区间时滞相关离散非线性系统的鲁棒模型预测控制

针对一类带有扰动、输入约束和凸多面体不确定性的区间时滞离散非线性系统, 提出一种鲁棒模型预测控制方法. 一方面, 利用min-max 模型预测控制求解鲁棒模型预测控制器, 以研究鲁棒预测控制在范数有界意义下的扰动抑制问题; 另一方面, 充分利用时滞的上下界信息构造Lyapunov 函数以得到控制器存在的充分条件. 最后给出了闭环系统鲁棒稳定性证明.     

离散系统鲁棒稳定的简化条件及其反馈控制方法

给出了一种离散系统鲁棒稳定性的分析方法。通过对离散系统不确定部分不同表达式的研究，提出一种系统鲁棒稳定判别不等式。为解决系统鲁棒稳定性的实际计算问题，给出了离散系统鲁棒稳定性的另一种描述，井由此描述和不等式恒等变形，得到新的鲁棒稳定性判据。该判据结构筒单，很容易判定系统的鲁棒性。在此基础上，给出了系统鲁棒反馈控制的设计方法。     

Stochastic model predictive control for constrained discrete-time Markovian switching systems

In this paper we study constrained stochastic optimal control problems for Markovian switching systems, an extension of Markovian jump linear systems (MJLS), where the subsystems are allowed to be nonlinear. We develop appropriate notions of invariance and stability for such systems and provide terminal conditions for stochastic model predictive control (SMPC) that guarantee mean-square stability and robust constraint fulfillment of the Markovian switching system in closed-loop with the SMPC law under very weak assumptions. In the special but important case of constrained MJLS we present an algorithm for computing explicitly the SMPC control law off-line, that combines dynamic programming with parametric piecewise quadratic optimization.     

Sufficient conditions for stabilization of sampled-data nonlinear systems via discrete-time approximations

Given a parameterized (by sampling period T) family of approximate discrete-time models of a sampled nonlinear plant and given a family of controllers stabilizing the family of plant models for all T sufficiently small, we present conditions which guarantee that the same family of controllers semi-globally practically stabilizes the exact discrete-time model of the plant for sufficiently small sampling periods. When the family of controllers is locally bounded, uniformly in the sampling period, the inter-sample behavior can also be uniformly bounded so that the (time-varying) sampled-data model of the plant is uniformly semi-globally practically stabilized. The result justifies controller design for sampled-data nonlinear systems based on the approximate discrete-time model of the system when sampling is sufficiently fast and the conditions we propose are satisfied. Our analysis is applicable to a wide range of time-discretization schemes and general plant models.     

Input-to-state stable finite horizon MPC for neutrally stable linear discrete-time systems with input constraints

MPC or model predictive control is representative of control methods which are able to handle inequality constraints. Closed-loop stability can therefore be ensured only locally in the presence of constraints of this type. However, if the system is neutrally stable, and if the constraints are imposed only on the input, global asymptotic stability can be obtained; until recently, use of infinite horizons was thought to be inevitable in this case. A globally stabilizing finite-horizon MPC has lately been suggested for neutrally stable continuous-time systems using a non-quadratic terminal cost which consists of cubic as well as quadratic functions of the state. The idea originates from the so-called small gain control, where the global stability is proven using a non-quadratic Lyapunov function. The newly developed finite-horizon MPC employs the same form of Lyapunov function as the terminal cost, thereby leading to global asymptotic stability. A discrete-time version of this finite-horizon MPC is presented here. Furthermore, it is proved that the closed-loop system resulting from the proposed MPC is ISS (Input-to-State Stable), provided that the external disturbance is sufficiently small. The proposed MPC algorithm is also coded using an SQP (Sequential Quadratic Programming) algorithm, and simulation results are given to show the effectiveness of the method.     

Sufficient condition for asymptotic stability of discrete interval systems

A counter-example is given to a recent result on the stability analysis of interval matrices by Jiang (1988). A sufficient condition is then presented for the asymptotic stability of the discrete-time interval system X(k + 1) = A _I X(k), by testing the norms of extreme matrices of the interval matrix A _I such that they are all less than one.     

A component-based simulation environment for statistical process control systems analysis

This paper describes a simulation environment, called Prosim, which permits a user to define components, subsystems, and their interconnections to analyse a statistical process control (SPC) system. The components and systems are defined and analysed interactively. A library of standard SPC objects containing models for the Xbar, range, exponential weighted moving average, p-chart and other SPC techniques have been created which help define the control application. The PC-based tool is tested on theoretical, and real data, and is useful for the design and trouble shooting of a manufacturing system. It is also an effective teaching and research tool.     

On globally stable adaptive control providing l 1 tracking performance for linear discrete-time systems

Existing adaptive control algorithms at best guarantee that the tracking error is a l ₂ sequence. This paper presents globally stable adaptive control algorithms for linear discrete-time systems providing l ₁ tracking performance. Two algorithms with different degree of complexity are proposed, one for the case of known control directions, and a separate algorithm for the case of unknown control directions. It is demonstrated that in both cases the tracking error is l ₁ sequence, while the input and output signals are uniformly bounded.     

Sufficient and necessary conditions for discrete-time nonlinear switched systems with uniform local exponential stability

In this paper, we investigate sufficient and necessary conditions of uniform local exponential stability (ULES) for the discrete-time nonlinear switched system (DTNSS). We start with the definition of T-step common Lyapunov functions (CLFs), which is a relaxation of traditional CLFs. Then, for a time-varying DTNSS, by constructing such a T-step CLF, a necessary and sufficient condition for its ULES is provided. Afterwards, we strengthen it based on a T-step Lipschitz continuous CLF. Especially, when the system is time-invariant, by the smooth approximation theorem, the Lipschitz continuity condition of T-step CLFs can further be replaced by continuous differentiability; and when the system is time-invariant and homogeneous, due to the extension of Weierstrass approximation theorem, T-step continuously differentiable CLFs can even be strengthened to be T-step polynomial CLFs. Furthermore, three illustrative examples are additionally used to explain our main contribution. In the end, an equivalence between time-varying DTNSSs and their corresponding linearisations is discussed.     

布尔型模糊系统逼近的充分条件

为了保证布尔模糊系统逼近定义在紧集上任意实值连续函数的逼近精度．给出一个估计布尔模糊系统的输入变量与输出变量各自需要构造的模糊集个数的公式,讨论如何设计布尔模糊系统．以便实现逼近任给的实值连续函数到需要的逼近精度．最后通过一个例子展示了如何设计布尔模糊系统来逼近所给的连续函数的具体方法．     

Near-optimal tracking control for discrete-time systems with delayed input

This paper considers the near-optimal tracking control problem for discrete-time systems with delayed input. Using a variable transformation, the system with delayed input is transformed into a non-delayed system, and the quadratic performance index of the optimal tracking control is transformed into a relevant format. The optimal tracking control law is constructed by the solution of a Riccati matrix equation and a Stein matrix equation. A reduced-order observer is constructed to solve the physically realizable problem of the feedforward compensator and a near-optimal tracking control is obtained. Simulation results demonstrate the effectiveness of the optimal tracking control law.     

Robust stabilisation control for discrete-time networked control systems

We consider the analysis and synthesis of discrete-time networked control systems (NCSs), where the plant has additive uncertainty and the controller is updated with the sensor information at stochastic time intervals. It is shown that the problem is linked to H_∞-control of linear discrete-time stochastic systems and a new small gain theorem is established. Based on this result, sufficient conditions are given for ensuring mean square stability of the NCS, and the genetic algorithm is utilised to design the controller of the NCS based on a linear matrix inequality technique. An illustrative example is given to demonstrate the effectiveness of our proposed method.     

Feedback control for linear discrete-time systems with time delays

A new decomposition-coordination approach is presented to design control laws for linear discrete-time systems with distributed lags. By a proper decomposition of the criterion, one obtains a control law with partial feedbacks and an open loop part in order to satisfy the optimality conditions. On-line implementation of such a law is discussed and comparative examples are given to show the advantage brought by this method.     

A second-order maximum principle for discrete-time bilinear control systems with applications to discrete-time linear switched systems

A powerful approach for analyzing the stability of continuous-time switched systems is based on using optimal control theory to characterize the “most unstable” switching law. This reduces the problem of determining stability under arbitrary switching to analyzing stability for the specific “most unstable” switching law. For discrete-time switched systems, the variational approach received considerably less attention. This approach is based on using a first-order necessary optimality condition in the form of a maximum principle (MP), and typically this is not enough to completely characterize the “most unstable” switching law. In this paper, we provide a simple and self-contained derivation of a second-order necessary optimality condition for discrete-time bilinear control systems. This provides new information that cannot be derived using the first-order MP. We demonstrate several applications of this second-order MP to the stability analysis of discrete-time linear switched systems.     

Finite-time control for discrete-time switched systems with time delay

The problem of finite-time state feedback control is considered in this paper for a class of discrete-time switched systems with time delay. Firstly, the concepts of finite-time stability and finitetime boundedness are extended to discrete-time switched systems with time delay, respectively. Then, by resorting to the average dwell time approach and Lyapunov-Krasovskii functional technology, some new delay-dependent criteria guaranteeing finite-time boundedness and stability are developed. The state feedback controller is also obtained by virtue of a cone complement linearization (CCL) method. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed results.     

时滞离散系统的非线性准滑模鲁棒控制

针对一类变时滞离散系统,基于一种新型的非线性时变准滑模面设计方案,研究了系统的鲁棒滑模控制问题.首先,给出了该种非线性切换函数的一般形式,该类准滑模面具有时变的特征,且能够动态地改善系统的运动品质.利用自由权矩阵与线性矩阵不等式技术,给出了该类时滞离散系统非线性准滑模面的设计方法,并得到了稳定的非线性准滑模面存在的充分条件;其次,基于一种改进的离散趋近律方法,设计了相应的准滑模控制器,以保证系统的状态在有限时间内到达准滑模,从而将此类非线性系统的滑模变结构控制的分析与综合问题推广到了时滞非线性系统.最后,仿真结果表明,在本文所设计的准滑模面与准滑模变结构控制器的作用下,系统的状态是稳定的,且具有响应速度快、超调量小、调节时间较小等优点,从而说明了本文所设计方法的有效性.     

Robust decentralized model reference adaptive control of discrete-time interconnected systems

A robust decentralized model reference adaptive controller is proposed for a class of large-scale systems composed of several interconnected subsystems and described by state space equations. We have formulated a local adaptive controller for each subsystem using only local information such that the state of this subsystem tracks the corresponding state of a reference model. The content of the paper is limited to interconnected subsystems which are described by linear, deterministic, single-input single-output and discrete-time models with unknown and/or slowly time-varying parameters. Sufficient conditions, formulated by utilizing Lyapunov theory, are given for the overall system to be stabilizable by decentralized state feedback adaptive control laws. The results are illustrated by a numerical example.     

不需持续激励条件的非线性离散时间系统的自适应模糊逻辑控制

针对一类非线性离散时间系统，根据模糊逻辑系统的逼近性质，给出了一种自适应模糊逻辑控制器的设计方法。利用李亚普诺夫稳定性理论，证明了控制算法是全局稳定的，跟踪误差收敛于零的某一领域中。该设计方法克服了要求模糊基函数向量满足持续激励（PE）条件这一难以验证和满足的假设条件。     

Passivity analysis and control for discrete-time two-dimensional switched systems in Roesser model

This paper investigates the passivity issues of discrete-time two-dimensional switched systems in Roesser model under a state-dependent switching law. Conditions for passivity of discrete-time two-dimensional switched systems are obtained without the requirement of passivity of subsystems. When the system states are completely available, state feedback controllers and switching laws are designed. In the case of partial state measurements, dynamic output feedback controllers and switching laws depending only on the state of the output feedback controllers are constructed to guarantee passivity of the closed-loop switched system. Finally, numerical examples are provided to illustrate the efficiency of the results.     

Minimax control for discrete-time time-varying stochastic systems

This paper gives a self-contained presentation of minimax control for discrete-time time-varying stochastic systems under finite- and infinite-horizon expected total cost performance criteria. Suitable conditions for the existence of minimax strategies are proposed. Also, we prove that the values of the finite-horizon problem converge to the values of the infinite-horizon problems. Moreover, for finite-horizon problems an algorithm of calculation of minimax strategies is developed and tested by using time-varying stochastic systems.