基于终端不变集的 Markov 跳变系统约束预测控制

针对离散 Markov 跳变系统, 研究带输入输出约束的有限时域预测控制问题. 对于给定预测时域内的每条模态轨迹, 设计控制输入序列, 驱动系统状态到达相应的终端不变集内, 在预测时域外, 则寻求一个虚拟的状态反馈控制器以保证系统的随机稳定性, 在此基础上, 分别给出了以线性矩阵不等式 (LMI) 描述的带输入、输出约束预测控制器的设计方法.     

Markov跳变系统的输出反馈鲁棒预测控制

对离散时间Markov跳变系统, 当系统状态不完全可测时, 研究了一类基于输出反馈的鲁棒模型预测控制问题. 所研究系统为准线性参数时变的, 考虑在当前时刻系统的时变参数是已知的, 将来时刻未知的情况. 综合考虑系统存在多胞不确定性和有界噪声等因素, 通过运用线性矩阵不等式方法及变量变换思想, 将无穷时域性能指标的最小最大鲁棒预测控制问题转化为具有线性矩阵不等式约束的凸优化问题, 得到了系统的输出反馈控制律. 引入二次有界概念, 在满足输入输出约束的情况下, 保证闭环系统的随机稳定性. 数值算例验证了方法的有效性.     

多面体不确定线性系统具有约束满足保证的预测控制(英文)

基于不变集理论, 拓展了Chiscil等人提出的约束不变预测控制方法(ICPC), 提出了一种适用于带约束多面体不确定线性系统的预测控制的框架. 其关键在于为针对标称系统设计的在线优化问题附加适当的额外的鲁棒可行约束. 若优化问题在初始阶段可行, 则此约束可保证在线优化问题始终可行, 从而保证了实际系统中约束条件的始终满足. 同时提出了闭环系统鲁棒稳定的一个充分条件, 可为成本函数的选择提供指导以保证预测控制器的鲁棒镇定.     

Markov跳变系统的稳定自适应控制研究

研究一类据有严参数反馈的Markov跳变系统的自适应稳定控制问题,传统的参数估计是基于某种等价原理得到,估计形式单一,收敛速度较慢,且很难保证参数收敛时系统收敛。应用参数估计与控制器设计分离的方法,先应用微分几何中的流形浸入与不变的概念,得到一种新的参数估计表示式,再应用积分反推方法设计了Markov跳跃非线性系统的控制率,证明了在该控制律的作用下系统平衡点依概率全局渐近稳定。该方法解决了传统参数估计存在的问题,系统的动态性能可通过参数收敛的快慢来调节。仿真实验结果表明了该方法的有效性。     

一类离散不确定系统的Tube不变集离线鲁棒模型预测控制

针对一类输入和状态受限的离散线性不确定系统,提出了一种基于Tube不变集的离线鲁棒模型预测控制方法.首先针对输入和状态约束线性时不变标准系统,设计了改进的基于多面体不变集的离线模型预测控制算法,并证明了稳定性.其次对于存在未知有界干扰的实际不确定系统,引入了Tube不变集策略,通过设计对应标准模型的最优控制序列和状态轨迹,给出了实际不确定系统的离线Tube不变集控制策略,保证系统状态鲁棒渐近稳定,并收敛于终端干扰不变集.仿真结果验证了该控制方法的有效性.     

计及随机传感器时滞的不确定半Markov跳变系统鲁棒滑模控制

在实际系统中,系统参数与结构随机变化、未知外界干扰、传感器时滞等现象时有发生并严重影响了系统的稳定运行.为了解决这一问题,本文提出计及随机传感器时滞的一类不确定半Markov跳变系统鲁棒滑模控制方法,其中系统的传感器时滞通过使用Bernoulli随机分布进行描述.考虑系统状态信息不可测量条件下,文章设计模态依赖Luenberger观测器去估计半Markov跳变系统的运行状态.然后,本文构造一个积分滑模面并借助随机Lyapunov理论,提出两种半Markov跳变系统的随机稳定性分析方法.进而,文章提出基于观测器的滑模控制方法使得系统状态能够在有限时间内到达滑模面上以及滑模动态在H_∞性能指标γ下是随机稳定的.最后,通过一种基于他励直流电动机模型的数值仿真例子验证所设计的滑模控制方法的有效性与正确性.     

一类不确定离散Markov 跳变系统滑模状态反馈控制

针对具有不确定的离散Markov跳变系统,研究其滑模状态反馈控制问题.考虑系统的不确定满足匹配条件,以线性矩阵不等式形式给出了离散滑模面存在的充分条件,设计了具有指数趋近律的滑模控制器,保证了系统状态到达滑模面并在滑模带上随机镇定.数值仿真验证了所提出的控制方案的有效性.     

转移概率一般有界的Markov跳变系统有限时间保成本控制

针对系统信息不完全,本文研究了转移概率一般有界的随机Markov跳变系统有限时间控制问题.一般有界涵盖了部分未知、有界不确定和一般不确定3种不完全转移概率的情况.首先,研究该系统有限时间随机稳定问题,引入自由连接权矩阵分离未知转移概率信息,给出开环系统有限时间稳定的充分性判据;其次,借助Lyapunov方法和完全平方技术,得到了实现系统有限时间保成本控制的充分条件,给出了控制增益的设计方式以及性能指标的精确上界;最后,以太阳能锅炉控制系统为实例进行数值仿真,说明本研究结果的有效性和实用性.     

模型不确定非线性Markov 跳变系统的滤波算法

针对模型不确定非线性Markov跳变系统,提出一种新的滤波算法.相比于传统交互多模型粒子滤波,该方法通过引入前一时刻的滤波误差来增强原先由于不精确模型而造成权值较小的真实粒子在滤波过程中的作用,以此来改善算法的估计性能.仿真结果表明,该方法在处理含不确定模型参数的非线性Markov跳变系统状态估计问题时具有较好的性能.     

A linear programming algorithm for invariant polyhedral sets of discrete-time linear systems

In this paper we formulate necessary and sufficient conditions for an arbitrary polyhedral set to be a positively invariant set of a linear discrete-time system. Polyhedral cones and linear subspaces are included in the analysis. A linear programming algorithm is presented that enables practical application of the results stated in this paper.     

Markov Jump Linear Systems with switching transition rates: Mean square stability with dwell-time

The stability of a class of Markov Jump Linear Systems characterized by piecewise-constant transition rates and system dynamics is investigated. For these Switching Markov Jump Linear Systems, mean square stability is analyzed through the time evolution of the second-order moment of the state. The main result is a sufficient condition that guarantees mean square stability under constraints on the dwell-time between switching instants. An alternative condition based on Kronecker calculus is worked out. It is shown that both the stability criteria admit an LMI implementation.     

The minimal disturbance invariant set: Outer approximations via its partial sums

This paper is concerned with outer approximations of the minimal disturbance invariant set (MDIS) of a discrete-time linear system with an additive set-bounded disturbance. The k-step disturbance reachable sets (Minkowski partial sums) are inner approximations of MDIS that converge to MDIS. Enlarged by a suitable scaling, they can lead to outer approximations of MDIS. Three families of approximations, each based on partial sums, are considered. Theoretical properties of the families are proved and interrelated. Algorithmic questions, including error bounds, are addressed. The results are illustrated by computational data from several examples.     

Constrained stabilization of continuous-time linear systems

In this paper we consider the stabilization problem for linear continuous-time systems, under state and control constraints. We show that the largest domain of attraction to the origin can be arbitrarily closely approximated by a polyhedral domain of attraction associated to a certain (continuous) feedback stabilizing control and we show how to use existing numeric procedures for discrete-time systems to solve the continuous-time problem. We propose a new discontinuous stabilizing control law for scalar-input systems which has the advantage of being successfully applicable to systems with quantized control.     

Constrained receding horizon predictive control for nonlinear systems

The paper concerns the receding horizon predictive control of constrained nonlinear systems and presents an algorithm which relies on the online solution of a simple linear program (LP). Use is made of a finite control horizon in conjunction with a terminal inequality constraint and a predicted cost that includes a terminal penalty term. The optimization procedure is based on predictions made by linearized incremental models at points of a given seed trajectory and the effects of linearization error are taken into account to give a bound on the predicted tracking error. The algorithm is posed in the form of an LP and the proper selection of the terminal penalty term of the predicted cost guarantees the asymptotic stability. The results of the paper are illustrated by means of a simple example.     

Stochastic stability of Positive Markov Jump Linear Systems

This paper investigates on the stability properties of Positive Markov Jump Linear Systems (PMJLS’s), i.e. Markov Jump Linear Systems with nonnegative state variables. Specific features of these systems are highlighted. In particular, a new notion of stability (Exponential Mean stability) is introduced and is shown to be equivalent to the standard notion of 1-moment stability. Moreover, various sufficient conditions for Exponential Almost-Sure stability are worked out, with different levels of conservatism. The implications among the different stability notions are discussed. It is remarkable that, thanks to the positivity assumption, some conditions can be checked by solving Linear Programming feasibility problems.