输入饱和约束下一类多智能体编队系统鲁棒一致性分析

针对输入饱和约束奈件下具有不对称时滞的二阶多智能体编队系统的鲁棒一致性问题,本文综合利用Lya-punov-Krasovskii泛函方法和线性矩阵不等式的方法对其进行了研究.首先在n维欧氏空间中建立了二阶多智能体所组成的编队系统的数学模型;然后设计了分布式的基于一致性的具有饱和约束和不对称时滞的编队控制律;进一步,利用非线性扇区法处理了饱和项,将其转化为一种简单的非线性项,从而建立了Lyapunov-Krasovskii泛函,并利用LMI方法对编队系统进行了鲁棒一致性分析,得到了系统达到鲁棒一致时的线性矩阵不等式条件,并通过仿真分析验证了所得条件的正确性.     

一类时滞不确定非线性系统的自适应鲁棒H∞控制

本文针对一类同时具有未知上界时滞不确定性和外部扰动的非线性系统，在非线性H∞控制的理论框架内讨论了系统的自适应鲁棒H∞控制问题，通过自适应律估计时滞不确定性的上界，并且基于Lyapunov-Krasovskii函数和Hamilton-Jacobi不等式获得使鲁棒控制问题可解的自适应鲁棒控制器。     

一类非线性时滞系统的鲁棒H∞滤波器设计

 研究了满足下列条件的时滞系统的鲁棒H_∞滤波问题:假设系统的参数矩阵带有不确定性,且不确定参数是时变且范数有界的.在系统的状态与输出中同时都含有非线性无穷分布时滞与离散时滞.在设计滤波器的过程中,引入了一个新的Lyapunov-Krasovskii泛函.通过线性矩阵不等式技术,提出了参数不确定时滞系统的鲁棒H_∞滤波器存在的时滞依赖条件.鲁棒H_∞滤波器可以保证带有参数不确定性的滤波误差系统是渐近稳定的,并且满足给定的H_∞性能指标.通过仿真的研究证明了该方法的有效性.     

不确定系统的鲁棒容错H∞控制

针对不确定线性连续系统,研究了执行器失效情况下的鲁棒容错H∞控制问题.利用LMI,给出了不确定线性系统对任意执行器故障均保持渐近稳定且满足给定干扰衰减指标的鲁棒容错H∞控制器存在的充要条件,讨论了参数不确定线性系统的鲁棒容错H∞控制器的设计问题.根据凸优化理论,进一步给出了鲁棒容错最优H∞控制器的线性凸优化设计算法和设计步骤.采用所设计的状态反馈控制器,当任意执行器出现故障时,闭环系统仍保持渐近稳定且满足给定的干扰衰减性能指标.数值仿真例子验证了该设计方法的可行性和有效性.     

基于LMI的时变时滞Cohen-Grossberg神经网络鲁棒稳定性

 研究了时变时滞Cohen-Grossberg神经网络的全局鲁棒稳定性问题.基于线性矩阵不等式技术,给出了保证时变时滞Cohen-Grossberg神经网络平衡点唯一性和全局鲁棒稳定性的新判据.这些新判据不依赖于时滞的大小和放大函数,且与现有的一些结果相比,具有易于验证、适用范围广、条件更不保守等特点.仿真结果验证了本文方法的有效性.     

一类非线性不确定时滞系统鲁棒容错控制

研究一类不确定非线性时滞系统的鲁棒容错控制问题.针对不确定非线性时滞系统,基于执行器连续型增益故障模式,利用Lyapunov-Krasovskii泛函方法和线性矩阵不等式方法,推导了当一类非线性不确定系统满足一定范数有界条件时,闭环系统时滞无关鲁棒容错控制器存在的充分条件,并给出了状态反馈鲁棒容错控制器的设计方法.将所设计的状态反馈控制方法应用于某一非线性不确定时滞系统,仿真结果表明设计的控制器不仅使得该故障系统对于执行器故障具有完整性,并且能达到给定的H∞性能指标,从而验证了所提出方法的可行性和有效性.     

时滞依赖型区间时滞系统非脆弱H_∞控制

针对一类状态和控制输入矩阵均为区间矩阵的不确定时滞系统,其中状态和控制输入同时具有未知但有上界的时间滞后,基于Lyapunov稳定性理论,利用线性矩阵不等式(LMI)方法,讨论了该类时滞系统的时滞依赖型非脆弱H∞状态反馈控制器设计问题.在区间不确定性和控制器执行机构扰动均满足增益有界条件下,得到了该类时滞系统的满足H∞性能的一个充分条件.通过求解一个线性矩阵不等式(LMIs)组,即可获得鲁棒H∞控制器.最后对某型飞机作机动飞行仿真,仿真结果表明该鲁棒控制器设计方法是有效的.     

鲁棒最小二乘在测位探测器建模中的应用

本文主要讨论了鲁棒最小二乘方法在测位控制器建模中的应用。首先简单介绍了鲁棒最小二乘方法的原理及几何解释;对测位控制器的输入误差的结构进行了估计,然后利用这种误差结构所确定的鲁棒最小二乘方法进行测位控制器建模,生成了模型参数,并对所生成的模型参数进行数字仿真验证和误差适应性测试,分析了各种测试结果,从而证明了在有不确定性扰动因素的情况下,利用鲁棒最小二乘方法建模对提高测位控制器的控制精度是有效而可行     

一类不确定关联时滞系统的可靠保性能鲁棒控制

针对一类具有参数不确定性、非线性扰动和多时变时滞的关联系统,采用[0,σ]故障模型,提出了考虑执行器故障的可靠保性能鲁棒控制问题。基于Lyapunov函数和线性矩阵不等式（LMI）方法,得到系统存在可靠保性能控制器的充分条件和控制器的设计方法,并给出了系统的可保性能的表达式。     

参数不确定的单时滞系统基于简化的L-K泛函的稳定性分析

参数不确定和时滞广泛存在于各种实际的控制系统中,而且它们往往是导致系统不稳定或性能下降的原因。本文基于Lyapunov稳定性理论,通过构造简化的Lyapunov-Krasovskii泛函,同时应用线性矩阵不等式(LMI:linearmatrix inequality)方法,研究了参数不确定和单时变时滞系统的鲁棒稳定性问题,并导出了由LMI表示的该类系统的鲁棒稳定性判据,而且,通过这类简化的L-K泛函,在充分利用时滞信息的基础上减少了判据的保守性。最后借助含不确定性扰动的具有单时变时滞的单机-无穷大系统模型,分析了保持鲁棒稳定时系统可承受的最大时滞的界限,数值仿真验证了方法的有效性。     

Robust Exponential Stabilization for Sampled-Data Systems with Variable Sampling and Packet Dropouts

This paper investigates the problem of robust exponential stabilization for sampled-data systems with variable sampling and packet dropouts. It is assumed that the system parameter uncertainties are norm-bounded and appear in both the state and input matrices. An input delay approach is adopted to model the sample-and-hold behavior with a time-varying delayed control input, and a switched system approach is proposed to model the data-missing phenomenon. On this basis, the sampled-data control system with variable sampling and packet dropouts is modeled as a switched system with time-varying delay. The objective is to design a sampled-data controller to guarantee the robust exponential stability of the resulting closed-loop system. Based on a new piecewise time-dependent Lyapunov functional, novel sufficient conditions are derived for the existence of robustly exponentially stabilizing sampled-data controllers. It is shown that the controller gains can be obtained by solving a set of linear matrix inequalities. Two simulation examples are given to demonstrate the effectiveness of the proposed method.     

Delay-Dependent Passivity and Passification for Uncertain Singularly Perturbed Markovian Jump Systems with Time-Varying Delay

This paper is concerned with passivity analysis and passivity-based controller design for uncertain singularly perturbed Markovian jump systems with time-varying delay in an interval. Firstly, a delay-dependent condition for the considered system to be mean-square exponentially stable and robustly passive is derived in terms of linear matrix inequality. Then, the passification problem is investigated. Based on the obtained passivity condition, the existence of the desired state feedback controller is established. Numerical examples are presented to show the effectiveness of the proposed method.     

A Delay Decomposition Approach to Delay-Dependent Robust Passive Control for Takagi–Sugeno Fuzzy Nonlinear Systems

This paper is concerned with the problem of delay-dependent robust passive control for a fuzzy nonlinear system with time-varying delays. A Takagi–Sugeno fuzzy model approach is exploited to design a passive control for nonlinear systems with time-varying delay. By decomposing the delay interval into multiple equidistant subintervals, new Lyapunov–Krasovskii functionals (LKFs) are constructed on these intervals. Employing these new LKFs, a new robust passive control criterion is proposed in terms of linear matrix inequalities, which is dependent on the size of the time delay. We also design a state feedback controller that guarantees a robustly strictly passive closed-loop system for all admissible uncertainties. Finally, two numerical examples are given to illustrate the effectiveness of the developed techniques.     

空间光通信中精跟踪控制器的设计

精跟踪伺服系统设计是APT的核心技术,决定了通信链路能否建立以及通信系统的性能.针对空间光通信中压电陶瓷驱动FSM偏转具有非线性、时变不确定性和纯滞后等特性,提出变论域自适应模糊PID控制方法.引入变论域思想,并通过对输入变量加入伸缩因子的方式来实现变论域的目的,自适应能力和抗干扰能力明显增强.可有效解决稳定性与准确性的矛盾.实验结果表明:模糊PID控制算法增强了伺服系统鲁棒性,并提高了伺服系统实时性;跟踪精度可达到5μrad,对卫星平台振动和大气湍流引起信标光斑抖动有一定的抑制作用,能够满足空间光通信精跟踪精度的要求.     

Analytical analysis and feedback linearization tracking control ofthe general Takagi-Sugeno fuzzy dynamic systems

The Takagi-Sugeno (TS) fuzzy modeling technique, a black-box discrete-time approach for system identification, has widely been used to model behaviors of complex dynamic systems. The analytical structure of TS fuzzy models, however, is unknown, causing at two major problems. First, the fuzzy models cannot be utilized to design controllers of the physical systems modeled. Second, there is no systematic technique for designing a controller that is capable of controlling any given TS fuzzy model to achieve the desired tracking or setpoint control performance. In this paper, we provide solutions to these problems. We have proved that a general class of TS fuzzy models is a nonlinear time-varying ARX (Auto-Regressive with eXtra input) model. We have established a simple condition for analytically determining the local stability of the general TS fuzzy dynamic model. The condition can also be used to analytically check the quality of a TS fuzzy model and invalidate the model if the condition warrants. We have developed a feedback linearization technique for systematically designing an output tracking controller so that the output of a controlled TS fuzzy system of the general class achieves perfect tracking of any bounded time-varying trajectory. We have investigated the stability of the tracking controller and established a condition, in relation to the stability of non-minimum phase systems, for analytically deciding whether a stable tracking controller can be designed using our method for any given TS fuzzy system. Three numerical examples are provided to illustrate the effectiveness and utility of our results and techniques     

Adaptive robust pressure control of variable displacement axial piston pumps with a modified reduced-order dynamic model

Variable displacement axial piston pumps (VDAPPs) are wildly used in mobile working machines and they play a key role in machine’s energy-saving load sensing (LS) systems. Typically, electric load sensing (ELS) systems utilize traditional linear control methods, which only can realize limited control flexibility and performance. This study proposes and experimentally verifies an adaptive robust pressure control strategy for a VDAPP system. To facilitate the model-based controller design, a modified reduced-order dynamic modeling of VDAPPs is proposed. Furthermore, an adaptive robust backstepping control strategy is designed to deal with the dynamic nonlinearities and parametric uncertainties of the VDAPP system for achieving accurate pressure tracking. The controller design consists of two steps, processing the pump pressure tracking and the axial angle control, respectively. Comparative experiments and simulations with different working conditions were performed to validate the advantages of the proposed control strategy. The proposed controller achieved higher pressure tracking accuracy and it showed great capability in dealing with dynamic nonlinearities, uncertainties, and time-varying disturbances.     

A method for improving the robustness of PID control

In this paper, an effective method is proposed for robust proportional-integral-derivative (PID) control that is easily implementable on commonly used equipment such as programmable logic controller (PLC) and programmable automation controller (PAC). The method is based on a two-loop model following control (MFC) system containing a nominal model of the controlled plant and two PID controllers. Basic features exhibited by the MFC structure are presented, and a technique to tune both component controllers is given. The proposed structures have been implemented in a programmable logic controller and tested on control plants with perturbed parameters. Also, the proposed control system has been checked for its performance in cases when the operation of PID controllers is based on fuzzy logic. Tuning rules for the fuzzy controllers in the presented MFC system have been proposed. Results of tests lend support to the view that the proposed control structures may find wide application to robust control of plants with time-varying parameters.     

Performance tuning of robust motion controllers for high-accuracy positioning systems

This paper presents a structural design method of robust motion controllers for high-accuracy positioning systems, which makes it possible to tune the performance of the whole closed-loop system systematically. First, a stabilizing control input is designed based on Lyapunov redesign for the system in the presence of uncertainty and disturbance. And adopting the internal model following control, robust internal-loop compensator (RIC) is proposed. By using the structural characteristics of the RIC, disturbance attenuation properties and the performance of the closed-loop system determined by the variation of controller gains are analyzed. Next, in order to design a robust motion controller for a high performance positioning system, dual RIC structure is proposed and it is shown that if the synthesis of the robust motion control law is performed in the RIC framework, the robust property of RIC can be naturally implanted in the feedback controller. The proposed structural design of robust motion controller provides a systematic approach to the problem of robust stability and performance requirement in the face of uncertainty. Furthermore, by allowing the tradeoffs between robust stability and performance to be quantified in a simple fashion, it can illuminate systematic design procedure of the robust motion controllers. Finally, the proposed method is verified through simulation and the performance is evaluated by experiments using a high-accuracy positioning system.     

Enhancing Design of Visual-Servo Delayed System

A robust adaptive predictor is proposed to solve the time-varying and delay control problem of an overhead crane system with a stereo-vision servo. The predictor is based on the use of a recurrent neural network (RNN) with tapped delays, and is used to supply the real-time signal of the swing angle. There are two types of discrete-time controllers under investigation, i.e., the proportional-integral-derivative (PID) controller and the sliding controller. Firstly, a design principle of the neural predictor is developed to guarantee the convergence of its swing angle estimation. Then, an improved version of the particle swarm optimization algorithm, the parallel particle swarm optimization (PPSO) method is used to optimize the control parameters of these two types of controllers. Finally, a homemade overhead crane system equipped with the Kinect sensor for the visual servo is used to verify the proposed scheme. Experimental results demonstrate the effectiveness of the approach, which also show the parameter convergence in the predictor.