一类非线性时变系统的鲁棒输出跟踪控制

研究一类具有非匹配不确定性的非线性时变系统的鲁棒状态反馈输出跟踪控制器设计问题。通过引入非线性时变系统的相对阶将系统输入输出线性化,然后设计出一种基于标称系统和不确定性上界的连接型鲁棒输出跟踪控制器,利用该方案设计的控制器可保证整个闭环系统是一致有界稳定的,且闭环输出可以渐近跟踪期望的轨迹。     

具有非匹配扰动的非线性变参数系统模型参考跟踪控制

本文研究了一类含有非匹配扰动的非线性变参数系统的跟踪控制问题.首先,设计非线性扰动观测器用于估计系统所受到的未知扰动.其次,在前馈–反馈跟踪控制器中引入扰动补偿控制项,提出一种基于扰动观测器的跟踪控制策略.利用依赖于状态和时变参数的线性矩阵不等式,导出保证闭环系统输入–状态稳定的充分条件,进而运用平方和凸优化技术解析地构造出扰动观测器和跟踪控制器.通过理论证明,所设计的控制策略能够实现非线性变参数系统输出对参考模型输出的跟踪,消除输出通道中非匹配扰动的影响.最后,由数值仿真例子验证了所提方法的有效性.     

一阶伪线性系统的模型参考输出跟踪控制

针对伪线性系统的模型参考输出跟踪问题,设计伪线性系统的模型参考跟踪策略.控制器分为两部分,其一为反馈镇定控制器,保证闭环系统是渐近稳定的;另一为前馈补偿控制器,通过求解基于控制器存在条件建立的方程组得到控制器的参量矩阵,使得闭环系统的输出渐近跟踪参考系统的输出,且当系统中存在时变系数时方法仍是有效的,控制器中保有部分自由度可以进一步利用,以提高具体控制任务所需的系统性能.数值仿真验证了所提出方法的有效性.     

一类线性不确定组合系统的输出反馈分散输出跟踪控制

讨论了线性不确定组合系统的鲁棒分散输出渐近跟踪问题.基于Lyapunov方程正 定解的存在性,给出了输出反馈跟踪控制器的设计方法.对于系统中所有允许的不确定性,所 设计的控制器均使系统的输出渐近跟踪所给定的参考信号,同时系统的状态保持有界.     

不确定未知界的相似组合系统分散自适应输出反馈控制

研究一类具有加性振动的不确定相似组合大系统的分散自适应输出反馈镇定问题,给出了该系统输出反馈镇定的条件。受控系统的不确定项可以是非线性的或时变的,输入通道不确定性满足一般限制,系统的不确定项的界是存在的但却是未知的。所设计的确定性非线性控制器能保证受控系统渐近收敛于系统的平衡点,并且自适应律保持有界。最后进行了仿真研究,表明所得结论是正确脯效的。     

时变不确定非线性系统自适应滑模跟踪控制

针对一般的具有时变且界未知的非线性不确定性的单输入多输出非线性系统,提出一种自适应滑模跟踪控制器的框架.在该框架内,系统的时变且界未知的非线性不确定性可以通过函数逼近技术(FAT)表示成为一组正交基函数序列的组合,并通过滑模控制技术和直接Lyapunov方法获得基函数系数的更新律以及对不确定性逼近误差的在线自适应补偿,从而得到自适应的滑模控制律.所提出的基于函数逼近技术的自适应滑模跟踪控制策略在直流电机跟踪控制系统实验装置上进行了实际控制实验,并进行了性能的对比与分析.     

具有参数不确定性的非线性系统的鲁棒输出跟踪

研究具有非线性参数化的非线性系统的输出跟踪问题.采用时变状态反馈控制律, 指数镇定输出跟踪误差,并保证非线性系统的所有状态是有界的.为了实现时变状态反馈控 制律,设计高增益鲁棒观测器观测构造该控制律所需要的状态,使得整个闭环系统的输出能 渐近跟踪期望输出,且该闭环系统中所有信号都是有界的.     

一类增长率依赖输出的非线性系统的输出反馈输出跟踪控制

研究一类增长率依赖输出非线性系统的输出反馈输出跟踪控制问题.利用系统结构特点,构造出系统实现输出跟踪时内部状态的渐近轨迹.通过建立状态与渐近轨迹偏差的动态方程,将输出跟踪问题转化为偏差系统的镇定问题,然后通过设计偏差系统的输出反馈镇定控制器给出输出反馈输出跟踪控制器.最后以仿真实例验证本文结论.     

一类线性时变系统的输出反馈控制

基于线性时不变系统能控能观标准型变换及非线性系统高增益观测器方法,本文研究了一类线性时变系统 的输出反馈控制问题. 通过引入时变的状态变量坐标变换,分别设计了线性时变系统的状态反馈控制器、状态观测器以及基于 状态观测器的输出反馈控制器. 进一步地,本文分别证明了观测器动态误差是渐近收敛于零的,而状态反馈控制器以及输出反馈控制器可以 保证闭环系统的渐近稳定性.     

严格反馈非线性时变系统的迭代学习控制

针对一类含未知时变参数的严格反馈非线性系统, 提出一种实现有限作业区间轨迹跟踪控制的迭代学习算法. 基于Lyapunov-like方法设计控制器, 回避了常规迭代学习控制中受控系统非线性特性需满足全局Lipschitz连续条件的要求. 以反推设计(Backstepping)方法设计控制器, 为使得虚拟控制项可导, 引入一级数收敛序列; 将时变参数展开为有限项多项式形式, 在控制器设计中采取双曲正切函数处理余项对于系统跟踪性能的影响. 理论分析表明, 闭环系统所有信号有界, 并能够实现系统输出完全收敛于理想轨迹.     

Design of robust-optimal output feedback controllers for linear uncertain systems using LMI-based approach and genetic algorithm

This paper considers the robust-optimal design problems of output feedback controllers for linear systems with both time-varying elemental (structured) and norm-bounded (unstructured) parameter uncertainties. Two new sufficient conditions are proposed in terms of linear-matrix-inequalities (LMIs) for ensuring that the linear output feedback systems with both time-varying elemental and norm-bounded parameter uncertainties are asymptotically stable, where the mixed quadratically-coupled parameter uncertainties are directly considered in the problem formulation. A numerical example is given to show that the presented sufficient conditions are less conservative than existing ones reported recently. Then, by integrating the hybrid Taguchi-genetic algorithm (HTGA) and the proposed LMI-based sufficient conditions, a new integrative approach is presented to find the output feedback controllers of the linear systems with both time-varying elemental and norm-bounded parameter uncertainties such that the control objective of minimizing a quadratic integral performance criterion subject to the stability robustness constraint is achieved. A design example of the robust-optimal output feedback controller for the AFTI/F-16 aircraft control system with the time-varying elemental parameter uncertainties is given to demonstrate the applicability of the proposed new integrative approach.     

Synthesis of adaptive gain robust model-following/tracking controllers for a class of uncertain linear systems

This paper proposes a new adaptive gain robust model-following/tracking controller for a class of uncertain linear systems. The proposed adaptive gain robust controller is composed of state feedback laws with fixed gains, feedfoward inputs for the reference model and nonlinear compensation inputs with adjustable time-varying parameters. Moreover, the proposed control strategy can achieve good transient performance and avoid the excessive control input by means of the design parameter. In this paper, linear matrix inequality-based sufficient conditions for the existence of the proposed adaptive gain controller are given, and two design strategies are presented. Finally, simple illustrative examples are included to show the effectiveness of the proposed adaptive gain robust controller.     

Universal integral controllers for minimum-phase nonlinear systems

We consider a single-input-single-output (SISO) nonlinear system that has a well-defined normal form with asymptotically stable zero dynamics. Using only knowledge of the relative degree and the sign of the high-frequency gain, we design an output feedback integral controller that asymptotically regulates the output to a bounded time-varying reference signal with a constant limit. We give regional as well as semi-global results. We also show that, for relative degree one and two systems, the proposed integral controller reduces to the classical PI and PID controllers, respectively     

Set-valued observers and optimal disturbance rejection

A set-valued observer (also called guaranteed state estimator) produces a set of possible states based on output measurements and models of exogenous signals. We consider the guaranteed state estimation problem for linear time-varying systems with a priori magnitude bounds on exogenous signals. We provide an algorithm to propagate the set of possible states based on output measurements and show that the centers of these sets provide optimal estimates in an l^∞-induced norm sense. We then consider the utility of set-valued observers for disturbance rejection with output feedback and derive the following general separation structure. An optimal controller can consist of a set-valued observer followed by a static nonlinear function on the observed set of possible states. A general construction of this function is provided in the scalar control case. Furthermore, in the special case of full-control, i.e., the number of control inputs equals the number of states, optimal output feedback controllers can take the form of an optimal estimate of the full-state feedback controller     

Iterative inversion of neural networks and its application toadaptive control

An iterative constrained inversion technique is used to find the control inputs to the plant. That is, rather than training a controller network and placing this network directly in the feedback or feedforward paths, the forward model of the plant is learned, and iterative inversion is performed on line to generate control commands. The control approach allows the controllers to respond online to changes in the plant dynamics. This approach also attempts to avoid the difficulty of analysis introduced by most current neural network controllers, which place the highly nonlinear neural network directly in the feedback path. A neural network-based model reference adaptive controller is also proposed for systems having significant dynamics between the control inputs and the observed (or desired) outputs and is demonstrated on a simple linear control system. These results are interpreted in terms of the need for a dither signal for on-line identification of dynamic systems.     

Robust static output feedback control for linear discrete-time systems with time-varying uncertainties

This paper is concerned with the problem of designing robust static output feedback controllers for linear discrete-time systems with time-varying polytopic uncertainties. Sufficient conditions for robust static output feedback stabilizing controller designs are given in terms of solutions to a set of linear matrix inequalities, and the results are extended to H₂ and H_∞ static output feedback controller designs. Numerical examples are given to illustrate the effectiveness of the proposed design methods.     

Time-varying feedforward and output feedback controllers for nonlinear time-delay processes

The problem of output regulation of nonlinear time-delay processes with time-varying disturbances is considered. We present a new disturbance-dependent coordinate transformation for the linearization of nonlinear time-varying processes. In our proposed controller configuration, the modified Smith-type predictor plays the central role. Using this approach, the modified Smith-type predictor is composed of a nonlinear process model and a linear internal model. The presented feedforward and dead-time compensation can eliminate the effect of delayed disturbances on the output. With the aid of the incorporating linear internal model it aims to achieve both the asymptotic output regulation and the dead time compensation. A reduced-order controller structure for nonlinear time-delay processes can also asymptotically track the desired trajectory. Finally, the synthesis controllers are successfully implemented for chemical reactor systems.     

Output regulation of a class of linear systems with switched exosystems

In this article we investigate the output regulation (servomechanism) problem of linear systems with external inputs generated by switched linear systems. We use switching controllers and consider both the full information and the error feedback controllers under the assumption that there is a synchronization between exosystem and controller switching.