分布式模糊离散事件系统的故障预测

本文研究分布式模糊离散事件系统的故障预测问题.先根据系统的模糊特性,提出一种分布式模糊离散事件系统的协同可预测性的形式化方法,使分布式模糊离散事件系统的协同可预测度不小于各分站点的局部可预测度.通过构造协同预测验证器,提出一种基于协同预测验证器的协同预测算法,并得到一个关于分布式模糊离散事件系统协同可预测性的充分必要条件.     

Observability, controllability and decentralized control of interconnected power systems

An examination is made of the structural properties of observability and controllability for a class of interconnected power system models. A state-space representation which is both completely observable and controllable is developed for a two-area interconnected power system (TAIPS). These properties of the new representation may be exploited in order to generate, for each area, controls which are based upon area output-feedback only. With the use of reduced-order observers, controls which are linear functionals of the global state-vector may be generated within each area. The proposed scheme therefore provides for the complete decentralization of a global state-feedback control policy (e.g. pole assignment; optimal control), in the sense that the area control feedback loops are completely decoupled.     

On the synthesis of safe control policies in decentralized control of discrete-event systems

State estimation and safe controller synthesis for a general form of decentralized control architecture for discrete-event systems is investigated. For this architecture, controllable events are assigned to be either "conjunctive" or "disjunctive." A new state estimator that accounts for past local control actions when calculating the set of estimated system states is presented. The new state estimator is applied to a previous general decentralized control law. The new control method generates a controlled language at least as large as that generated by the original method if a safety condition is satisfied. An algorithm for generating locally maximal control policies for a given state estimate is also discussed. The algorithm allows an amount of "steering" of the controlled system through an event priority mechanism.     

Centralized and decentralized asynchronous optimization ofstochastic discrete-event systems

We propose and analyze centralized and decentralized asynchronous control structures for the parametric optimization of stochastic discrete-event systems (DES) consisting of K distributed components. We use a stochastic approximation type of optimization scheme driven by gradient estimates of a global performance measure with respect to local control parameters. The estimates are obtained in distributed and asynchronous fashion at the K components based on local state information only. We identify two verifiable conditions for the estimators and show that if they, and some additional technical conditions, are satisfied, our centralized optimization schemes, as well as the fully decentralized asynchronous one we propose, all converge to a global optimum in a weak sense. All schemes have the additional property of using the entire state history, not just the part included in the interval since the last control update; thus, no system data are wasted. We include an application of our approach to a well-known stochastic scheduling problem and show explicit numerical results using some recently developed gradient estimators     

Hierarchical control of discrete-event systems

An abstract hierarchical control theory is developed for discrete-event systems, based on the concepts of control structures and observers. Control structure is an abstract generalization of the family of controllable sublanguages in the Ramadge-Wonham framework. We establish a general version of Zhong's hierarchical consistency by first achieving control consistency — preservation of control structures through the aggregation mapping in a two-level hierarchy. For a refinement of hierarchical consistency with preservation of nonblocking, the concept of observer is introduced via congruences on nondeterministic transition structures.     

高阶耦合机器人的自适应模糊滑模分散控制

针对一类存在模型不确定性和未知非线性扰动的机器人系统,考虑其不确定项和未知扰动项的上界是关于系统状态的普通高阶多项式,结合模糊系统的逼近能力,提出了一种基于滑模控制原理的自适应模糊分散控制方法.该方法不仅能够使得关节之间相互耦合的机器人各关节的控制器仅由本关节的信息就能完全确定,而且消除了现存文献在设计机器人分散控制器...     

基于分散模糊推理的多输入多输出系统预测控制

对于动态过程具有明显迟延和惯性的MIMO系统,常规模糊控制难以建立模糊规则,控制效果不理想.针对MIMO控制对象,提出一种基于分散模糊推理的预测控制(predictive control based on decentralized fuzzy inference, DFIPC)方法.构造一组与被控输出相对应的分散模糊推理模块,每个推理模块利用一组分散的模糊推理单元,分别根据各个输出的期望值与预测值之间的偏差进行分散推理.在时间层面,根据动态响应程度对推理结果进行加权综合,获得等效控制输入;进一步,通过对等效控制输入加权综合产生系统实际控制输入增量,从而有效克服模糊推理系统处理多维输入信息时模糊规则难以建立的困难.最后,通过实验验证所提出控制方法对于迟延和惯性明显的MIMO控制对象的有效性和适应性.     

Supervisory control of concurrent discrete-event systems

When a discrele-event system P consists of several subsystems P₁,...,P_n which operate concurrently, a natural approach to the supervisory control problem is to synthesize a ‘local’ controller S_i , for each subsystem P_i , and operate the individually controlled subsystems S_i/P_i concurrently. Such an approach is called concurrent supervisory control and is closely related to decentralized supervisory control as studied by Cieslak et al. (1988) and Lin and Wonham (1988). In the present paper simple and easily computable conditions are developed which guarantee that concurrent supervisory control can achieve the optimal behaviour achievable by a global supervisor. To achieve this, two specific concurrent control strategies are introduced.     

Hierarchical control of timed discrete-event systems

An abstract hierarchical control theory is developed for a class of timed discrete-event systems (TDES) within the discrete-event control architectural framework proposed earlier by the authors. For this development, a control theory for TDES is introduced in the spirit of a prior theory of Brandin. A notion of time control structures is introduced, and on its basis a general property of hierarchical consistency is achieved by establishing control consistency — namely preservation of time control structures through the aggregation mapping in a two-level hierarchy.     

Modular supervisory control of discrete-event systems

A modular approach to the supervisory control of a class of discrete-event systems is formulated, and illustrated with an example. Discrete-event systems are modeled by automata together with a mechanism for enabling and disabling a subset of state transitions. The basic problem of interest is to ensure by appropriate supervision that the closed loop behavior of the system lies within a given legal behavior. Assuming this behavior can be decomposed into an intersection of component restrictions, we determine conditions under which it is possible to synthesize the appropriate control in a modular fashion. The work of this author was supported by NSERC (Canada) under Grant No. A-7399. The work of this author was supported by the National Science Foundation through Grant No. ECS-8504584.     

Supervisory control of timed discrete-event systems

The Ramadge-Wonham framework for control of discrete event systems is augmented with timing features by use of Ostroff's semantics for timed transition models. It is shown that the RW concept of controllability and the existence of maximally permissive supervisory controls can be suitably generalized. The enhanced setting admits subsystem composition and the concept of forcible event as an event that preempts the tick of a global clock. An example of a simple manufacturing cell illustrates how the new framework can be used to solve synthesis problems which may include logic-based, temporal and quantitative optimality specifications     

Similarity-based supervisory control of discrete-event systems

Due to the appearance of uncontrollable events in discrete-event systems, one may wish to replace the behavior leading to the uncontrollability of pre-specified language by some quite similar one. To capture this similarity, we introduce metric to traditional supervisory control theory and generalize the concept of original controllability to /spl lambda/-controllability, where /spl lambda/ indicates the similarity degree of two languages. A necessary and sufficient condition for a language to be /spl lambda/-controllable is provided. We then examine some properties of /spl lambda/-controllable languages and present an approach to optimizing a realization.     

The relationship of controllability between classical and fuzzy discrete-event systems

We have known that the controllability of classical discrete-event systems has already been extended into fuzzy discrete-event systems. In this paper, firstly, we recall some related definitions and results of the controllability for classical and fuzzy discrete-event systems, respectively. Secondly, we are concerned with the relationship of the controllability between classical and fuzzy discrete-event systems. In particular, we show that there is an equivalence of the controllability between the two systems to some extent, some special proofs are also presented. Finally, we use this equivalence to extend some general controllability properties of classical discrete-event systems into fuzzy ones.     

Robust stabilization of nonlinear multiple time-delay large-scale systems via decentralized fuzzy control

To overcome the effect of modeling errors between nonlinear multiple time-delay subsystems and Takagi-Sugeno (T-S) fuzzy models with multiple time delays, a robustness design of fuzzy control is proposed in This work. In terms of Lyapunov's direct method, a delay-dependent stability criterion is hence derived to guarantee the asymptotic stability of nonlinear multiple time-delay large-scale systems. Based on this criterion and the decentralized control scheme, a set of model-based fuzzy controllers is then synthesized via the technique of parallel distributed compensation (PDC) to stabilize the nonlinear multiple time-delay large-scale system. Finally, a numerical example with simulations is given to demonstrate the concepts discussed throughout This work.     

Mind the gap: Expanding communication options in decentralized discrete-event control

Frameworks that incorporate communication into decentralized supervisory control theory address the following problem: find locations in the evolution of the plant behavior where supervisors send information so that a supervisor that was unable to make the correct control decision prior to receiving external information, is now capable of making the correct control decision. Existing solutions to this problem identify an earliest and a latest placement where the communication protocol leads to the synthesis of a correct control solution. In addition to the first and last communication opportunities, there may be a selection of intermediate possibilities where communication would also produce the correct control solution. We present a computable procedure to identify a broader range of suitable communication locations.     

Adaptive fuzzy decentralized control for a class of large-scale nonlinear systems.

In this paper, direct and indirect adaptive output-feedback fuzzy decentralized controllers for a class of uncertain large-scale nonlinear systems are developed. The proposed controllers do not need the availability of the state variables. By designing the state observer, the adaptive fuzzy systems, which are used to model the unknown functions, can be constructed using the state estimations, and a new hybrid adaptive fuzzy control methodology is proposed by combining the adaptive fuzzy systems with H infinity control and the sliding mode control techniques. Based on Lyapunov stability theorem, the stability of the closed-loop systems can be verified. Moreover, the proposed overall control schemes guarantee that all the signals involved are bounded and achieve the H infinity-tracking performance. To demonstrate the effectiveness of the proposed methods, simulation results are illustrated in this paper.     

Adaptive fuzzy decentralized control for nonlinear large-scale systems based on high-gain observer

An adaptive fuzzy decentralized backstepping output-feedback control approach is proposed for a class of nonlinear large-scale systems with completely unknown functions,the interconnections mismatched in control inputs,and without the measurements of the states.Fuzzy logic systems are employed to approximate the unknown nonlinear functions,and an adaptive high-gain observer is developed to estimate the unmeasured states.Using the designed high-gain observer,and combining the fuzzy adaptive control theory with backstepping approach,an adaptive fuzzy decentralized backstepping output-feedback control scheme is developed.It is proved that the proposed control approach can guarantee that all the signals of the closed-loop system are semi-globally uniformly ultimately bounded(SUUB),and that the observer errors and the tracking errors converge to a small neighborhood of the origin by appropriate choice of the design parameters.Finally,a simulation example is provided to show the eectiveness of the proposed approach.