大系统的动态递阶控制

本文提出了一种镇定线性大系统的动态递阶控制新方案.对于分散控制线性大系统,如 果是可控可观的,则可以设计一个上一层系统,并能确定它的最小维数,使所产生的新系统在 递阶控制下无固定模,从而能够得到一个协调控制器,使整个闭环系统能任意配置极点.这种 新的大系统动态递阶控制具有实际意义,其递阶控制器的设计也简单易行.     

非线性最小相位系统输出反馈镇定的一个注记

讨论了单输入单输出非线性最小相位系统的动态输出反馈镇定.通过加积分器和非 线性变换将系统化为一种标准形式,并基于标准形式的线性部分提出了动态补偿器的设计方 法.然后根据得到的中心流形的表达式和稳定性定理,在零动态流形为一维时,证明了闭环系 统的渐近稳定性,最后给出了一个零动态不具有齐次渐近稳定性但仍能动态输出反馈镇定的 非线性最小相位系统的例子.     

基于反馈线性化的MIMO非最小相位系统指数镇定

针对仿射多输入多输出非线性非最小相位系统,提出了一种新的镇定方案.用反馈线性化解耦系统输入输出关系,通过高增益状态反馈镇定系统外部动态,用模型预测控制镇定内部动态,所设计控制器能保证闭环系统的指数稳定性.仿真结果表明了所提出方法的有效性和优越性.     

离散时间非线性最小相位系统的动态输出反馈镇定

研究了离散时间非线性最小相位系统的动态输出反馈镇定.首先对离散时间非线性系 统引入了逼近渐近稳定性的概念.基于此概念,提出了一种动态补偿器设计的新方法.主要结果 是,如果一非线性系统的零动态是逼近渐近稳定的,则能用动态输出反馈镇定.动态补偿器的设 计是构造性的.     

关于最小分散镇定结构的研究

本文考察线性时不变多变量系统的分散镇定问题,揭示了局部控制站间的通信与消除固 定模间的内在联系,并由此把求最小(最经济)分散可镇定结构问题转化成一个显式的特殊0-1 规划问题,导出了一种求最小分散可镇定结构的有效算法.     

带有不确定性参数的多变量非线性系统的半全局实用镇定

研究一类含有零动态和不确定性参数的多输入多输出非线性系统的镇定问题,通过 构造一个组合Lyapunov函数,对非线性动态部分设计了一个控制器可半全局实用镇定整个 闭环系统的平衡点.仿真实例说明了所采用方法的有效性.     

一类线性不可观非线性系统的动态输出反馈镇定

本文研究一类不可观非线性系统的动态输出反馈镇定,基于逼近渐近稳定性的概念,给出了动态输出反馈可镇定的充分条件,本文主要结果的直接推论是零动太逼近渐近稳定的最小相位系统能用动态输出反馈镇定,本文的方法也能处理非最小相位系统。     

一类带不确定输入动态非线性系统的输出反馈鲁棒镇定

研究一类带不确定输入动态非线性系统的输出反馈鲁棒镇定问题.通过在高增益观测器引入新的设计参数,改进了通常的高增益反馈控制的设计方法.在输入动态满足零相对阶最小相位的假设下,基于非分离设计原则给出了动态输出反馈控制器的设计方法,所设计的控制器实现了对任意可允许不确定输入动态的全局鲁棒镇定.     

基于反馈线性化的MIMO非最小相位系统指数镇定

针对仿射多输入多输出非线性非最小相位系统,提出了一种新的镇定方案.用反馈线性化解耦系统输入输出关系,通过高增益状态反馈镇定系统外部动态,用模型预测控制镇定内部动态,所设计控制器能保证闭环系统的指数稳定性.仿真结果表明了所提出方法的有效性和优越性.

     

关于最小分散镇定结构的研究

本文考察线性时不变多变量系统的分散镇定问题,揭示了局部控制站间的通信与消除固定模间的内在联系,并由此把求最小(最经济)分散可镇定结构问题转化成一个显式的特殊0-1规划问题,导出了一种求最小分散可镇定结构的有效算法。     

Controllability under decentralized information structure

In this paper, the controllability under decentralized information structure is studied for linear continuous-time systems. It is defined as follows. A system is controllable under the decentralized information structure if there exists a decentralized control law which transfers any unknown initial state to the origin in a finite time interval Necessary and sufficient conditions of the controllability under the decentralized information structure are given. It is also shown that the controllability under the decentralized information structure is a necessary condition of the pole-assignability with a local dynamic feedback control law.     

大系统的动态递阶伺服控制

本文针对大系统的伺服控制问题,提出了动态递阶伺服控制这一新的伺服控制方案,给出了动态递阶伺服控制器的结构及动态递阶伺服控制问题可解的条件。研究结果表明,这种伺服控制方案可用来解决有不稳定分散固定模的大系统的伺服控制问题。     

Near optimal decentralised control with a pre-specified degree of stability

In this paper we develop a method for computing near optimal decentralised control with a pre-specified degree of stability for large scale, linear, interconnected dynamical systems. All the calculations in the new method are performed off-line using a three level hierarchical structure. We provide a condition the satisfaction of which ensures that the system has a pre-specified degree of stability. We also show that the control developed using the new method is more stable than the optimal decentralised control obtained by neglecting all interactions between the subsystems.     

线性时滞系统对时滞参数的自适应控制

针对实际中线性时滞系统的时滞常数往往不能精确已知的缺点,对具有状态滞后的线性时滞系统提出一种对时滞常数的自适应控制方案,其控制器存在的充分条件由一个线性矩阵不等式（LMI）的形式给出,并对整个闭环系统的稳定性进行了分析。     

On the receding horizon hierarchical optimal control of manufacturing systems

This paper concerns the development of a hierarchical framework for the integrated planning and scheduling of a class of manufacturing systems. In this framework, dynamic optimization plays an important role in order to define control strategies that, by taking into account the dynamic nature of these systems, minimize customized cost functionals subject to state and control constraints. The proposed architecture is composed of a set of hierarchical levels where a two-way information flow, assuming the form of a state feedback control, is obtained through a receding horizon control scheme. The averaging effect of the receding horizon control scheme enables this deterministic approach to handle random and unexpected events at all levels of the hierarchy. At a given level, production targets to the subsystems immediately below are defined by solving appropriate optimal control problems. Efficient iterative algorithms based on optimality conditions are used to yield control strategies in the form of production rates for the various subsystems. At the lower level, this control strategy is further refined in such a way that all sequences of operations are fully specified. The minimum cost sensitivity information provided in the optimal control formulation supports a mechanism, based on the notion of a critical machine, which plays an important role in the exploitation of the available flexibility. Finally, an important point to note is that our approach is particularly suited to further integration of the production system into a larger supply chain management framework, which is well supported by recent developments in hybrid systems theory.     

不确定性时滞大系统的分散鲁棒H∞控制

研究一类具有状态时滞的内联不确定性动态大系统的分散鲁棒H∞控制问题.系统 的不确定性参数满足范数有界条件.得到了由无记忆状态反馈分散控制器使每一个子系统和 整个大系统都可镇定且满足给定H∞性能的充分条件.所得结果与系统时滞的大小有关,并 以线性矩阵不等式的形式给出.     

基于LMI的大型互联线性系统的分散有限时间镇定

借助于有限时间稳定性的定义,针对大型互联线性系统,引入了分散有限时间镇定的概念.对一类大型互联线性系统进行分散状态反馈和分散动态输出反馈控制器设计,利用线性矩阵不等式(LMI)的方法提出一个充分条件,当反馈控制律作用于该系统时,闭环系统是有限时间稳定的.仿真算例说明了所得结论的可行性和有效性.     

Data-driven output-feedback fault-tolerant control for unknown dynamic systems with faults changing system dynamics

This paper studies the data-driven output-feedback fault-tolerant control (FTC) problem for unknown dynamic systems with faults changing system dynamics. In a framework of active FTC, two basic issues are addressed: the fault detection employing only the measured input–output information; the controller reconfiguration to achieve optimal output-feedback control in the presence of multiple faults. To detect faults and write the system state via the input–output data, an approach to data-driven design of a residual generator with a full-rank transformation matrix is presented. An output-feedback approximate dynamic programming method is developed to solve the optimal control problem under the condition that the unknown linear time-invariant discrete-time plant has multiple outputs. According to the above results and the proposed input–output data-based value function approximation structure of time-varying plants, a model-free output-feedback FTC scheme considering optimal performance is given. Finally, two numerical examples and a practical example of a DC motor control system are used to demonstrate the effectiveness of the proposed methods.     

Consensus of multi-agent linear dynamic systems via impulsive control protocols

In this article, we introduce impulsive control protocols for multi-agent linear dynamic systems. First, an impulsive control protocol is designed for network with fixed topology based on the local information of agents. Then sufficient conditions are given to guarantee the consensus of the multi-agent linear dynamic systems by the theory of impulsive systems. Furthermore, how to select the discrete instants and impulsive matrices is discussed. The case that the topologies of networks are switching is also considered. Numerical simulations show the effectiveness of our theoretical results.     

A variable structure gradient adaptive algorithm for a class of dynamical systems

A standard assumption in adaptive control is that the parameters being estimated are either constant or vary ‘slowly’ as a function of time. This paper investigates the adaptive control of a class of systems in which the parameters vary as a specified function of state. The dynamic structure of the systems may be either linear or nonlinear. For this class of systems, the state space is separated into distinct subsets. The parameters are then required to remain constant, or be slowly time varying, within the subsets. Given a controller for the system, an analysis of the output error dynamics and the parameter error dynamics leads to a parameter adaptation algorithm with a variable structure. The stability and convergence of both the parameter error and the output tracking error are investigated. An analysis of SISO linear systems with full state information is used to motivate and illustrate the treatment of SISO feedback linearizable systems.