不同阶分数阶混沌系统的同步与参数辨识

针对不确定分数阶混沌系统的同步和参数辨识问题,提出一种新的方法,即用不同阶分数阶系统来同步和参数辨识.利用主动控制和预控制量方法,基于分数阶混沌系统稳定性理论和自适应控制理论,设计控制器,实现不同阶分数阶混沌系统之间的同步和参数辨识.理论和仿真结果实现了不同阶Chen 系统间的同步和辨识,表明了该方法的有效性.     

Bayesian assessing for a repairable system with standby imperfect switching and reboot delay

System performance measures of a repairable system are studied from a Bayesian viewpoint with different types of priors assumed for unknown parameters, in which the system consists of two active components and one warm standby. There is a failure probability q that switches from standby state to active state. Time-to-failure of components is assumed to be an exponential distribution. The reboot time and repair time are also exponential distributions. When time-to-failure, time-to-repair and reboot time are with uncertain parameters, a Bayesian assessing is adopted to evaluate system performance measures. Monte Carlo simulation is used to derive the posterior distribution for the steady-state availability and the mean time-to-system failure. Some numerical experiments are performed to illustrate the results derived in this article.     

A nonlinear robust PI controller for an uncertain system

This paper presents a smooth control strategy for the regulation problem of an uncertain system, which assures uniform ultimate boundedness of the closed-loop system inside of the zero-state neighbourhood. This neighbourhood can be made arbitrarily small. To this end, a class of nonlinear proportional integral controllers or PI controllers was designed. The behaviour of this controller emulates very close a sliding mode controller. To accomplish this behaviour saturation functions were combined with traditional PI controller. The controller did not need a high-gain controller or a sliding mode controller to accomplish robustness against unmodelled persistent perturbations. The obtained closed-solution has a finite time of convergence in a small vicinity. The corresponding stability convergence analysis was done applying the traditional Lyapunov method. Numerical simulations were carried out to assess the effectiveness of the obtained controller.     

Variable structure sliding mode control for a class of uncertain distributed parameter systems with time-varying delays

This article considers sliding mode control of a class of parabolic linear uncertain distributed parameter systems with time-varying delays. The sliding mode controller design does not contain time delay terms and drives the state trajectory of the system to the sliding manifold in finite time. A sufficient condition of asymptotic stability for the sliding motion is derived. A simulation example is presented to illustrate effectiveness of the proposed method.     

Robust adaptive control for a class of uncertain strict‐feedback nonlinear systems

In this paper, robust adaptive control is presented for a class of perturbed strict‐feedback nonlinear systems with both completely unknown control coefficients and parametric uncertainties. The proposed design method does not require the a priori knowledge of the signs of the unknown control coefficients. For the first time, the key technical Lemma is proven when the Nussbaum function is chosen by N(ζ)=ζ²cos(ζ), based on which the proposed robust adaptive scheme can guarantee the global uniform ultimate boundedness of the closed‐loop system signals. Simulation results show the validity of the proposed scheme. Copyright © 2008 John Wiley & Sons, Ltd.     

Sensor fault diagnosis of singular delayed LPV systems with inexact parameters: an uncertain system approach

In this paper, sensor fault diagnosis of a singular delayed linear parameter varying (LPV) system is considered. In the considered system, the model matrices are dependent on some parameters which are real-time measurable. The case of inexact parameter measurements is considered which is close to real situations. Fault diagnosis in this system is achieved via fault estimation. For this purpose, an augmented system is created by including sensor faults as additional system states. Then, an unknown input observer (UIO) is designed which estimates both the system states and the faults in the presence of measurement noise, disturbances and uncertainty induced by inexact measured parameters. Error dynamics and the original system constitute an uncertain system due to inconsistencies between real and measured values of the parameters. Then, the robust estimation of the system states and the faults are achieved with H_∞ performance and formulated with a set of linear matrix inequalities (LMIs). The designed UIO is also applicable for fault diagnosis of singular delayed LPV systems with unmeasurable scheduling variables. The efficiency of the proposed approach is illustrated with an example.     

不确定时滞分布参数系统鲁棒控制的LMI方法

对常时滞、变时滞的不确定分布参数控制系统,提出了一种与现有的研究分布参数控制系统不同的鲁棒控制方法.该方法通过构造平均Lyapunov函数,利用线性矩阵不等式知识,在只要求系统本身所固有的系数是负定矩阵的条件下,给出了所给的分布参数系统镇定的充分条件.当模型中的时滞为常时滞时,所得的充分条件与时滞无关.当模型中的时滞为变时滞时,所得模型的镇定准则依赖于时滞.此外,该方法与已有方法比较的一个显著优点就是所获得的条件容易检验,因而易于应用.最后举了一个实例以说明该方法的有效性.     

不确定隶属函数T-S模糊控制器设计与稳定分析

针对许多非线性系统存在的结构不确定和难以用精确数学模型表达等问题,在研究基本Takagi-Sugeno(T-S)模糊模型的基础上,通过增加一个隶属函数自由变量,利用线性矩阵不等式(LMI)设计了一个使得闭环系统渐进稳定的状态反馈控制器,并给出稳定条件.所得到的条件充分利用了前件变量隶属函数的结构信息和后件局部子系统之间的相互关系,降低了常规T-S模糊系统的稳定性条件的保守性和求解难度.通过仿真实例验证了该方法的可行性和有效性.     

Decentralized tracking control for linear uncertain interconnected systems with time delays

This paper investigates the robust output tracking problem for a class of large‐scale linear uncertain systems with interactions and time delays. Time delays exist in both states and controls. Using the Riccati equation, a procedure for determining decentralized linear control laws is presented such that the closed‐loop system asymptotically tracks the reference output and rejects any constant but unknown disturbances. The main feature of this approach is that the uncertain systems may contain time delays in both states and controls as well as in interactions between subsystems. A numerical example is included to show the results. Copyright © 2008 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

基于容许集的多胞不确定系统三模RMPC

针对输入和状态受约束的多胞不确定线性系统,提出了基于容许集的扩大吸引域三模鲁棒模型预测控制方法.在多面体不变集离线模型预测控制算法的基础上引入容许集,以多面体不变集序列的并集作为模态1,基于N步容许集的控制容许集作为模态2,并利用离线设计和在线优化的控制策略,设计了三模变终端约束鲁棒模型预测控制算法,以实现系统渐近稳定.该算法不仅降低了在线运算量,而且扩大了吸引域.最后的仿真结果验证了所提出算法的有效性.