Robust reliable control design for networked control system with sampling communication

In this article, the problem of robust exponential stability and reliable stabilisation for a class of continuous-time networked control systems (NCSs) with a sample-data controller and unknown time-varying sampling rate is considered. The analysis is based on average dwell-time, Lyapunov–Krasovskii functional and linear matrix inequality (LMI) technique. The delay-dependent criteria are developed for ensuring the robust exponential stability of the considered NCSs. The obtained conditions are formulated in terms of LMIs that can easily be solved by using standard software packages. Furthermore, the result is extended to study the robust stabilisation for NCS with parameter uncertainties. A state feedback controller is constructed in terms of the solution to a set of LMIs, which guarantee the robust exponential stabilisation of NCS and the controller. Finally, numerical examples are presented to illustrate the effectiveness of the obtained results.     

Robust reliable guaranteed cost control of positive interval systems with multiple time delays and actuator failure

This paper addresses the robust reliable guaranteed cost control problem of positive interval systems with multiple time delays and actuator failure for a given quadratic cost function. Through constructing a Lyapunov–Krasovskii functional, a sufficient condition for the existence of robust reliable guaranteed cost controllers is established such that the closed-loop system is positive and asymptotically stable, and the cost function is guaranteed to be no more than a certain upper bound. Based on the linear matrix inequality method, a criterion for the design of robust reliable guaranteed cost controllers is derived which can tolerate all admissible uncertainties as well as actuator failure. Moreover, a convex optimisation problem with linear matrix inequality constraints is formulated to design the optimal robust reliable guaranteed cost controller which minimises the upper bound of the closed-loop system cost. A numerical example is given to show the effectiveness of the proposed methods.     

不匹配不确定线性时滞系统的鲁棒自适应控制

对一类同时具有匹配不确定性及结构确定不匹配不确定性的不确定时滞系统进行鲁棒自适应控制。首先,采用李雅谱诺夫函数方法,结合基于线性矩阵不等式的鲁棒控制器设计方法和变结构控制方法,设计鲁棒控制器,保证闭环系统的二次渐近稳定。利用自适应参数估计方法,设计具有匹配不确定性范数界估计能力的鲁棒自适应控制器,保证闭环系统的一致终结有界。结合算例,进行控制器的设计和仿真研究,验证所提出的设计方法的有效性。     

基于连续时间模型的多智能体系统采样数据一致性（英文）

This paper discusses the sampled-data consensus problem of multi-agent systems with general linear dynamics and timevarying sampling intervals. To investigate the allowable upper bound of sampling intervals, we employ the property of discretization of sampled-data to identify the upper bound on the variable sampling intervals via a continuous-time model. Without considering the states in the sampling intervals, the decrease of Lyapunov function is guaranteed only at each sampling time. Consequently, it results in a more robust sampling interval which is obtained by verifying the feasibility of LMIs. Subsequently, provided a limited matrix variable, the control gain matrix K is solved by the LMI approach. Numerical simulations are provided to demonstrate the effectiveness of theoretical results.     

基于连续时间模型的多智能体系统采样数据一致性

讨论了一般线性模型的多智能体系统具有时变采样间隔的采样数据一致性问题.首先基于连续时间模型,利用采样数据的离散时间特性分析时变采样间隔允许的上界.由于不考虑采样间隔之间的状态,Lyapunov函数仅需要在每个采样时刻保证递减.由此得到了一个利用线性矩阵不等式求解更低保守性的时变采样间隔上界的方法.接着通过参数化矩阵变量得到了基于线性矩阵不等式的控制器设计方法.最后数值仿真展示了理论结果的正确性.     

输出概率密度函数鲁棒弹性最优跟踪控制

研究了一类随机动态系统的鲁棒弹性最优跟踪控制问题。在采用B样条神经网络模型逼近随机动态系统的输出概率密度函数(PDF)的基础上,同时考虑系统模型和控制器增益不确定性,结合Lyapunov稳定性理论和线性矩阵不等式(LMI)技术,引入增广控制作用,设计基于广义状态反馈的鲁棒弹性最优跟踪控制器,目的是使系统的输出PDF跟踪给定PDF。通过求解LMI,所得控制器不仅能实现跟踪目的,而且能确保该随机动态系统全局稳定并满足一定的线性二次型性能指标上界。仿真结果表明该方法简单易行,且无需任何设计参数调整。     

Model reference resilient control for the helicopter with time‐varying disturbance

In this paper, the problem of model reference resilient control is investigated for the helicopter system with the time‐varying disturbance and unmeasurable states. Firstly, a disturbance observer and a state observer are built to estimate the time‐varying disturbance and unmeasurable states. Then, combining the methods of model reference control and disturbance observer–based control, the state feedback robust resilient control scheme and the dynamic output feedback robust resilient control method are proposed, respectively. Under the two developed robust resilient control schemes, sufficient conditions are obtained to guarantee that the helicopter system asymptotically tracks the reference model with H_∞ performance. Finally, simulation results are presented to show the effectiveness of the model reference resilient control method.     

New results on robust H-infinity control for discrete-time systems with interval time-varying delays

This paper deals with delay-dependent robust H-infinity control for uncertain discrete-time systems with interval time-varying delay. By using a new Lyapunov functional and the convex combination method, a new delay-dependent stability criterion is established. Some redundant variable matrices are removed in the new conditions, which makes the obtained results more efficient. Then, an iterative algorithm based on the cone complementarity Linearization method is proposed to obtain the delay-dependent robust H-infinity controller. Numerical examples are given to show the effectiveness of the proposed method.     

鲁棒模型预测控制在变风量空调系统中的应用

在变风量空调系统中二次泵压差控制可以有效地减少空调能耗,为克服二次泵模型的不确定性,提高二次泵变频调速控制的响应速度和精度,采用基于线性矩阵不等式的鲁棒预测控制策略。算法分为离线和在线两个部分,离线时首先用传统算法得出目标函数上界,以此为已知量重新优化得到一系列较大的渐近稳定的不变椭圆集。在线时,每个采样周期用三个相邻的椭圆集优化来对状态变量进行精确定位,并给出控制量。给出在线优化的理论证明。通过和传统算法的仿真比较,表明该算法的有效性。二次泵压差控制的实验表明该算法可得到较大的可行域,系统响应快,控制效果好。     

一类不确定混沌系统的模糊滑模控制与同步

针对一类具有不确定项的二阶连续时间混沌系统的定值跟踪控制和自混沌同步及异结构混沌同步问题,提出了一种模糊滑模变结构控制方法,设计了模糊滑模变结构控制器,并从理论上证明了控制系统的稳定性.在该控制器的作用下,可以实现两个相同或不同结构的混沌系统的控制与同步,且不受不确定性的影响,具有很强的鲁棒性.定值跟踪和同步控制的仿真结果表明,该控制器是有效的.     

基于动态调度的网络控制系统设计方法

针对网络控制系统中存在多回路共享网络资源的问题,本文提出一种基于反馈和预测机理的动态调度策略,根据当前的网络状态在线调整控制系统的采样周期,以适应当前网络中信息流的变化,达到改善网络运行性能的目的．采用动态调度策略的网络控制系统为不确定变采样周期系统,经过等效变换,将系统等效为一类具有参数不确定性的离散系统．基于建立的模型,给出系统的鲁棒控制器参数化设计方法,并通过仿真实例验证了所提方法的有效性．     

Model predictive control of distributed networked control systems with quantization and switching topology

This work is concerned with the robust model predictive control (MPC) for a class of distributed networked control systems (NCSs), in which the input quantization and switching topology are both considered. By utilizing the sector bound approach, the NCSs with quantization are converted into the linear systems with sector bound uncertainties. The topology switching is governed by a switching signal and the dynamic behavior is modeled as a switched control system. A new robust MPC design technique is derived to minimize the upper bound of a weighted quadratic performance index. Moreover, the conditions of both the recursive feasibility of the MPC design and the stability of the resulting closed‐loop system are developed. Finally, simulation results are presented to verify the effectiveness of the proposed MPC design.     

不确定系统的变结构鲁棒自适应控制及其在机械手控制中的应用

本文针对一类不确定非线性系统,通过状态微分同坯变换和反馈控制建立了系统的变结构鲁棒控制设计过程,并在此基础上提出了一种新型的变结构鲁棒自适应控制算法。该算法优点是:1)不需要确切知道系统不确定性,也不需要知道不确定性的界,而是利用自适应规律对系统不确定性范围进行在线估计;2)能够保证系统获得较为满意的动态性能;3)控制规律是连续性的,因而避免了一般变结构系统中的不连续控制所导致的颤振现象。为了说明本文所提算法的正确性,本文还以二连杆机械手为例讨论了其终端夹持不定载荷时的轨迹跟踪问题。     

Robust decentralized fast-output sampling technique based power system stabilizer for a multi-machine power system

Power-system stabilizers (PSSs) are added to excitation systems to enhance the damping during low-frequency oscillations. In this paper, the design of robust decentralized PSS for four machines with a 10-bus system using fast-output sampling feedback is proposed. The nonlinear model of a multimachine system is linearized at different operating points, and 16 linear state space models are obtained. For all of these plants, a common stabilizing state feedback gain, F, is obtained. A robust decentralized fast-output sampling feedback gain which realizes this state feedback gain is obtained using LMI approach. This method does not require all the states of the system for feedback and is easily implementable. This robust decentralized fast-output sampling control is applied to a nonlinear plant model of several machines at different operating (equilibrium) points. This method yields encouraging results for the design of power-system stabilizers.     

时滞关联大系统的分散变结构自适应控制

针对一类满足匹配条件的不确定性时滞关联大系统,提出了一种基于Lyapunov稳定性理论的分散变结构自适应控制方案.通过引入积分滑模和能在线估计不确定性扰动与时滞关联的界的自适应算法,保证了闭环系统的渐近稳定性,实现了系统的鲁棒自适应控制.所提出的方案具有较强的工程实用性.算例仿真的结果表明了该控制方案的可行性.     

H∞ output tracking control for uncertain networked control systems via a switched system approach

In this paper, the problem of H_∞ output tracking control for networked control systems with random time delays and system uncertainties is investigated. Effective sampling instant that is tightly related with transmission delay from sensor to actuator is proposed to ensure that the random variable time delay is always shorter than one effective sampling period. By using both active time‐varying sampling period strategy and hybrid node‐driven mechanism, the switching instant is coincided with the effective sampling instant. An augmented time‐varying networked tracking system model is provided by including the output tracking error as an additional state. However, random transmission delay causes indeterminate sampling period, which induces infinite subsystems. Gridding approach is introduced to transform the continuous time axis into discrete‐time sequences, which guarantees the finite number of switching rules. By employing multiple Lyapunov–Krasovskii functions, linear matrix inequality (LMI)‐based output tracking H_∞ performance analysis is presented, and robust switching H_∞ model reference tracking controller for networked control systems with communication constraints and system uncertainties is designed to guarantee asymptotic tracking of prescribed reference outputs while rejecting disturbances. Finally, simulation results illustrate the correctness and effectiveness of the proposed approaches. Copyright © 2015 John Wiley & Sons, Ltd.     

Exponential stability of impulsive systems with application to uncertain sampled-data systems

We establish exponential stability of nonlinear time-varying impulsive systems by employing Lyapunov functions with discontinuity at the impulse times. Our stability conditions have the property that when specialized to linear impulsive systems, the stability tests can be formulated as Linear Matrix Inequalities (LMIs). Then we consider LTI uncertain sampled-data systems in which there are two sources of uncertainty: the values of the process parameters can be unknown while satisfying a polytopic condition and the sampling intervals can be uncertain and variable. We model such systems as linear impulsive systems and we apply our theorem to the analysis and state-feedback stabilization. We find a positive constant which determines an upper bound on the sampling intervals for which the stability of the closed loop is guaranteed. The control design LMIs also provide controller gains that can be used to stabilize the process. We also consider sampled-data systems with constant sampling intervals and provide results that are less conservative than the ones obtained for variable sampling intervals.     

动态不确定多输入多输出系统的变结构鲁棒控制

本文仅利用输入输出数据给出了一种动态不确定多输入多输出系统的变结构控制器设计机制，控制系统的设计中引入了一个严格正实的模型．应用适当逻辑切换的状态变量滤波器实现变结构控制．证明了所提方案能保证全局输出有界稳定并能实现滑模控制和渐近跟踪参考模型的输出．该设计方案对结构不确定性具有一定的鲁棒性．仿真结果表明了所提方案的有效性．     

时延网络控制系统的模型预测控制

针对有输入约束的不确定时延网络控制系统,提出鲁棒模型预测控制方法;其中,将不确定时延建模为范数有界的输入矩阵的不确定性．给出了鲁棒性能指标的上界和系统渐近稳定的充分条件,通过在线求解LMI凸优化问题得到状态反馈控制律．仿真例子验证了该方法的有效性．     

一类不确定非线性系统的变结构鲁棒控制及应用

针对一类具有不确定性的非线性系统，在假定系统模型不确定性界已知的情况下，提出一个变结构鲁棒控制算法。以船舶减摇鳍非线性控制系统为例，进行变结构鲁棒自适应控制器的设计，经仿真研究表明，它可以使控制系统具有较强的鲁棒性。