控制模态转移型系统的稳定切换

离散事件决策子系统和数值反馈子系统合成的混合控制系统呈现出复杂的稳定动态 特性.研究了在达到模态切换周期的控制规则下,相应的系统连续状态轨迹的平稳性.给出了具 有较少约束的李雅谱诺夫型判据,不要求全局一致的李雅谱诺夫函数,不要求每个模态下的能 量函数单调递减.     

离散事件动态系统的状态补偿观测控制

在离散事件控制系统中,系统的信息结构由系统事件和系统状态构成。本文研究了具有混合信息结构的离散事件控制系统的分析与综合等问题。     

离散线性切换系统的一致有限时间稳定分析和反馈控制及其在网络控制系统中的应用

研究了一类离散线性切换系统的一致有限时间稳定性分析和反馈镇定．基于线性矩阵不等式技术,给出了在任意切换信号作用下,离散线性切换系统有限时间稳定和有限时间有界的充分条件,并给出了离散线性切换控制系统一致有限时间状态反馈控制器的设计方法．将上述分析结果应用于一类丢包有界的网络控制系统,得到了保证其有限时间稳定的反馈控制器．最后,通过两个数值仿真例子验证了所提方法的有效性．     

基于切换频度的马尔科夫网络控制系统均方指数镇定

针对一类马尔科夫网络控制系统(Networked control system, NCS),研究了其均方指数镇定问题. 首先将网络控制系统建模为离散时间切换系统,子系统间的切换过程由一个转移概率矩阵已知的马尔科夫链描述, 并给出了子系统间切换频度的范围;进而基于随机过程理论和切换系统稳定性理论, 利用状态反馈实现了网络控制系统均方指数镇定,状态反馈控制律可通过求解一组线性矩阵不等式获得. 最后通过数值仿真例子验证了本文方法的有效性.     

一类不确定脉冲型混杂系统的保代价控制

针对混合代价函数,研究了参数不确定脉冲型混杂系统的保代价控制问题,给出了混杂状态反馈保代价控制律的设计方法,由此得到的控制律既能使系统闭环鲁棒渐近稳定,又可使系统的闭环混合代价指标在对象参数摄动的范围内不超过确定的上界.本文提出的控制律不仅包含连续时间动态,也包含离散事件动态,而且其离散事件动态行为不需要与被控系统的离散事件动态行为一致,因此设计时不要求被控系统的每个连续时间子系统都具有可控性.仿真结果表明所提设计方法是可行有效的.     

变计时过程ö变迁网模型及其应用研究

基于过程运行的离散标识(逻辑变量)和剩余时间连续标识(时间变量)，提出一种新的混合标识过程／变迁网——变计时过程／变迁网模型．基于该模型，混杂动力学系统离散事件的实时监控、连续子过程的实时调度等问题可得到有效解决．     

并行离散事件模拟的同步机制研究

逻辑模拟在设计新系统的过程中起着重要作用，通过计算机进行模拟可以实时反馈输出结果，及早发现潜在的问题，进而缩短设计周期，降低研发成本。并行离散事件模拟通过分散计算量到并行机或者网络的多个节点来减少模拟时间，被视为解决模拟速度问题的有效途径。在影响模拟性能的因素中，各并行子系统之间的同步问题是直接影响并行性能的关键因素之一。探讨了并行离散事件模拟的同步机制，介绍了其基本原理、特点及存在的问题，并阐述了可能的改进方法。     

国民经济动员仿真演练混合仿真策略研究

国民经济动员仿真演练是一个复杂的基于HLA的分布式离散事件仿真过程,包括人在回路与无人在回路的混合仿真环节,且一次演练中参演单位数量非常多,需要解决高效的实时与超实时混合仿真控制问题.在分析仿真演练特点的基础上,将并行离散事件仿真(PDES)技术应用于联邦成员仿真控制过程,提出联邦成员离散事件仿真与成员内部PDES混合仿真策略.在分析时间推进过程的基础上,设计全局仿真时间控制机制.混合仿真策略可以支持实时与超实时混合仿真模式,并能充分地提高仿真并行能力,而全局时间控制则保证了系统时间的有效推进.     

基于双子代数的高通量筛选系统优化控制

为了提高控制效率,对一类新兴的离散事件系统,即高通量筛选系统,利用双子代数dioid同时从事件域和时间域进行建模.对于很多离散事件系统,期望的输入输出模型行为是进行优化控制时常用的指标.然而,根据实际控制要求,往往高通量筛选系统的优化指标还会考虑期望的状态轨迹或期望的输出轨迹.对此,研究dioid框架下具有不同优化指标的优化控制结构,并结合状态反馈和输出反馈进行讨论.最后通过实例说明了应用该控制结构的方法.仿真结果表明了所提出的优化控制方法的有效性.     

双采样频率多变量自适应控制

本文提出一个稳定的离散时间自适应控制算法。该算法适用于如下的多变量工业过程控制:在这类系统中有两组子系统需要用不同的频率采样,优点是:1)减轻实时计算负担;2)增强采样反馈的鲁棒性。     

Event‐switched control design with guaranteed performances

In this paper, a new event‐switched control method is presented for controlling discrete‐time linear systems subject to bounded disturbances. The main advantage of the proposed method is that the nominal performance of the controlled system with periodic control updates is kept in a framework that do not require to periodically update the control law. The feedback control loop can be opened as long a state‐dependent event condition is satisfied. This condition is obtained using set theory approaches. In particular, the concept of robustly positively invariant sets is used to calculate the nominal performance and the event condition. The simulation presented in this paper confirms the efficiency of the present approach. A reduction of the numerical complexity of the approach is also proposed. Copyright © 2016 John Wiley & Sons, Ltd.     

Composite State Feedback of the Finite Frequency H∞ Control for Discrete‐Time Singularly Perturbed Systems

This paper mainly is concerned with the finite frequency H_∞ control for the discrete‐time singularly perturbed systems. A state feedback controller is designed to stabilize the whole system and to satisfy the desired design specifications. The generalized Kalman–Yakubovich–Popov (GKYP) lemma is used to convert the related frequency domain inequalities in finite frequency ranges to feasible linear matrix inequalities. Based on the Lyapunov stability method, stable conditions are obtained for discrete‐time singularly perturbed systems. A bounded real lemma then is derived, which characterizes the H_∞ norm performance in specific frequency ranges. Furthermore, the approach for the design of a composite state feedback controller is put forward combined with the unique frequency characteristics of singularly perturbed systems. Detailed analysis of the performance achieved by the piecewise composite controller is provided when it is applied to the original system, and the effectiveness and merits of the proposed controller are illustrated with a numerical result.     

Stable controller design of MIMO systems in real Grassmann space

A new design method of a stable dynamic output feedback (DOF) controller in linear MIMO systems is presented on the frame of real Grassmann spaces. For the analysis, the DOF systems are decomposed into augmented static output feedback (SOF) systems using signal flow graph analysis of all DOF loops. For synthesis and design, the characteristic polynomial of the augmented SOF system for the system’s stable poles and the sub-characteristic polynomial of the sub-SOF system for the controller’s stable poles are parametrized within their Grassmann invariants in real Grassmann spaces, whose coordinates are defined in the real coefficient function spaces of their augmented SOF variables. The numerical parametrization and computation algorithm for a stable controller design is illustrated over a MIMO plant of a practical aircraft carrier model.     

Decentralized control: Status and outlook

This paper reviews state of the art in the area of decentralized networked control systems with an emphasis on event-triggered approach. The models or agents with the dynamics of linear continuous-time time-invariant state-space systems are considered. They serve for the framework for network phenomena within two basic structures. The I/O-oriented systems as well as the interaction-oriented systems with disjoint subsystems are distinguished. The focus is laid on the presentation of recent decentralized control design and co-design methods which offer effective tools to overcome specific difficulties caused mainly by network imperfections. Such side-effects include communication constraints, variable sampling, time-varying transmission delays, packet dropouts, and quantizations. Decentralized time-triggered methods are briefly discussed. The review is deals mainly with decentralized event-triggered methods. Particularly, the stabilizing controller–observer event-based controller design as well as the decentralized state controller co-design are presented within the I/O-oriented structures of large scale complex systems. The sampling instants depend in this case only on a local information offered by the local feedback loops. Minimum sampling time conditions are discussed. Special attention is focused on interaction-oriented system architecture. Model-based approach combined with event-based state feedback controller design is presented, where the event thresholds are fully decentralized. Finally, several selected open decentralized control problems are briefly offered as recent research challenges.     

Control of discrete‐time periodic linear systems with input saturation via multi‐step periodic invariant sets

This paper studies local control of discrete‐time periodic linear systems subject to input saturation by using the multi‐step periodic invariant set approach. A multi‐step periodic invariant set refers to a set from which all trajectories will enter a periodic invariant set after finite steps, remain there forever, and eventually converge to the origin as time approaches infinity. The problems of (robust) estimation of the domain of attraction, (robust) local stabilization (with bounded uncertainties), and disturbance rejection are considered. Compared with the conventional periodic invariant set approach, which has been used in the literature for local stability analysis and stabilization of discrete‐time periodic linear systems subject to input saturation, this new invariant set approach is capable of significantly reducing the conservatism by introducing additional auxiliary variables in the set invariance conditions. Moreover, the new approach allows to design (robust) stabilizing periodic controller, in the presence of norm bounded uncertainties, whose period is the same as the open‐loop system and is different from the existing periodic enhancement approach by which the period of the controller is multiple times of the period of the open‐loop system. Several numerical examples are worked out to show the effectiveness of the proposed approach. Copyright © 2013 John Wiley & Sons, Ltd.     

Constrained linear system with disturbance: Convergence under disturbance feedback

This paper proposes a disturbance-based control parametrization under the Model Predictive Control framework for constrained linear discrete time systems with bounded additive disturbances. The proposed approach has the same feasible domain as that obtained from parametrization over the family of time-varying state feedback policies. In addition, the closed-loop system is stable in the sense that the state converges to a bounded set that has a characterization determined by a feedback gain.     

SENSITIVITY APPROACH TO OPTIMAL CONTROL FOR AFFINE NONLINEAR DISCRETE‐TIME SYSTEMS

This paper deals with the optimal control problem for a class of affine nonlinear discrete‐time systems. By introducing a sensitivity parameter and expanding the system variables into a Maclaurin series around it, we transform the original optimal control problem for affine nonlinear discrete‐time systems into the optimal control problem for a sequence of linear discrete‐time systems. The optimal control law consists of an accurate linear term and a nonlinear compensating term, which is an infinite sequence of adjoint vectors. In the present approach, iteration is required only for the nonlinear compensation series. By intercepting a finite sum of the series, we obtain a suboptimal control law that reduces the complexity of the calculations. A numerical simulation shows that the algorithm can be easily implemented and has a fast convergence rate.     

Positive real control of two-dimensional systems: Roesser models and linear repetitive processes

This paper considers the problem of positive real control for two-dimensional (2-D) discrete systems described by the Roesser model and also discrete linear repetitive processes, which are another distinct sub-class of 2-D linear systems of both systems theoretic and applications interest. The purpose of this paper is to design a dynamic output feedback controller such that the resulting closed-loop system is asymptotically stable and the closed-loop system transfer function from the disturbance to the controlled output is extended strictly positive real. We first establish a version of positive realness for 2-D discrete systems described by the Roesser state space model, then a sufficient condition for the existence of the desired output feedback controllers is obtained in terms of four LMIs. When these LMIs are feasible, an explicit parameterization of the desired output feedback controllers is given. We then apply a similar approach to discrete linear repetitive processes represented in their equivalent 1-D state-space form. Finally, we provide numerical examples to demonstrate the applicability of the approach.     

A NEW ALGORITHM FOR DISCRETE‐TIME SLIDING MODE CONTROL USING INFREQUENT OUTPUT OBSERVATIONS

This paper presents a new approach for sliding‐mode control of discrete‐time systems using the reaching law approach together with periodic output feedback technique. This method does not need the system states for feedback as it makes use of only the output samples for designing the controller. Thus, this methodology is more practical and easy to implement. A numerical example is presented to illustrate the design technique.