Robust output tracking control for discrete-time nonlinear systems with time-varying delay: Virtual fuzzy model LMI-based approach

This paper proposes an output tracking control via virtual reference model for a class of nonlinear discrete-time systems with time-varying delay and disturbance. First, a Takagi–Sugeno (T–S) fuzzy model represents the discrete-time nonlinear system with time-varying delay. Second, a fuzzy observer design estimates immeasurable state. Third, a virtual desired variable (VDV) based tracking controller design guarantees H_∞ control performance for the overall system. Using Lyapunov’s stability analysis, we obtain sufficient conditions for stability of estimation, control, and robustness. The advantages are as follows: (i) allow unknown time-varying delay; (ii) ensure robust output tracking; (iii) provide relaxed conditions via a three-steps procedure to find observer and controller gain. To verify the theoretical derivation, we carry out numerical simulations on a stirred tank reactor system as an example. Satisfactory results validate the claims.     

H∞ output tracking fuzzy control for nonlinear systems with time-varying delay

This paper proposes an observer-based output tracking control via virtual desired reference model for a class of nonlinear systems with time-varying delay and disturbance. First, the Takagi–Sugeno fuzzy model represents the nonlinear system with time-varying delay and disturbance. Then we design an observer to estimate immeasurable states and controller to drive the error between estimated state and virtual desired variables (VDVs) to zero such that the overall control output tracking system has H_∞ control performance. Using Lyapunov–Krasovskii functional, we derive sufficient conditions for stability. The advantages of the proposed output control system are (i) systematic approach to derive VDVs for controller design; (ii) relaxes need for real reference model; (iii) drops need for information of equilibrium; (iv) relaxed condition is provided via three-step procedure to find observer and controller gain. We carry out simulation using a continuous stirred tank reactor system where the effectiveness of the proposed controller is demonstrated by satisfactory numerical results.     

非线性系统广义模糊跟踪控制

研究一种给定 H∞ 模型参考跟踪特性的非线性系统的 T-S 广义模糊跟踪控制问题. 通过把一般的模糊模型等价变换到广义模糊模型, 引入了松弛变量, 并基于线性矩阵不等式 (LMI) 给出了新的 H∞ 跟踪控制器设计方法. 控制器参数在一组线性矩阵不等式中同时得到求解, 避免了原有方法分步求解的困难, 方法简单易行且具有鲁棒性. 两个算例表明了结论的有效性.     

State feedback tracking control for indirect field-oriented induction motor using fuzzy approach

This paper deals with the synthesis of fuzzy controller applied to the induction motor with a guaranteed model reference tracking performance. First, the Takagi-Sugeno (T-S) fuzzy model is used to approximate the nonlinear system in the synchronous d-q frame rotating with field-oriented control strategy. Then, a fuzzy state feedback controller is designed to reduce the tracking error by minimizing the disturbance level. The proposed controller is based on a T-S reference model in which the desired trajectory has been specified. The inaccessible rotor flux is estimated by a T-S fuzzy observer. The developed approach for the controller design is based on the synthesis of an augmented fuzzy model which regroups the model of induction machine, fuzzy observer, and reference model. The gains of the observer and controller are obtained by solving a set of linear matrix inequalities (LMIs). Finally, simulation and experimental results are given to show the performance of the observer-based tracking controller.     

T-S模糊系统的稳定性分析与镇定控制器设计

应用广义模糊Lyapunov函数方法研究T-S模糊系统的稳定性与控制器设计问题.首先,将T-S模糊系统表示成模糊广义系统的形式;然后利用广义模糊Lyapunov函数得到模糊系统稳定的充分条件,并且给出基于线性矩阵不等式(LMI)的PDC控制器设计方法.该方法与已有的模糊Lyapunov函数方法相比,计算量小,并且表达成LMI形式,容易求解.最后,通过例子验证方法的优越性和有效性.     

Takagi-Sugeno模糊连续系统的模糊采样控制

研究了T-S模糊连续系统的模糊采样控制问题．利用广义系统的描述方法、Lyapunov-Krasovikii泛函以及线性矩阵不等式(LMI)方法,建立了LMIs形式的依赖于采样时间间隔的模糊采样镇定条件,同时给出了模糊采样控制律的设计方法．所设计的模糊采样控制律可以镇定T-S模糊系统．而且,当连续时间模糊控制律可以镇定T-S模糊系统时,对于足够小的采样时间间隔,带有同样增益矩阵的模糊采样控制律也可以镇定T-S模糊系统．最后,通过两个仿真实例说明了所给方法的有效性．     

Switching fuzzy controller design based on switching Lyapunov function for a class of nonlinear systems

This paper presents a switching fuzzy controller design for a class of nonlinear systems. A switching fuzzy model is employed to represent the dynamics of a nonlinear system. In our previous papers, we proposed the switching fuzzy model and a switching Lyapunov function and derived stability conditions for open-loop systems. In this paper, we design a switching fuzzy controller. We firstly show that switching fuzzy controller design conditions based on the switching Lyapunov function are given in terms of bilinear matrix inequalities, which is difficult to design the controller numerically. Then, we propose a new controller design approach utilizing an augmented system. By introducing the augmented system which consists of the switching fuzzy model and a stable linear system, the controller design conditions based on the switching Lyapunov function are given in terms of linear matrix inequalities (LMIs). Therefore, we can effectively design the switching fuzzy controller via LMI-based approach. A design example illustrates the utility of this approach. Moreover, we show that the approach proposed in this paper is available in the research area of piecewise linear control.     

T–S Fuzzy Bilinear Model and Fuzzy Controller Design for a Class of Nonlinear Systems

This paper proposes a fuzzy bilinear model for a class of nonlinear systems and a fuzzy controller to stabilize such systems. By examination of a modeling problem, we describe how to transform a nonlinear system into a bilinear one via Taylor's series expansion and then we adopt the Takagi-Sugeno (T-S) fuzzy modeling technique to construct a fuzzy bilinear model. For controller design, the parallel distributed compensation (PDC) method is utilized to stabilize the fuzzy bilinear system (FBS), and some sufficient conditions are derived to guarantee the stability of the overall fuzzy control system via linear matrix inequalities (LMIs). Moreover, we propound some sufficient conditions for robust stabilization of the FBS with parametric uncertainties. Finally, a numerical example and the Van de Vusse model are utilized to demonstrate the validity and effectiveness of the proposed FBS.     

基于观测器的参数不确定非线性系统的模糊鲁棒控制

对一类非线性系统进行模糊建模及其模糊观测器设计，研究了在系统的状态不可测且存在参数不确定的模糊鲁捧控制问题，以线性矩阵不等式的形式给出了模糊控制系统具有李雅普诺夫意义下稳定的充分条件，最后把所提出的方法应用到倒立摆系统进行仿真，仿真结果验证了该控制方法的有效性。     

Non-monotonic robust H2 fuzzy observer-based control for discrete time nonlinear systems with parametric uncertainties

A non-monotonic Lyapunov function (NMLF) is deployed to design a robust H₂ fuzzy observer-based control problem for discrete-time nonlinear systems in the presence of parametric uncertainties. The uncertain nonlinear system is presented as a Takagi and Sugeno (T–S) fuzzy model with norm-bounded uncertainties. The states of the fuzzy system are estimated by a fuzzy observer and the control design is established based on a parallel distributed compensation scheme. In order to derive a sufficient condition to establish the global asymptotic stability of the proposed closed-loop fuzzy system, an NMLF is adopted and an upper bound on the quadratic cost function is provided. The existence of a robust H₂ fuzzy observer-based controller is expressed as a sufficient condition in the form of linear matrix inequalities (LMIs) and a sub-optimal fuzzy observer-based controller in the sense of cost bound minimization is obtained by utilising the aforementioned LMI optimisation techniques. Finally, the effectiveness of the proposed scheme is shown through an example.     

基于观测器的参数不确定非线性系统的模糊鲁棒控制

对一类非线性系统进行模糊建模及其模糊观测器设计, 研究了在系统的状态不可测且存在参数不确定的模糊鲁棒控制问题, 以线性矩阵不等式的形式给出了模糊控制系统具有李雅普诺夫意义下稳定的充分条件, 最后把所提出的方法应用到倒立摆系统进行仿真, 仿真结果验证了该控制方法的有效性.     

A novel criterion for nonlinear time-delay systems using LMI fuzzy Lyapunov method

This study presents a kind of fuzzy robustness design for nonlinear time-delay systems based on the fuzzy Lyapunov method, which is defined in terms of fuzzy blending quadratic Lyapunov functions. The basic idea of the proposed approach is to construct a fuzzy controller for nonlinear dynamic systems with disturbances in which the delay-independent robust stability criterion is derived in terms of the fuzzy Lyapunov method. Based on the robustness design and parallel distributed compensation (PDC) scheme, the problems of modeling errors between nonlinear dynamic systems and Takagi–Sugeno (T–S) fuzzy models are solved. Furthermore, the presented delay-independent condition is transformed into linear matrix inequalities (LMIs) so that the fuzzy state feedback gain and common solutions are numerically feasible with swarm intelligence algorithms. The proposed method is illustrated on a nonlinear inverted pendulum system and the simulation results show that the robustness controller cannot only stabilize the nonlinear inverted pendulum system, but has the robustness against external disturbance.     

Fuzzy-chaos hybrid controller for controlling of nonlinear systems

A novel concept for controlling of nonlinear systems using chaos and fuzzy model-based regulators is presented. In the control of such systems, we employ two phases, the first of which uses open-loop control forming a chaotic attractor or using chaotic inherent features in a system itself. Once the system states reach a predefined convex domain, open-loop control is cut off and a fuzzy model-based controller is employed under state feedback control in the second phase. The relaxed stability conditions and linear matrix inequalities (LMIs)-based design for a fuzzy regulator is introduced to construct a fuzzy attractive domain, in which a global solution is obtained so as to achieve the desired stability condition of the closed-loop system. The proposed controller architecture has been tested using three nonlinear systems: the Henon map, the Lorenz attractor, and a two-link manipulator. The simulation results show the effectiveness of the proposed controller     

Polynomial Fuzzy Observer Designs: A Sum-of-Squares Approach

This paper presents a sum-of-squares (SOS) approach to polynomial fuzzy observer designs for three classes of polynomial fuzzy systems. The proposed SOS-based framework provides a number of innovations and improvements over the existing linear matrix inequality (LMI)-based approaches to Takagi-Sugeno (T-S) fuzzy controller and observer designs. First, we briefly summarize previous results with respect to a polynomial fuzzy system that is a more general representation of the well-known T-S fuzzy system. Next, we propose polynomial fuzzy observers to estimate states in three classes of polynomial fuzzy systems and derive SOS conditions to design polynomial fuzzy controllers and observers. A remarkable feature of the SOS design conditions for the first two classes (Classes I and II) is that they realize the so-called separation principle, i.e., the polynomial fuzzy controller and observer for each class can be separately designed without lack of guaranteeing the stability of the overall control system in addition to converging state-estimation error (via the observer) to zero. Although, for the last class (Class III), the separation principle does not hold, we propose an algorithm to design polynomial fuzzy controller and observer satisfying the stability of the overall control system in addition to converging state-estimation error (via the observer) to zero. All the design conditions in the proposed approach can be represented in terms of SOS and are symbolically and numerically solved via the recently developed SOSTOOLS and a semidefinite-program solver, respectively. To illustrate the validity and applicability of the proposed approach, three design examples are provided. The examples demonstrate the advantages of the SOS-based approaches for the existing LMI approaches to T-S fuzzy observer designs.     

Robust H∞ control for Van de Vusse reactor via T–S fuzzy bilinear scheme

This paper proposes a fuzzy bilinear scheme including a fuzzy modeling method and a fuzzy controller for a class of uncertain nonlinear systems with an additive disturbance input. Firstly, this procedure of modeling describes how to transform a nonlinear system into a fuzzy bilinear system (FBS). For controller design problem, the parallel distributed compensation (PDC) method is adopted to design a fuzzy controller which ensures the robust asymptotic stability of the uncertain T–S FBS with an additive disturbance input and guarantees an H_∞ norm bound constraint on disturbance attenuation. Besides, some sufficient conditions are derived to guarantee the robust stabilization of the overall fuzzy control system via linear matrix inequalities (LMIs). Finally, the Van de Vusse reactor (Chen, Lin, Lin, & Tong, 2008; Chong & Zak, 1996; Kashiwagi & Rong, 2002; Li, Tsai, Lee, Hsiao, & Chao, 2008; Perez, Ogunnaike, & Devasia, 2000) with additive disturbance input is utilized to demonstrate the validity and feasibility of the proposed control scheme.     

Controller synthesis for uncertain fuzzy systems with integrating multiple time-varying delays

This article mainly investigates the controller synthesis for uncertain fuzzy systems with integrating multiple time-varying delays, which can describe a much larger class of nonlinear systems or uncertain time-delay systems. First, a sufficient stability condition for the unforced Takagi–Sugeno (T-S) fuzzy models with multiple time-varying delays and uncertainties are derived. By involving the parallel distributed compensator (PDC), some design conditions for the resulting closed-loop fuzzy systems are further presented. These proposed conditions are all expressed in terms of linear matrix inequalities (LMIs), and we can readily perform the PDC synthesis from current LMI solvers. Numerical examples are given to demonstrate the validity and superiority of the proposed approach.