamic output feedback controller parameters can be obtained by variable substitution method. An example is provided to demonstrate the effectiveness of the proposed design method.

This paper studies the problem of dynamic output feedback control for continuous-time Takagi–Sugeno fuzzy systems. Based on the fuzzy Lyapunov functions without the special structure, a controller design method is developed and the relaxed stabilisation conditions are proposed. First, some shortcomings of the existing results are improved and a new approach is proposed for bounding the time derivatives of the membership functions. Then, less conservative conditions are obtained by introducing regulable parameters and applying the matrix decoupling techniques, which guarantee the prescribed performance. Moreover, the relaxation technique proposed in this paper is also suitable for the fuzzy system with immeasurable premise variables. Finally, some examples are provided to demonstrate the validity of the approach.

ABSTRACTThis paper is concerned with the problem of non-fragile reduced-order dynamic output feedback control for both continuous- and discrete-time switched systems with average dwell-time switching. First, Lyapunov conditions for the analysis of asymptotic stability and weighted performance are presented. Then, sufficient conditions for the solvability of the problem of controller design are developed in terms of linear matrix inequalities. The design methods are suitable for general switched systems, without the need to impose extra constraints on the system matrices. Finally, numerical examples are presented to illustrate the effectiveness of the proposed methods.

Dynamic output-feedback control for nonlinear continuous-time systems based on parametric uncertain subsystem and interval type-2 fuzzy model

Multiple intermittent fault estimation and tolerant control for switched T-S fuzzy stochastic systems with multiple time-varying delays

This study is concerned with the problem of observer-based output feedback control for T-S fuzzy systems with time-delay under imperfect premise matching. The objective is to design an observer-based controller such that the closed-loop control system is asymptotically stable. The proposed fuzzy controller and fuzzy observer do not need to share the same premise membership functions and number of rules with T-S fuzzy systems, which makes the controller and observer design more flexible. Using a recently developed integral inequality, a delay-dependent method for the controller and observer design is provided. With the help of some advanced matrix inequalities, the proposed conditions are presented in the form of linear matrix inequalities (LMIs). An illustrative example is given to show the effectiveness of the present result.

Single-parameter-learning-based fuzzy fault-tolerant output feedback dynamic surface control of constrained-input nonlinear systems

This paper deals with the event‐triggered dynamic output feedback control for fuzzy systems against denial‐of‐service (DoS) attacks. The DoS attack behavior is modeled using a binary Markov chain to reflect the unreliability of the communication channel. To reduce network communication overhead, a novel probabilistic event‐triggered protocol with uncertain probabilities is introduced. Additionally, the potential mismatches between premise variables and modes in both the fuzzy system and the controller are accounted, leading to the design of a dual‐asynchronous dynamic output feedback controller. Finally, the efficacy of the proposed approach is validated through a comprehensive numerical example, highlighting its effectiveness in handling asynchronous control scenarios and DoS attack resilience in fuzzy systems.