事件反馈与状态反馈的混合模监控

在监控理论中 ,处理状态膨胀的标准方法之一是基于语言或谓词的模监控 .但文献中没有涉及同时基于语言与谓词的混合模监控 .本文研究混合模监控综合及其性质 .通过提出状态反馈与某一事件反馈的等价关系 ,给出了两者相连接的定义 ,进而得到了混合模监控器等价于子监控器与子控制器的连接 .并讨论了混合模监控器具有非阻塞性与无死锁性所满足的条件 ,即基于语言的闭环系统行为的封闭性与谓词的Σu-不变性 ,而其是无死锁的充要条件是子监控器与子控制器必须均是无死锁的并满足d-不变关系     

离散事件动态系统的D－B动机模型

首先引入Ｄ－子集和Ｄ－语言的概念，在此基础上给出了一类离散事件动态系统的一般形式化表述──Ｄ－自动机模型，并讨论了受控系统的动态行为．最后研究了系统的状态可达性问题．     

Takagai-Sugeno模糊模型的并行分布补偿:新的稳定条件和动态反馈设计(英文)

讨论可以用 Ｔａｋａｇａｉ－Ｓｕｇｅｎｏ模糊模型描述的系统的补偿器设计．这种被称之为并行分布补偿（ＰＤＣ）的控制器是基于参数并且影像了 Ｔａｋａｇａｉ－Ｓｕｇｅｎｏ模型的结构．通过引进动态并行分布控制（ＤＰＤＣ）的概念,扩展了关于此类控制器状态反馈的已有结果．提出三个新的结果．第一个结果给出了以往结果的宽松条件．这种条件是存在二次型稳定状态反馈这类控制器的充分条件．第二个结果给出了类似的二次型稳定动态反馈控制器存在的充分条件．第三个结果适用于 Ｔａｋａｇａｉ－Ｓｕｇｅｎｏ模糊模型的基于性能的控制器设计．     

基于Riccati-ItXô方程设计线性时滞系统鲁棒控制器的方法*

利用Ｒｉｃｃａｔｉ－Ｉｔｏ型矩阵代数方程研究线性时不变系统的状态反馈镇定问题，对时滞系统给出了一种状态反馈镇定方法，这种镇定方法适应于许多时滞系统，其设计方案具有滞后无关性及对于许多系统滞后项系数任意性的完全适应性，本文第二部分研究对不变线性不确定系统的鲁棒镇定，利用Ｒｉｃｃａｔｉ－Ｉｔｏ型矩阵代数方程给出了这类系统鲁棒镇定控制器的设计方法。     

实时离散事件动态系统的状态行为与最速控制

基于Ｄ－自动机模型，通过广义状态谓词空间与半范数的概念，深入研究了实时ＤＥＤＳ的状态行为及最速控制问题，最后讨论了此类控制问题解的存在性。     

一个分布式文件系统及多缓存数据－致性策略

本文介绍了我们设计实现的一个分布式操作系统ＨＩＴ－ＤＵＮＩＸ中分布式文件系统的实现要点，给出了维护分布式文件多缓存数据一致性的ＭＢＣ策略并讨论了ＭＢＣ策略中防止死锁的技术。     

一个分布式文件系统及多缓存数据一致性策略

本文介绍了我们设计实现的一个分布式操作系统ＨＩＴ－ＤＵＮＩＸ中分布式文件系统的实现要点，给出了维护分布式文件多缓存数据一致性的ＭＢＣ策略并讨论了ＭＢＣ策略中防止死锁的技术。     

用自动机建立操作系统模型

这篇文章用自动机理论的一些概念,建立在一个多道程序的操作系统中进程间如何交互作用的模型。为了得到所需的模型采取的方法是,引进状态集合的结构和自动机转换规则。操作系统的一些概念,如限定性和死锁等,用自动机理论的术语加以形式化并进行细致的分析。为读者方便文中提供了许多例子。本文预备知识涉及有限自动机概念。(原提要)     

基于神经网络算法的实时DES监督控制

本文在包含状态转移时间离散事件系统（ＤＥＳ）的自动机模型基础上，引入神经网络优化算法用以确定表征闭环系统最大允许逻辑行为的语言Ｋ的一个某项指标最优的子集Ｋｅｐｔ，并探讨了这种情况下用Ｒ－Ｗ理论设计监控ＤＥＳ的有关问题．     

基于Petri网模型的FMS死锁结构

死锁是柔性制造系统中容易发生的异常现象，如不加以消除，将会导致整个系统的瘫痪。文中通过Petri网模型对FMS的结构分析，揭示出导致FMS死锁的结构元素和活性特征，在此基础上，提出了FMS的无死锁Petri网控制器算法，并举例说明这种控制器算法在FMS中的应用。     

On deadlock-free modular supervisory control of discrete-eventsystems

In this paper the problem of synthesizing deadlock-free modular supervisors for discrete-event systems is discussed. By introducing the d-invariant relation between a pair of supervisors, it is shown that when the control objective is described in terms of intersection of two languages, a necessary and sufficient condition for the modular supervisor to be deadlock-free is that this pair of subsupervisors satisfies a d-invariant relation. A procedure for synthesizing the deadlock-free modular supervisor is presented. Some issues concerning deadlock-free modular supervisory control are also discussed     

MD-SIR: a methodology for developing sensor—guided industry robots

In this paper, we present a generic methodology for the synthesis of industrial robot applications with sensory feedback at the end-effector level. The presented methodology assumes an open controller architecture and leads to the creation of a library of modular and reusable entities, which can be used to build new systems based on the proposed architectural framework. The library facilitates the integration of new algorithms and it evolves as new modular applications are built. The library components belong to the control objects layer of the open controller architecture and implement functionality for sensor interfacing, sensor modeling, pattern recognition, state estimation and state regulation. The validity of the approach is verified by composing real industrial applications. The experimental results indicate the high quality of the developed systems.     

Modular nonblocking state feedback control of discrete event systems and its application to dynamic oligopolistic markets

This article addresses a modular state feedback supervisory control problem where two local controllers should achieve a common control objective against another local controller. Each local controller has its own control objective described as a predicate. This article also addresses a nonblocking modular control problem in which a discrete event system controlled by three local controllers tends to reach the common marked states of two local controllers that are, however, prohibited by the third local controller. For a case study, we apply the proposed theory to an oligopolistic market composed of two firms and one government. Two oligopolistic firms have a common objective to maximise their total profit through collusion. However, the government prevents them from engaging in collusion. We show that the modular supervisory control theory presented in this article can be used to solve the problem of ‘how can the firms maximise their total profit against the intervention of government’?     

基于神经网络的一类非线性系统自适应输出跟踪

针对一类未知非线性系统,提出了一种输出反馈控制方法.首先,在假设系统状态已 知情况下设计状态反馈控制器,实现跟踪性能;然后,在系统状态不完全可测的情况下,通过 设计高增益观测器对系统的状态进行估计,实现输出反馈控制器设计,证明了所设计的输出 反馈控制器可以获得状态反馈控制器的性能.     

Robust control of robots via linear estimated state feedback

In this note we propose a robust tracking controller for robots that requires only position measurements. The controller consists of two parts: a linear observer part that generates an estimated error state from the error on the joint position and a linear feedback part that utilizes this estimated state. It is shown that this computationally efficient controller yields semi-global uniform ultimate boundedness of the tracking error. An interesting feature of the controller is that it straightforwardly extends results on robust control of robots by linear state feedback to linear estimated-state feedback     

基于观测器的一类连续非线性系统的采样控制

首先使用反演方法分别设计了系统的连续时间状态反馈控制器、连续时间观测器和基于连续时间观测器的连续时间控制器. 接下来, 利用零阶保持法对连续时间状态反馈控制器进行离散化, 获得了状态反馈采样控制器; 利用零阶保持法对基于连续时间观测器 的连续时间控制器离散化, 获得了基于连续时间观测器的采样控制器; 利用Euler法对连续时间观测器离散化, 同时利用零阶保持法对控制器离散化, 从而获得了采样观测器和基于采样观测器的采样控制器. 本文论证了上述状态反馈采样控制器和基于连续时间观测器的采样控制器可以保证闭环系统渐近稳定, 而基于采样观测器的采样控制器可以保证被控对象的状态是有界的, 其最终边界依赖于设计参数与采样周期. 最后, 通过选择适当的采样周期, 完成了闭环采样控制系统的设计. 一个船舶航向控制的例子表明应用本文 所提方法设计出的三种采样控制器具有良好的控制效果.     

Static-state feedback control of discrete-event systems underpartial observation

Studies static-state feedback control of discrete-event systems under partial observation. The authors present a necessary and sufficient condition for the existence of a static-state feedback controller. A static controller is a special case of a dynamic controller studied by Kumar et al. The authors' condition, however, has computational advantage in contrast to those obtained by Kumar et al. The authors also present a necessary and sufficient condition under which the modular feedback synthesis is possible     

Backstepping design for a class of coupled parabolic PDEs with spatially varying coefficient

In this paper, we concentrate on the state feedback stabilization of a class of coupled parabolic partial differential equations with space dependent diffusion coefficients. To stabilize the system, we design a state feedback controller using the backstepping technique. Namely, we convert the original system into a stable desired system called the target system to obtain a backstepping feedback controller. We prove that the feedback controller causes the main system to be exponential stable. Also, the numerical simulations show that validity and efficiency of theoretical results.     

State and Mode Feedback Control for Discrete-time Markovian Jump Linear Systems With Controllable MTPM

In this note, the state and mode feedback control problems for a class of discrete-time Markovian jump linear systems (MJLSs) with controllable mode transition probability matrix (MTPM) are investigated. In most achievements, controller design of MJLSs pays more attention to state/output feedback control for stability, while the system cost in practice is out of consideration. In this paper, we propose a control mechanism consisting of two parts: finite-path-dependent state feedback controller design with which uniform stability of MJLSs can be ensured, and mode feedback control which aims to decrease system cost. Differing from the traditional state/output feedback controller design, the main novelty is that the proposed control mechanism not only guarantees system stability, but also decreases system cost effectively by adjusting the occurrence probability of system modes. The effectiveness of the proposed mechanism is illustrated via numerical examples.      

State and mode feedback control strategy for discrete‐time Markovian jump linear systems with time‐varying controllable mode transition probability matrix

In this article, the state and mode feedback control strategy is investigated for the discrete‐time Markovian jump linear system (MJLS) with time‐varying controllable mode transition probability matrix (MTPM). This strategy, consisting of a state feedback controller and a mode feedback controller, is proposed to ensure MJLS's stability and meanwhile improve system performance. First, a mode‐dependent state feedback controller is designed to stabilize the MJLS based on the time‐invariant part of the MTPM such that it can still keep valid even if the MTPM is adjusted by the mode feedback control. Second, a generalized quadratic stabilization cost is put forward for evaluating MJLS's performance, which contains system state, state feedback controller, and mode feedback controller. To reduce the stabilization cost, a mode feedback controller is introduced to adjust each mode's occurrence probability by changing the time‐varying controllable part of MTPM. The calculation of such mode feedback controller is given based on a value‐iteration algorithm with its convergence proof. Compared with traditional state feedback control strategy, this state and mode feedback control strategy offers a new perspective for the control problem of general nonhomogeneous MJLSs. Numerical examples are provided to illustrate the validity of the proposed strategy.