离散事件系统结构化状态反馈控制逻辑

离散事件系统(Discrete Event System,DES)是从制造系统、通讯系统、资源管理系统和城市/空中交通系统等人工系统中抽象出来的.这种系统可认为是离散的(在时间上和状态空间内)、异步的(即是由事件驱动而不是由时钟驱动),并且一般是非确定性的,所以处理这类系统的方法与连续时间系统迥然不同.在已有的处理 DES 的方法中,Wonham 和他的学生所提出的一种概念模型方法已引起了广泛的注意.在这方法中,他们成功地将计算机科学的一些概念和方法引入到控制中,新领域的出现和新方法论的发展使控制科学产生了新的活力.     

An inclusion principle for hereditary systems

Given two hereditary dynamic systems having different dimensions, the conditions are provided under which a part of the motion of the larger system is reproduced by the smaller system, that is, the larger system “includes” the smaller one. The conditions for inclusion are useful in applying the concept of vector Liapunov functions to stability analysis of systems composed of overlapping subsystems. By expanding the systems into a larger space the overlapping subsystems appear as disjoint and standard methods can be used to conclude stability of the expanded system. Under the inclusion conditions, stability of the expansion implies stability of the original system. An example is provided to show stability where the standard disjoint decompositions fail.     

Quadratic stabilization of a class of switched nonlinear systems via single Lyapunov function

This paper is concerned with the problem of globally quadratic stabilization for a class of switched cascade systems. The system under consideration is composed of two subsystems: a linear switched part and a nonlinear part, which are also switched systems. The feedback control law and the switching law are designed respectively when the first part is stabilized under some switching law and when both parts can be stabilized under some switching laws. We construct the single Lyapunov functions and design the switching laws based on the structure characteristics of the switched system. Also, the designed switching laws are of hysteresis switching form in order to avoid sliding models.     

Asymptotically suboptimal control of weakly interconnected dynamical systems

Optimal control problems for a group of systems with weak dynamical interconnections between its constituent subsystems are considered. A method for decentralized control is proposed which distributes the control actions between several controllers calculating in real time control inputs only for theirs subsystems based on the solution of the local optimal control problem. The local problem is solved by asymptotic methods that employ the representation of the weak interconnection by a small parameter. Combination of decentralized control and asymptotic methods allows to significantly reduce the dimension of the problems that have to be solved in the course of the control process.     

Decentralized feedback control of uncertain cellular neural networks subject to time-varying delays and dead-zone input

This paper investigates the stabilization problem for uncertain cellular neural networks (CNNs) subject to time-varying delays and dead-zone input. On the basis of Lyapunov stability theory, a memoryless decentralized feedback control law is derived for guaranteeing global exponential stability of the system. The main results illustrate that the derived control law does not impose restriction on the derivative of the time-varying delays and can be applied to stabilizing the uncertain CNNs with time-varying delays and dead-zone input. An illustrative example is given to justify the validity and feasibility of the proposed control scheme.     

Symbolic models for infinite networks of control systems: A compositional approach

This paper presents a compositional framework for the construction of symbolic models for a network composed of a countably infinite number of finite-dimensional discrete-time control subsystems. We refer to such a network as infinite network. The proposed approach is based on the notion of alternating simulation functions. This notion relates a concrete network to its symbolic model with guaranteed mismatch bounds between their output behaviors. We propose a compositional approach to construct a symbolic model for an infinite network, together with an alternating simulation function, by composing symbolic models and alternating simulation functions constructed for subsystems. Assuming that each subsystem is incrementally input-to-state stable and under some small-gain type conditions, we present an algorithm for orderly constructing local symbolic models with properly designed quantization parameters. In this way, the proposed compositional approach can provide us a guideline for constructing an overall symbolic model with any desired approximation accuracy. A compositional controller synthesis scheme is also provided to enforce safety properties on the infinite network in a decentralized fashion. The effectiveness of our result is illustrated through a road traffic network consisting of infinitely many road cells.     

Tracking control for switched time-varying delays systems with stabilizable and unstabilizable subsystems

We investigate the tracking control problem for switched linear time-varying delays systems with stabilizable and unstabilizable subsystems. Sufficient conditions for the solvability of the tracking control problem are developed. The tracking control problem of a switched time-varying delays system with stabilizable and unstabilizable subsystems is solvable if the stabilizable and unstabilizable subsystems satisfy certain conditions and admissible switching law among them. Average dwell time approach and piecewise Lyapunov functional methods are utilized to the stability analysis and controller design. By introducing the integral controllers and free weighting matrix scheme, some restricted assumptions imposing on the switched systems are avoided. A simulation example shows the effectiveness of the proposed method.     

A minimax problem for semilinear nonlocal competitive systems

A two-sided game for the control of a stationary semilinear competitive system with autonomous sources is considered, where the controls are the kernels of the nonlocal interaction terms. The saddle point (the optimal solution of the game) is characterized as the unique solution of the associated optimality system, which is solved by an iterative scheme.This research has been partially sponsored by DARPA under Contract No. 1868-A037-A1 with Martin Marietta Energy Systems, Inc., under Contract No. DE-AC05-84OR21400 with U.S. Department of Energy. S. Lenhart's work was also partially supported by an NSF grant.     

Decentralized event-based control: Stability analysis and experimental evaluation

Event-based control aims at reducing the amount of information which is communicated between sensors, actuators and controllers in a networked control system. The feedback link is only closed at times at which an event indicates the need for an information update to retain a desired performance. Between consecutive event times the control loop acts as a continuous system, whereas at the event times it performs a state jump. Thus, the event-based control loop belongs to the class of hybrid dynamical systems. In this paper a new method for decentralized event-based control is proposed. Two methods are presented for the stability analysis of the decentralized event-based state feedback control of physically interconnected systems. The comparison principle leads to a stability criterion that provides an upper bound for the coupling strength for which the stability of the uncoupled event-based control loops implies ultimate boundedness of the interconnected event-based system. It is shown that ultimate boundedness of the event-based state-feedback loop is implied by the asymptotic stability of the continuous state-feedback system. Furthermore, it is explained how the number of events can be reduced by estimating the interconnection signals between the subsystems and two different estimation methods are proposed. The derived methods are demonstrated for a thermofluid process by simulation and experiments.     

Adaptive tracking control for a class of switched uncertain nonlinear systems under a new state-dependent switching law

This paper deals with the problem of adaptive fuzzy tracking control for a class of switched uncertain nonlinear systems. Fuzzy logic systems are utilized to approximate the unknown nonlinear functions, and the adaptive backstepping and dynamic surface control techniques are adopted. First, a new state-dependent switching method is proposed. By introducing convex combination technique and designing a state-dependent switching law, only the solvability of the adaptive tracking control problem for a convex combination of the subsystems is necessary. Second, a new common Lyapunov function with switched adaptive parameters is constructed to reduce the conservatism. Third, to avoid Zeno behavior, a modified state-dependent switching law with dwell time is proposed. It is shown that under the proposed control and switching laws, all the signals of the closed-loop system are bounded and all the state tracking errors can converge to a priori accuracy, even if some subsystems are uncontrollable. Finally, the effectiveness of the proposed method is illustrated through two simulation examples.     

Secure communications based on the synchronization of the hyperchaotic Chen and the unified chaotic systems

This paper deals with the adaptive synchronization of two identical hyperchaotic master and slave systems. The master system and the slave system each consists of two subsystems: a hyperchaotic Chen subsystem and a unified chaotic subsystem. The asymptotic convergence of the errors between the states of the master system and the states of the slave system is proven using Lyapunov theory. Simulation results are presented to illustrate the ability of the control law to synchronize the master and slave systems. Moreover, the proposed control scheme is applied to encrypt and decrypt discrete signals such as digital images where computer simulation results are provided to show that the proposed control law works well.     

Semi-global finite-time output feedback stabilization for a class of large-scale uncertain nonlinear systems

This paper addresses the problem of semi-global finite-time decentralized output feedback control for large-scale systems with both higher-order and lower-order terms. A new design scheme is developed by coupling the finite-time output feedback stabilization method with the homogeneous domination approach. Specifically, we first design a homogeneous observer and an output feedback control law for each nominal subsystem without the nonlinearities. Then, based on the homogeneous domination approach, we relax the linear growth condition to a polynomial one and construct decentralized controllers to render the nonlinear system semi-globally finite-time stable.     

Various Feedforward Schemes and a Passivity Based Backstepping Feedback Control of an Elastic Robot

Lightweight constructions in industry plants lead to elastic deflections causing vibrations and a loss in tracking precision. In order to keep the tracking error for these elastic multibody systems low, the proposed control strategies are combinations of feedforward and feedback schemes. In this work various implemented strategies for computing a feedforward control are proposed and compared, which can be calculated with some simplifications from the mathematical model of the elastic multibody system. Some of these are considering the elastic deflections. The stabilization of the error dynamics is achieved by a simple PD-joint control or passivity based backstepping. In this algorithm the system is split into subsystems and for these subsystems simple control concepts can be applied. The feedback control law of the total system is obtained by means of backstepping theory, considering the internal energy flows in the system. Experimental results are presented to verify the control strategies. (© 2010 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Hybrid decentralized maximum entropy control for large-scale dynamical systems

In the analysis of complex, large-scale dynamical systems it is often essential to decompose the overall dynamical system into a collection of interacting subsystems. Because of implementation constraints, cost, and reliability considerations, a decentralized controller architecture is often required for controlling large-scale interconnected dynamical systems. In this paper, a novel class of fixed-order, energy-based hybrid decentralized controllers is proposed as a means for achieving enhanced energy dissipation in large-scale lossless and dissipative dynamical systems. These dynamic decentralized controllers combine a logical switching architecture with continuous dynamics to guarantee that the system plant energy is strictly decreasing across switchings. The general framework leads to hybrid closed-loop systems described by impulsive differential equations. In addition, we construct hybrid dynamic controllers that guarantee that each subsystem–subcontroller pair of the hybrid closed-loop system is consistent with basic thermodynamic principles. Special cases of energy-based hybrid controllers involving state-dependent switching are described, and an illustrative combustion control example is given to demonstrate the efficacy of the proposed approach.     

A hierarchical structure of observer-based adaptive fuzzy-neural controller for MIMO systems

An observer-based adaptive controller developed from a hierarchical fuzzy-neural network (HFNN) is employed to solve the controller time-delay problem for a class of multi-input multi-output (MIMO) non-affine nonlinear systems under the constraint that only system outputs are available for measurement. By using the implicit function theorem and Taylor series expansion, the observer-based control law and the weight update law of the HFNN adaptive controller are derived. According to the design of the HFNN hierarchical fuzzy-neural network, the observer-based adaptive controller can alleviate the online computation burden. Moreover, the common adaptive controller is utilized to control all the MIMO subsystems. Hence, the number of adjusted parameters of the HFNN can be further reduced. In this paper, we prove that the proposed observer-based adaptive controller can guarantee that all signals involved are bounded and that the outputs of the closed-loop system track asymptotically the desired output trajectories.     

Chaos control in AFM system using sliding mode control by backstepping design

This paper presents a robust algorithm to control the chaotic atomic force microscope system (AFMs) by backstepping design procedure. The proposed feedback controller is composed by a sliding mode control (SMC) and a backstepping feedback, so its implementation is quite simple and can be made on the basis of the measured signal. The developed control scheme allows chaos suppression despite uncertainties in the model as well as system external disturbances. The concept of extended system is used such that a continuous sliding mode control effort is generated using backstepping scheme. It is guaranteed that under the proposed control law, uncertain AFMs can asymptotically track target orbits. The converging speed of error states can be arbitrary turned by assigning the corresponding dynamics of the sliding surfaces. Numerical simulations demonstrate its advantages by stabilizing the unstable periodic orbits of the AFMs and this method can also be easily extended to elimination chaotic motion in any types of chaotic AFMs.     

Impulsive controller for wireless networked control system: Switched system approach

The problem of stabilization for wireless networked control system (NCS) with packet dropout and time delay is studied in this article. The impulsive control law for the NCS is defined with time delay and impulse. Using a switching model, the network‐induced imperfections can be treated as three switching subsystems. Therein, in the case of packet dropout, the control law use the previous state via the first‐order hold. The impulsive control law is designed using the switched system approach and the average dwell time method. The obtained sufficient conditions which can guarantee the exponential stability of switched system are in the form of linear matrix inequalities. Finally, a numerical example is used to demonstrate the merits and applicabilities of the proposed method. © 2015 Wiley Periodicals, Inc. Complexity 21: 291–299, 2016     

离散时间大种群随机多智能体系统的线性二次分散动态博弈

研究具有耦合二次型随机性能指标的离散时间大种群随机多智能体系统的分散博弈问题.系统所受的噪声干扰为条件二阶矩有界的鞅差序列,比以往研究所考虑的高斯白噪声情形更具有广泛性.采用状态聚集方法构造了对种群状态平均的估计,基于Nash必然等价原理设计了分散控制律,并利用概率极限理论分析了闭环系统的稳定性和最优性.主要结果包括(1)证明了对种群状态的平均的估计在某种范数意义下的强一致性,即种群状态的平均与其估计值之间的误差在该范数意义下将随系统个体数N的增加几乎必然收敛于0;(2)证明了闭环系统的几乎必然一致稳定性,即系统的稳定性与种群个体数N无关;(3)证明了所设计的分散控制律是几乎必然渐近Nash均衡策略.     

非完整性多体编队运动的一种无源化控制方法

讨论了非完整性多体编队运动问题．首先利用动态反馈将单个体的动力学模型线性化为2个三阶输入输出积分链的形式;然后提出一种带有单个体间阻尼注入的非连续分布式控制律,并利用Liapunov方法证明了在该控制律作用下闭环系统的渐进稳定性;最后通过一个平面机器人的编队运动仿真验证了所提方法的有效性．     

Lur''''e系统稳定与同步的脉冲控制

提出了Lur’e系统的脉冲控制系统，利用关于脉冲系统稳定的几个定理，得到了具变化的脉冲区间的Lur'e系统镇定的充分条件；并且给出了Lur'e系统的适当参数与脉冲控制律，使得两个Lur'e系统脉冲同步。最后，给出数值例子说明本结论的有效性。