Static Output Feedback Control for Interval Type‐2 T‐S Fuzzy Systems Based on Fuzzy Lyapunov Functions

This study aims to design an interval type‐2 (IT2) fuzzy static output feedback controller to stabilize the IT2 Takagi‐Sugeno (T‐S) fuzzy system. Conservative results may be obtained when a common quadratic Lyapunov function is utilized to investigate the stability of T‐S fuzzy systems. A fuzzy Lyapunov function is employed in this study to analyze the stability of the IT2 fuzzy closed‐loop system formed by the IT2 T‐S fuzzy model and the IT2 fuzzy static output feedback controller. Stability conditions in the form of linear matrix inequalities are derived. Several slack matrices are introduced to further reduce the conservativeness of stability analysis. The membership‐function shape‐dependent analysis approach is also employed to relax the stability results. The numerical examples illustrate the effectiveness of the proposed conditions.     

不确定离散时滞模糊系统的广义H2控制

针对一类利用Takagi-Sugeno（T-S）模糊模型，构建了具有状态和输入时滞的不确定离散时间非线性系统，研究了其广义H2稳定和控制器的设计问题。基于分段二次李雅普诺夫（Lyapunov）函数稳定性分析理论，设计出了分段静态输出反馈控制器，使闭环系统对于允许的不确定参数广义H2稳定。数值仿真例子验证了这种控制器的设计方法的有效性和其理论结果的正确性。     

Nonlinear Observer-based Control Design and Experimental Validation for Gasoline Engines with Exhaust Gas Recirculation

This paper presents a nonlinear observer-based control design approach for gasoline engines equipped with exhaust gas recirculation (EGR) system. A mean value engine model is designed for control which includes both the intake manifold and exhaust manifold dynamic focused on gas mass flows. Then, the nonlinear feedback controller based on the developed model is designed for the state tracking control, and the stability of the close loop system is guaranteed by a constructed Lyapunov function. Since the exhaust manifold pressure is usually unmeasurable in the production engines, a nonlinear observer-based feedback controller is proposed by using standard sensors equipped on the engine, and the asymptotic stability of the both observer dynamic system and control dynamic system are guaranteed with Lyapunov design assisted by the detail analysis of the model. The experimental validations show that the observer-based nonlinear feedback controller is able to regulate the intake pressure and exhaust pressure state to the desired values during both the steady-state and transient conditions quickly by only using the standard sensors.     

一类T-S模糊广义系统的稳定性研究

针对T-S模糊广义系统,基于模糊Lyapunov函数研究了其渐近稳定性问题。简化了传统的T-S模糊广义系统模型的表达式,根据李亚普诺夫稳定性理论,分别选取普通Lya-punov函数和模糊Lyapunov函数来讨论该系统的稳定性问题,得到了保证稳定性的充分条件;基于模糊Lyapunov函数得出的稳定性条件线性矩阵不等式个数少,减小了计算量。数值仿真实例验证了该方法的有效性。     

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.     

Stabilisation of discrete-time polynomial fuzzy systems via a polynomial lyapunov approach

This paper deals with the problem of designing a controller for a class of discrete-time nonlinear systems which is represented by discrete-time polynomial fuzzy model. Most of the existing control design methods for discrete-time fuzzy polynomial systems cannot guarantee their Lyapunov function to be a radially unbounded polynomial function, hence the global stability cannot be assured. The proposed control design in this paper guarantees a radially unbounded polynomial Lyapunov functions which ensures global stability. In the proposed design, state feedback structure is considered and non-convexity problem is solved by incorporating an integrator into the controller. Sufficient conditions of stability are derived in terms of polynomial matrix inequalities which are solved via SOSTOOLS in MATLAB. A numerical example is presented to illustrate the effectiveness of the proposed controller.     

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.     

离散模糊系统分析与设计的模糊Lyapunov方法

研究离散T-S模糊控制系统基于模糊Lyapunov函数的稳定性分析及控制器设计问 题.首先,构造出离散型模糊Lyapunov函数,模糊Lyapunov函数是系数与T-S模糊系统的模糊 规则权重相对应的复合型Lyapunov函数.然后,得到了开环系统新的稳定性充分条件,与公共 Lyapunov方法的结果相比,这一条件更为宽松.进而,基于一系列线性矩阵不等式设计出模糊 控制器.最后,仿真实例说明了该方法的算法和本文条件的优越性.     

基于分段模糊Lyapunov方法的离散模糊系统分析与设计

研究了基于分段模糊Lyapunov函数的离散T-S模糊控制系统稳定性分析及控制器设计问题．首先,在定义离散型分段模糊Lyapunov函数的基础上,提出了一个新的判定开环离散T-S模糊系统稳定性的充分条件．该条件仅需在每个最大交叠规则组内分别满足模糊Lyapunov方法中的条件,从而降低了公共Lyapunov方法和模糊Lyapunov方法的保守性和难度．然后,利用并行分布补偿方法对闭环系统的稳定性进行了分析并设计了模糊控制器．最后,一个仿真示例说明了本文方法的有效性和优越性．     

一类离散切换模糊系统的稳定性

针对离散模糊系统,提出一类离散切换模糊系统的稳定性问题.使用切换技术及单Lyapunov函数、多Lyapunov函数方法构造出连续状态反馈控制器,使得相应的闭环系统渐近稳定,同时设计可以实现系统全局渐近稳定的切换律.模型中的每个切换系统的子系统是离散模糊系统,取常用的平行分布补偿PDC控制器,主要条件以凸组合和矩阵不等式的形式给出,具有较强的可解性.计算机仿真结果表明设计方法的可行性与有效性.     

Functional observer-based fuzzy controller design for continuous nonlinear systems

This paper presents a novel method of synthesising controllers for nonlinear systems represented by Takagi--Sugeno fuzzy model using functional observer. The proposed method uses minimum order observer for estimating the control input of each rule as a function of states. Existence conditions of the functional observer-based controller are provided in the form of rank equality conditions. The stability conditions of the observer are obtained using quadratic Lyapunov function, and the conditions are presented in the form of linear matrix inequalities. Observer parameters can be obtained by solving these inequalities. Finally, systematic synthesis procedures for constructing the observer are presented. Examples with simulation output are given to demonstrate this method and to compare its performance with a conventional full-state observer-based controller.     

Robust H2 guaranteed cost fuzzy control for uncertain discrete‐time fuzzy systems via poly‐quadratic Lyapunov functions

In this paper, new approaches regarding H₂ guaranteed cost stability analysis and controller synthesis problems for a class of discrete‐time fuzzy systems with uncertainties are investigated. The state‐space Takagi‐Sugeno fuzzy model with norm‐bounded parameter uncertainties is adopted. Based on poly‐quadratic Lyapunov functions, sufficient conditions for the existence of the robust H₂ fuzzy controller can be obtained in terms of linear matrix inequalities (LMIs). Furthermore, a convex optimization problem with LMI constraints is formulated to design a suboptimal fuzzy controller which minimizes the upper bound on the quadratic cost function. The effectiveness of the proposed design approach is illustrated by two examples. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

不确定Van der Pol混沌系统的模糊同步控制

本文研究了不确定Van der Pol混沌系统的同步问题,并进行了基于规则的模糊逻辑控制器(FLC)的控制。首先寻找主从Van der Pol混沌系统满足Lyapunov稳定性理论的条件,在此基础上建立模糊规则,设计模糊控制器,实现不确定混沌系统的同步。通过不确定VanderPol混沌系统的两组仿真结果,验证了模糊同步控制方法具有很好的鲁棒性。最后为了进一步验证该方法的有效性,本文在相同条件下,利用反馈控制的方法实现不确定主从VanderPol混沌系统的同步,然后再将此方法的仿真结果与本文的模糊同步控制方法的仿真结果在稳态误差及同步所需时间这两个方面进行对比分析。分析结果验证了本文同步方法的可行性及有效性。     

Fuzzy guaranteed cost control for nonlinear systems with time-varying delay

This paper focuses on the problem of guaranteed cost control for Takagi-Sugeno (T-S) fuzzy systems with time-varying delayed state. A linear quadratic cost function is considered as a performance index of the closed-loop fuzzy system. Then, the guaranteed cost control of the closed-loop fuzzy system is discussed, and the sufficient conditions are provided for the construction of a guaranteed cost controller via state feedback and observer-based output feedback. When these conditions, which are given in terms of the feasibility of linear matrix inequalities (LMIs), are satisfied, the designed state feedback controller and observer-based controller gain matrices can be obtained via a convex optimization problem. Two illustrative examples are provided to demonstrate the effectiveness of the approaches proposed in this paper.     

基于观测器的不确定T-S模糊系统鲁棒镇定

为带有参数不确定性的T-S模糊控制系统提出了新的基于观测器的鲁棒输出镇定条件. 该条件用来设计模糊控制器和模糊观测器. 为了设计模糊控制器和模糊观测器, 用T-S模糊模型来表示非线性系统, 并运用平行分布补偿观念. 充分条件基于二次Lyapunov函数, 通过将模糊系统的鲁棒镇定条件表述为一系列矩阵不等式, 比以往文献中列出的条件具有更小的保守性. 该不等式为双线性矩阵不等式, 可分两步骤先后解得使T-S模糊系统镇定的控制器增益和观测器增益. 最后, 通过对一个具有不确定性的连续时间非线性系统控制的例子证明了提出方法比以往方法更宽松.     

基于分段Lyapunov 函数的Hammerstein-Wiener 非线性预测控制

针对输入和输出受约束的Hammerstein-Wiener型非线性系统,建立T-S模糊模型,并提出一种基于分段Lyapunov函数的非线性预测控制算法.通过构造分段二次Lyapunov函数,分析非线性系统的稳定性,降低普通二次Lyapunov函数的保守性;通过离线设计分段反馈控制律,在线实施符合条件的反馈控制律,极大程度地提高了在线计算效率.仿真结果验证了该方法的有效性.     

Improved results on stability analysis and controller synthesis for T-S fuzzy systems

This paper is concerned with the stability analysis and synthesis issues for T-S fuzzy systems. By fully using the properties of fuzzy weighting functions and matrix inequalities, two improved sufficient stability conditions are derived based on the common Lyapunov function and fuzzy Lyapunov function, respectively. It is not necessary to require every fuzzy subsystem to be stable in these conditions. Following the analysis, both parallel and non-parallel distributed compensation controllers are obtained by solving linear matrix inequalities. Finally, four examples are given to show the effectiveness of our proposed approach and the advantages of the approach over existing methods.     

Sum-of-squares-based fuzzy controller design using quantum-inspired evolutionary algorithm

In the field of fuzzy control, control gains are obtained by solving stabilisation conditions in linear-matrix-inequality-based Takagi–Sugeno fuzzy control method and sum-of-squares-based polynomial fuzzy control method. However, the optimal performance requirements are not considered under those stabilisation conditions. In order to handle specific performance problems, this paper proposes a novel design procedure with regard to polynomial fuzzy controllers using quantum-inspired evolutionary algorithms. The first contribution of this paper is a combination of polynomial fuzzy control and quantum-inspired evolutionary algorithms to undertake an optimal performance controller design. The second contribution is the proposed stability condition derived from the polynomial Lyapunov function. The proposed design approach is dissimilar to the traditional approach, in which control gains are obtained by solving the stabilisation conditions. The first step of the controller design uses the quantum-inspired evolutionary algorithms to determine the control gains with the best performance. Then, the stability of the closed-loop system is analysed under the proposed stability conditions. To illustrate effectiveness and validity, the problem of balancing and the up-swing of an inverted pendulum on a cart is used.     

Quadratic boundedness via dynamic output feedback for constrained nonlinear systems in Takagi–Sugeno’s form

This paper studies output feedback stabilization of Takagi–Sugeno fuzzy systems with input or state constraint and bounded noise. A dynamic output feedback controller is adopted, rather than a controller based on the state observer. The notion of quadratic boundedness specified by a common Lyapunov matrix, which is novel in fuzzy control, is invoked to handle the noise. Under the proposed controller, the state of the closed-loop system is stabilizing to an ellipsoid specified by this common Lyapunov matrix. Two numerical examples are given to show the effectiveness of the controller.