基于观测器的受扰多项式系统H∞输出跟踪控制

考虑一类受到外部扰动影响的多项式系统在状态不完全可测情况下的H_∞输出跟踪控制问题.首先,综合前馈-反馈复合控制思想,设计基于观测器的输出跟踪控制器,其中反馈镇定控制器用于保证闭环系统稳定,前馈补偿控制器用以实现对参考模型输出信号的跟踪;然后,提出具有输出反馈结构的跟踪控制方法,其优势在于实现了分离原则,可单独设计观测器和控制器,降低计算复杂度;接着,利用依赖全状态的齐次多项式Lyapunov函数导出使得闭环系统渐近稳定且满足H_∞跟踪性能的充分条件,借助多项式平方和凸优化技术可直接求得相应的观测器和控制器;最后,通过数值仿真实例验证所提出设计方法的有效性和优越性.     

一类非线性系统的输出反馈半局鲁棒镇定

从半局镇定角度研究了一类非线性系统的输出反馈镇定问题,这类系统具有较强的非线性增长特征.利用高增益观测器,把非分离设计原则应用于输出反馈半局镇定控制器设计.在不需系统具有一个一致完全可观状态反馈控制器情况下,给出了输出反馈控制器的设计方法.对任意给定紧子集,所设计的反馈控制器使闭环系统是渐近稳定的且吸引域包含指定的紧子集.最后的仿真实例说明了设计方法的有效性.     

一类非线不确定组合系统基于观测器的鲁棒分散镇定

讨论一类组合系统的鲁棒观测器的设计及该类系统基于估计状态反馈分形镇定问题。所设计的变结构观测器使得观测误差渐近趋于零,基于估计状态所设计的鲁棒分散控制器确保闭环系统是渐近稳定的,系统的相似结构使得所设计的各个子系统的分散观测器以及控制器在结构上具有一致性,从而简化了系统的设计。     

一类非线性不确定组合系统基于观测器的鲁棒分散镇定

讨论一类组合系统的鲁棒观测器的设计及该类系统基于估计状态反馈分散镇定问题.所设计的变结构观测器使得观测误差渐近趋于零,基于估计状态所设计的鲁棒分散控制器确保闭环系统是渐近稳定的,系统的相似结构使得所设计的各个子系统的分散观测器以及控制器在结构上具有一致性,从而简化了系统的设计.     

一类非线性系统的控制器和观测器设计

研究一类非线性系统的全状态反馈控制问题、观测器设计问题及输出反馈控制设计问题.首先设计出非线性全状态反馈控制器,获得了系统指数镇定的充分条件.然后提出了非线性观测器,并证明了该观测器是指数稳定观测器.进一步,在控制器和观测器问题的充分条件满足的假设下,证明了提出的带估计状态的反馈控制能达到指数镇定.最后,仿真实例验证了所得结果的有效性.     

一类开关切换系统的输出反馈镇定

对一类子系统为线性的开关切换系统进行观测器设计，并给出系统动态输出反馈可镇定的充分条件。在所设计的观测器基础上，以系统状态的观测值为依据设计各子控制器和切换方案，使整个闭环系统是指数渐近稳定的。对于切换时间间隔受限制的情况，给出了相应的动态输出反馈可镇定条件和镇定控制方案。实例仿真结果表明，所给出的设计方案是可行的。     

非线性微分——代数系统的输出反馈镇定控制

对满足线性增长条件的非线性微分--代数系统, 研究了其输出反馈镇定控制问题. 通过将状态观测器与控制器耦合在一起设计, 构造出一种非初始化的线性高增益状态观测器, 具有良好的鲁棒性. 基于反推设计方法构造出一个线性的动态输出补偿器, 使得整个闭环系统是渐近稳定的. 仿真结果验证了本文所提控制方法的有效性.     

严格反馈非线性系统的自适应神经网络输出反馈控制

基于非线性反馈函数,文章设计神经网络状态观测器,解决一类非线性系统的输出反馈控制问题.非线性反馈神经网络观测器在系统存在不确定性函数的情况下实时估计系统状态.利用所获得的状态信号,设计了自适应神经网络动态面控制器,同时保证了闭环系统的稳定性和所有信号的有界性.通过调节设计参数的取值能够达到期望的闭环跟踪性能.数值仿真表明,所设计的状态观测器不需要对原系统做状态变换,能够克服输出反馈滑模控制器带来的抖震问题.     

时滞系统的状态反馈和基于观测嚣的输出反馈设计

考虑了同时具有状态和输入时滞线性定常系统的H∞镇定问题．基于动态耗散理论和微分对策原理,通过采用带积分项的储存函数,对系统的状态反馈控制器和基于观测器的输出反馈设计问题进行了处理．它们的可解充分条件可以化为与时滞相关的矩阵不等式和Riccati方程的形式．得到的与时滞相关的状态反馈控制律和基于观测器的输出反馈控制律都能使闭环系统内稳且具有H∞干扰衰减．     

带有随机时延的非线性网络控制系统的输出反馈镇定

考虑了一类非线性网络控制系统的输出反馈镇定问题.通过齐次马尔可夫链来描述采样器-控制器和控制器.执行器的时延,将网络控制系统建模为带跳非线性系统.利用Lyapunov方法和线性矩阵小等式技巧,得到了闭环系统随机稳定的充分条件,并给出了镇定控制器的设计方法.     

低阶时滞过程的伪预测PI／PID控制

基于单位反馈控制结构,根据期望的闭环传递函数设计得到了一种伪预测PI/PID(ADQPI/ADQPID)控制器。这种控制器只有一个可调参数,可调参数与系统动态响应性能和鲁棒稳定性之间存在直接关系,只需单调的调节控制器参数,便可实现系统的动态响应性能与鲁棒稳定性之间的最佳折衷。仿真实例表明,这种控制器在扰动和模型失配的情况下仍然具有良好的控制性能和鲁棒稳定性,是一种值得在实际工程中推广运用的新型控制器。     

Optimum Design of Fractional Order Pid Controller Using Chaotic Firefly Algorithms for a Control CSTR System

A fractional‐order PID controller is a generalization of a standard PID controller using fractional calculus. Compared with the standard PID controller, two adjustable variables, “differential order” and “integral order”, are added to the PID controller. Fractional‐order PID is more flexible, has better responses, and the precise adjustment closed‐loop system stability region is larger than that of a classic PID controller. But the design and stability analysis is more complicated than for the PID controller. Therefore, the optimal setting of parameters is very important. A firefly algorithm in standard mode has only local optimization and accuracy is low. In order to fix this flaw an improved chaotic algorithm firefly is proposed for a design controller FOPID. To evaluate the performance of the proposed controller, it has been used in the control of a CSTR system with a variety of fitness functions. Simulations confirm the optimal performance of the proposed controller.     

An LMI approach to dencentralized H8 control

We consider the design of a decentralized controller for a linear time invariant (LTI) system. This system is modelled as an interconnection of subsystems. For every subsystem, a linear time invariant controller is sought such that the overall closed loop system is stable and achieves a given H performance level. The main idea is to design every local controller such that the corresponding closed loop subsystem has a certain input-output (dissipative) property. This local property is constrained to be consistent with the overall objective of stability and performance. The local controllers are designed simultaneously, avoiding the traditional iterative process: both objectives (the local one and the global one) are achieved in one shot. Applying this idea leads us to solving the following new problem: given an LTI system, parameterize all the dissipative properties which can be achieved by feedback. The proposed approach leads to solving convex optimization problems that involve linear matrix inequality constraints.     

Characteristic model based adaptive controller design and analysis for a class of SISO systems一类SISO系统基于特征模型的极点配置自适应控制设计与分析

The design of an adaptive controller and stability analysis of the corresponding closed loop system are discussed for a class of SISO systems based on the characteristic model method. The obtained characteristic model is a second-order slow time-varying linear system with a compress mapping function for the system modeling error. The pole placement method is used to design the controller, and sufficient conditions for the stability of the closed loop system are obtained based on the robust control theory of slow time-varying systems with perturbations. The effectiveness of the proposed method is illustrated by two numerical examples.     

Sensor fault tolerant control of nonlinear Takagi–Sugeno systems. Application to vehicle lateral dynamics

This paper presents a new scheme for sensor fault tolerant control for nonlinear systems based on the Takagi–Sugeno modeling. First, a structured residual generator aimed at detecting and isolating sensor faults is designed. A bank of observers controlled either by only one system output or a set of outputs is then implemented, leading to a set of state estimates. The parallel distributed compensation structure is adopted to design the fault tolerant controller. The novelty in this paper is that the estimated state used in the controller is a weighted state vector obtained from all the estimated states provided by the different observers. The weighting functions depend on the residual vector signals delivered by the residual generator. They are designed to avoid crisp switches in the control law. Indeed, the interesting feature of the proposed approach is to avoid the commonly used switching strategy. For each residual component, the greater its magnitude is, the less the weight affected to the corresponding state estimate is. Consequently, the controller only uses estimations computed on the basis of healthy measurements. The closed‐loop stability is studied with the Lyapunov theory, and the obtained conditions are expressed as a set of linear matrix inequalities. The proposed residual generation and fault tolerant controller are applied to a vehicle lateral dynamics affected by sensor faults. Copyright © 2015 John Wiley & Sons, Ltd.     

Coordination of two robot manipulators based on position measurements only

In this note we propose a controller that solves the problem of coordination of two (or more) robots, under a master-slave scheme, in the case when only position measurements are available. The controller consists of a feedback control law, and two non-linear observers. It is shown that the controller yields ultimate uniformly boundedness of the closed loop errors, a relation between this bound and the gains on the controller is established. Simulation results on two twolink robot systems show the predicted convergence performance.     

Asymptotic Stability and Finite‐Time Stability of Networked Control Systems: Analysis and Synthesis

This paper focuses on the problems of asymptotic stability and finite‐time stability (FTS) analysis, along with the state feedback controller design for networked control systems (NCSs) with consideration of both network‐induced delay and packet dropout. The closed‐loop NCS is modeled as a discrete‐time linear system with a time‐varying, bounded state delay. Sufficient conditions for the asymptotic stability and the FTS of the closed‐loop NCS are provided, respectively. Based on the stability analysis results, a mixed controller design method, which guarantees the asymptotic stability of the closed‐loop NCS in the usual case and the FTS of the closed‐loop NCS in the unusual case (that is, in some particular time intervals, large state delay occurs), is presented. A numerical example is provided to illustrate the effectiveness of the proposed mixed controller design method.     

Stability analysis of nonlinear processes using empirical state affine models and LMIs

A novel methodology is proposed for the analysis of robust stability of a nonlinear process under PI (Proportional-Integral) control. The analysis is based on state-affine empirical models regressed from input-output data. The state model is represented by a set of polynomial matrices nonlinear with respect to the manipulated variables. This model in combination with a linear PI controller results in a closed loop model that can be shown to lie in a polytope of matrices. This allows for the formulation of a Lyapunov stability test in terms of a simple set of LMIs (linear matrix inequalities). This set of inequalities can be also expanded to account for input saturation. The stability analysis produces regions of stability, in terms of the PI controller parameters, that are significantly larger than the regions previously calculated by a singular value test. The issues of saturation and modeling error are also incorporated into the analysis. The technique permits also to test the stability of the closed loop system with a gain scheduling PI controller. The conservativeness of the analysis is assessed by comparison to closed loop simulations of a highly nonlinear CSTR (continuous stirred tank reactor) under PI control.     

模糊系统的稳定性分析与最优控制器设计

针对一类线性系统,首先设计了一种模糊控制器保证闭环系统的稳定性.根据得到的结果,如果只需满足稳定性条件,可以有很大的空间选择控制器参数.因此,本文根据Pontryagin最小值原理给出了一种最优模糊控制器的设计方法.     

Model predictive control for networked control systems

This paper investigates the problem of model predictive control for a class of networked control systems. Both sensor‐to‐controller and controller‐to‐actuator delays are considered and described by Markovian chains. The resulting closed‐loop systems are written as jump linear systems with two modes. The control scheme is characterized as a constrained delay‐dependent optimization problem of the worst‐case quadratic cost over an infinite horizon at each sampling instant. A linear matrix inequality approach for the controller synthesis is developed. It is shown that the proposed state feedback model predictive controller guarantees the stochastic stability of the closed‐loop system. Copyright © 2008 John Wiley & Sons, Ltd.