具有输入时滞的不确定采样系统的鲁棒控制北大核心CSCD

针对具有输入时滞的结构不确定采样系统,研究了该类系统基于离散化模型的鲁棒控制器设计问题。通过将采样系统的连续的结构不确定对象离散化得到其近似模型,使具有输入时滞不确定采样系统的鲁棒控制器设计问题转换为讨论具有输入时滞的离散系统的鲁棒稳定性问题。利用Lyapunov函数的构造及解析技巧,给出了基于线性矩阵不等式(LMI)的输入时滞离散系统的鲁棒稳定性条件,并在此基础上将控制器参数化,得到了一个通过求解线性矩阵不等式(LMI)来获得采样系统鲁棒控制器的设计方法,所设计的控制器保证了系统的鲁棒稳定性,对结构摄动有着较好的鲁棒性能。最后,通过数值计算仿真验证了本文方法的可行性。     

具有输入时滞的不确定采样系统的鲁棒控制

针对具有输入时滞的结构不确定采样系统,研究了该类系统基于离散化模型的鲁棒控制器设计问题。通过将采样系统的连续的结构不确定对象离散化得到其近似模型,使具有输入时滞不确定采样系统的鲁棒控制器设计问题转换为讨论具有输入时滞的离散系统的鲁棒稳定性问题。利用Lyapunov函数的构造及解析技巧,给出了基于线性矩阵不等式(LMI)的输入时滞离散系统的鲁棒稳定性条件,并在此基础上将控制器参数化,得到了一个通过求解线性矩阵不等式(LMI)来获得采样系统鲁棒控制器的设计方法,所设计的控制器保证了系统的鲁棒稳定性,对结构摄动有着较好的鲁棒性能。最后,通过数值计算仿真验证了本文方法的可行性。     

时变不确定切换广义系统的鲁棒最优保性能控制

针对一类时变参数不确定切换广义系统,对其鲁棒最优保性能控制问题进行研究,假定其中的时变不确定性项是范数有界的,但不需要满足匹配条件。通过构造广义Lyapunov函数和线性矩阵不等式方法,给出系统鲁棒最优保性能控制器存在的充分条件。进一步,建立一个具有线性矩阵不等式约束的凸优化问题,得到鲁棒最优保性能控制律及闭环性能指标上界。最后用示例说明该方法的有效性。     

带不确定时滞的中立型系统之鲁棒非脆弱保性能控制

针对一类动态不确定时滞中立型系统,研究了非脆弱鲁棒保性能控制器设计问题.考虑的中立型系统和状态反馈控制器均具有不确定性.在适当的假设下利用Lyapunov稳定性方法,以线性矩阵不等式的形式,给出了使该动态时滞不确定中立型系统二次稳定及非脆弱鲁棒保性能状态反馈控制器存在的充分条件.通过求解相应的线性矩阵不等式就可得到系统的非脆弱鲁棒保性能控制器,同时也能保证二次性能函数不超过一个确定的界.最后,用数值仿真验证了所给方法的可行性.     

一类结构不确定采样系统的鲁棒H∞控制

本文针对一类结构不确定线性采样系统,研究了鲁棒H∞控制问题,给出了系统鲁棒稳定的充分条件及响应的鲁棒H∞控制律和最优鲁棒H∞控制律,控制律的求取通过借助一类线性矩阵不等式(LMI),或通过求取满足线性矩阵不等式约束的优化问题.仿真结果表明,系统在受到扰动后仍然是稳定的,同时给出了最优性能指标随外部扰动加权矩阵的变化规律.     

不确定广义大系统分散鲁棒H∞保性能控制

针对一类状态矩阵和控制矩阵存在参数不确定的广义大系统,研究其分散鲁棒H∞保性能控制问题,系统中不确定项具有数值界,可不满足匹配条件.基于广义系统的有界实引理,应用线性矩阵不等式(LMI)方法,给出了不确定广义大系统存在分散鲁棒H∞保件能控制器的一个LMI条件,并用这个线性矩阵不等式系统的可行解提供了一组分散鲁棒H∞保性能控制律的参数化表示,最后用例子说明该方法的应用.     

不确定多时滞系统非脆弱鲁棒保代价控制

针对一类含有多时滞的不确定线性系统，在控制器增益存在乘性和加性两种摄动形式时分别设计了非脆弱具有鲁棒性能的保代价控制器．利用构造的Lyapunov函数和线性矩阵不等式，证明并给出了非脆弱鲁棒保代价状态反馈控制问题有解的充分条件，仅通过求解相应的线性矩阵不等式就可得到非脆弱鲁棒保代价控制器．所设计的控制器不仅使闭环系统具有鲁棒性，能满足所给的的鲁棒保代价性能指标，而且当控制器增益参数变化时，系统性能指标同样能够满足要求．该系统对环境参数的变化具有更好的适应能力。     

基于观测器的不确定广义时滞系统保成本控制

讨论了基于观测器的一类不确定广义时滞系统的保成本控制问题,给出了系统保成本控制器的设计方法.控制器的构造使得闭环系统是鲁棒稳定的.利用线性矩阵不等式以及Lyapunov函数方法,给出了鲁棒保成本控制器存在的充分条件以及相应的可保成本指标,并证明了这个条件等价于一组线性矩阵不等式(LM Is)的可解性问题,同时推广了已知的相关结果.最后以算例验证了设计方法的有效性.     

一类分布时滞不确定系统的鲁棒非脆弱保性能控制器设计

研究了一类具有分布时滞的线性不确定系统的鲁棒非脆弱保性能控制问题.考虑分布时滞系统和状态反馈控制器均具有时变不确定性,通过构造新的含三重积分项的Lyapunov-Krasovskii泛函,并结合不等式推导技巧,以线性矩阵不等式形式给出了系统鲁棒非脆弱保性能控制器存在的充分条件.该方法保证了给定的二次性能函数不超过一个确定的界并且是分布时滞相关的.仿真实例表明了该方法的可行性和有效性.     

一类结构不确定采样系统的鲁棒控制

针对一类结构不确定性线性采样系统，在时域中用Lyapunov方法研究采样系统的鲁棒控制及最优鲁棒控制，给出了系统鲁棒稳定的充分条件以及相应的鲁棒控制律，控制律的求取借助于求解一类线性矩阵不等式（LMI），或求解满足特定线性不等式条件下的优化问题，算例结果表明，采样周期是一个关键性的设计参数。     

Controlling linear systems with nonlinear perturbations under sampled-data output feedback: digital redesign approach

This article develops a digital redesign (DR) technique for sampled-data observer-based output-feedback control of a continuous-time linear system with nonlinear perturbation. It is assumed that the nonlinear perturbation is a locally Lipschitz function. To deal with the discrete-time modelling error in nonlinear systems, as opposed to the previous approach, the DR problem is configured as a stabilisation one for error dynamics between the closed-loop system of nominal linear model under an analogue state-feedback controller and that of the linear system with the nonlinear perturbation under a sampled-data output-feedback controller. A constructive DR condition is formulated in the format of linear matrix inequalities. The stability of the actual sampled-data control system is guaranteed within the DR procedure. The effectiveness of the proposed DR methodology is demonstrated through a numerical simulation.     

Robust sampled-data control with random missing data scenario

The problem of robust sampled-data control for uncertain dynamic systems in the presence of missing data has been investigated. By using stochastic variables with a Bernoulli distributed white sequence to model missing data, along with time-varying norm-bounded uncertainties, and the input delay approach for sampled-data systems, two models for the considered sampled-data control system are proposed as the consecutive missing data scenario. Moreover, when data are missing, the control signals are held as the last received data. Sufficient conditions for the existence of desired robust sampled-data controllers are presented in the form of a linear matrix inequality. A numerical example is given to illustrate the validity of the proposed methods and to compare the results between the two proposed models of the sampled-data control system.     

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．     

Robust stability bounds for multi-delay networked control systems

In this paper, the robust stability of a perturbed linear continuous-time system is examined when controlled using a sampled-data networked control system (NCS) framework. Three new robust stability bounds on the time-invariant perturbations to the original continuous-time plant matrix are presented guaranteeing stability for the corresponding discrete closed-loop augmented delay-free system (ADFS) with multiple time-varying sensor and actuator delays. The bounds are differentiated from previous work by accounting for the sampled-data nature of the NCS and for separate communication delays for each sensor and actuator, not a single delay. Therefore, this paper expands the knowledge base in multiple inputs multiple outputs (MIMO) sampled-data time delay systems. Bounds are presented for unstructured, semi-structured, and structured perturbations.     

Decentralised sampled-data control for large-scale systems with nonlinear interconnections

This paper presents a decentralised sampled-data control technique for a class of large-scale systems, which are considered to consist of linear subsystems and nonlinear interconnections. The decentralised sampled-data controller design problem is established using a closed-loop subsystem. Based on the controller design problem, the stability condition is derived for a closed-loop large-scale system, and the maximum interconnection bound is guaranteed to satisfy the stability condition. Also, its sufficient condition is formulated in terms of linear matrix inequalities. Finally, the effectiveness of the proposed technique is verified by using an example of the multi-machine power system.     

Exponential sampled-data control for T–S fuzzy systems: application to Chua's circuit

ABSTRACT

This study deals with the chaotic phenomenon of nonlinear Chua's circuit for power generator systems. Takagi–Sugeno (T–S) fuzzy model of a nonlinear system is established. By constructing a suitable Lyapunov functional, exponential stability conditions are obtained for fuzzy systems. Based on the sampled-data control theory, extreme sensitivity is visualised in the state trajectory depending on the initial conditions and sampled-data fuzzy controllers are designed in the form of linear matrix inequality (LMI). Finally, some numerical simulation results are shown that the sampled-data fuzzy control system adopts a well-designed methodology.     

非线性时变时延系统的模糊采样最优控制

针对非线性时变时延系统,采用输入时延和自由权重矩阵方法研究模糊采样最优控制问题.应用T-S模糊系统表征非线性系统,控制器是零阶保持采样信号.由线性矩阵不等式给出最优控制准则,所设计的模糊采样控制器在闭环系统渐近稳定意义下可保证期望最优控制性能.最后,通过卡车拖车系统实验验证模糊采样控制设计方案的可行性.     

Robust guaranteed cost control of uncertain fuzzy systems under time-varying sampling

In practice, the system is often modeled as a continuous-time fuzzy system, while the control input is applied only at discrete instants. This system is called a sampled-data control system. In this paper, robust guaranteed cost control for uncertain sampled-data fuzzy systems is discussed. A guaranteed cost control where a quadratic cost function is bounded by a certain scalar, not only stabilizes a system but also considers a control performance. A typical sampled-data control is the zero-order input, which can be represented as a piecewise-continuous delay. Here we take a delay system approach to the sampled-data guaranteed cost control problem. The closed-loop system with a sampled-data state feedback controller becomes a system with time-varying delay. First, guaranteed cost control performance conditions for the closed-loop system are given in terms of linear matrix inequalities (LMIs). Such conditions are derived by using Leibniz–Newton formula and free weighting matrix method for fuzzy systems under the assumption that sampling time is not greater than some prescribed scalar. Then, a design method of robust guaranteed cost state feedback controller for uncertain sampled-data fuzzy systems is proposed. Examples are given to illustrate our robust sampled-data guaranteed cost control design.     

Sampled-data consensus of general linear multi-agent systems under switching topologies: averaging method

This paper investigates sampled-data consensus problems of general linear multi-agent systems under switching topologies. To perform the consensus analysis by the averaging method, the multi-agent system in the sampled-data setting is first converted into the continuous-time system with the input delay. Then, the approximate relationship between the states of this input delay system and the states of its averaged system is established by using the tool from non-standard analysis. Subsequently, a sufficient condition ensuring the sampled-data consensus is obtained by linear matrix inequalities. It is shown that the sampled-data consensus of general linear multi-agent systems, including exponential unstable agents, can be achieved, if the speed of topology switching is fast enough and the sampled-data consensus under the averaging topology can be achieved. Finally, numerical simulations are provided to demonstrate the effectiveness of theoretical analyses.