互质因子摄动系统最优l1鲁棒控制:连续性与自适应控制

针对具有互质因子摄动和未知干扰的离散时间系统研究了一种自适应鲁棒控制策略. 本文的主要工作包括三个方面.首先建立了互质因子摄动系统最优l1鲁棒控制设计的连续性. 然后,提出了一种带变死区的参数鲁棒估计投影算法.最后,结合所提出的参数估计算法和最优 l1鲁棒控制,利用确定性等价原理提出了互质因子摄动系统的一种新的自适应鲁棒控制方法.基 于本文建立的l1优化设计的连续性,证明了自适应鲁棒控制的全局稳定性,给出了自适应控制系 统稳定性的后验可计算条件.     

互质因子摄动系统最优е1鲁棒控制: 连续性与自适应控制

针对具有互质因子摄动和未知干扰的离散时间系统研究了一种自适应鲁棒控制策略. 本文的主要工作包括三个方面. 首先建立了互质因子摄动系统最优е1鲁棒控制设计的连续性. 然后,提出了一种带变死区的参数鲁棒估计投影算法. 最后, 结合所提出的参数估计算法和最优е1鲁棒控制,利用确定性等价原理提出了互质因子摄动系统的一种新的自适应鲁棒控制方法. 基于本文建立的е1优化设计的连续性, 证明了自适应鲁棒控制的全局稳定性,给出了自适应控制系统稳定性的后验可计算条件.     

互质因子摄动下的最优鲁棒稳态跟踪控制器设计

研究了存在未知外部干扰时的互质因子摄动系统的鲁棒稳态追踪问题.利用Youla参数化方法，提出了一个最坏情况稳态绝对误差的精确计算公式.该公式使得最优稳态跟踪控制器设计问题等价于保证系统鲁棒稳定时e1的最优鲁棒控制器设计问题.     

不确定性离散时间系统非保守自适应鲁棒控制

研究含未知干扰和互质因子摄动离散时间不确定性系统的自适应鲁棒控制问题，为非保守的自适应鲁棒镇定提出一种广义参数递推估计方法，基于确定性等价原理，并利用ι1设计方法提出一种自适应鲁棒控制策略，证明了自适应算法的全局收敛性，给出了一个可验算的鲁棒稳定性条件，证明了该鲁棒稳定性条件是非保守和最优的。     

基于互质因子摄动的反馈系统的鲁棒稳定性

考虑对象和控制器同时具有互质因子摄动时闭环系统的鲁棒稳定性问题,得到了闭环 系统鲁棒稳定的充要条件并给出了鲁棒控制器的优化设计方法.     

基于互质因子摄动的系统非脆弱鲁棒解耦控制

研究对象和控制器存在互质因子不确定性时闭环系统鲁棒稳定和非脆弱鲁棒解耦控制问题,得到了闭环系统具有鲁棒稳定性和鲁棒解耦性能的充分条件,给出了鲁棒控制器的优化设计方法.     

基于l_∞范数和l_1范数最小化的二自由度最优鲁棒跟踪控制

研究了具有乘摄动模型不确定性并存在未知干扰系统的最优鲁棒跟踪控制问题 .采用二自由度控制器结构Youla参数化方法将最优鲁棒跟踪控制问题转化为两个相互独立的优化问题 :跟踪问题和鲁棒设计问题 .跟踪问题以l∞ 范数为性能指标通过极小化跟踪误差的最大幅值实现最优跟踪控制 ;鲁棒性设计问题中 ,将模型不确定性视为一种外界干扰 ,通过极小化干扰到误差的灵敏度函数的l1范数使得干扰对跟踪误差的影响最小 .通过截断处理 ,上述两种优化问题均可化为标准线性规划问题 .给出了截断阶数与逼近误差之间的关系 .仿真结果表明新方法的有效性 .     

时变不确定性系统的二自由度最优鲁棒稳态跟踪控制器设计

研究了被控系统存在范数有界的时变模型摄动和未知外部干扰时鲁棒稳态跟踪问题. 利用二自由度控制结构和Youla参数化方法.提出了一个最坏情况稳态绝对误差的精确计算公 式,利用该公式最优稳态跟踪控制器设计问题可化为一个有限维l1优化问题.因此控制器设计 只需解一个标准线性规划问题.此外,还证明了所提出的控制器可同时保证系统的鲁棒稳定性 和最优跟踪性能.仿真结果表明了该方法的有效性和可行性.     

基于l∞范数和l1范数最小化的二自由度最优鲁棒跟踪控制

研究了具有乘摄动模型不确定性并存在未知干扰系统的最优鲁棒跟踪控制问题,采用二自由度控制器结构Youla参数化方法将最优鲁棒跟踪控制问题转化为两个相互独立的优化问题,跟踪问题和鲁棒设计问题,跟踪问题以l∞范数为性能指标通过极小化跟踪误差的最大幅值实现最优跟踪控制;鲁棒性设计问题中,将模型不确定性视为一种外界干扰,通过极小化干扰到误差的灵敏度函数的l1范数使得干扰对跟踪误差的影响最小,通过截断处理,上述两种优化问题均可化为标准线性规划问题,给出了截断阶数与逼近误差之间的关系,仿真结果表明新方法的有效性。     

H∞回路成形设计的鲁棒性

回路成形法设计中是用互质因子摄动来表示系统不确定性的. 文中对这种互质因子摄动进行了较详尽的分析, 指出系统中的弱阻尼模态会增大互质因子摄动的范数, 因而降低了允许的摄动值, 使系统实际上失去了鲁棒性. 所以H∞回路成形设计并不一定像所期望的那样具有鲁棒性. 文中并用一个参数摄动下的鲁棒性为例来进行说明.     

Continuous-time optimal robust servo-controller design with internal model principle

The linear quadratic design of an optimal robust servo–controller for a continuous–time control system is described. It introduces a servo–control performance measure which accommodates the internal model principle. The measure selectively discounts penalties on control effort of desirable frequencies and provides complete flexibility in the selection of weighting matrices. The proposed servo–controller uses plant state feedback, signal state feedforward and a servo–compensator for ensuring robust asymptotic command tracking and disturbance rejection. An informal alternate proof of the internal model principle in the state variable domain is presented using an operator-transformation technique. Where necessary, observers are used to complement the servo-controller. The proposed optimal robust servo–controller yields the expected superior performance in terms of response and error minimization. An illustrative example is given.     

Control of LTI systems subject to unanticipated extreme perturbations using self-tuning 3-term switching controllers

In the design of conventional control systems for a multivariable system, using robust/adaptive control techniques, the motivation is to design a controller which "works satisfactorily" in the presence of plant uncertainty. Unfortunately, however, if large unanticipated structural changes subsequently occur in the system, severe limitations in practical performance may occur, since such conventional control schemes usually do not have the ability to control systems which are subject to unplanned extreme changes. Moreover, for the realistic situation when control input constraints exist, few results for continuous time multivariable systems are available. In this paper, a new class of self-tuning proportional-integral-derivative switching controllers, which is an extension of the self-tuning integral controller of Miller and Davison, is described, and has the property that it is robust to unplanned extreme changes in the plant and satisfies any feasible control signal input constraints. Results of this self-tuning controller when applied to an experimental multivariable system also are described.     

Polynomial Design of Optimal Sampled-Data Tracking Systems: II. Robust Optimization

A direct method for robust sampled-data tracking systems design is presented. The method is based on the use of Laplace transformation in continuous time and polynomial equation theory. A criterion is proposed for robust optimization of sampled-data tracking systems. The structure of the optimal robust controller transfer function is investigated and its order is determined explicitly. The relations between robust and quadratic optimization problems are established. A mixed optimization problem is considered, when the cost function includes the integral quadratic error and a robustness term.     

球形对象族的最优鲁棒镇定

本文对球形对象族系统最优鲁棒镇定问题进行了研究.利用最小范数解方法求解球形对象族的可镇定性半径.可镇定性半径是系统稳定性半径的上界,最优控制器的稳定性半径等于镇定性半径.文中给出球形对象族最优鲁棒控制器的形式,并通过示例具体说明球形对象族最优鲁棒控制器的设计方法.     

一类模糊P I D 控制器的鲁棒优化设计

研究一类模糊 PID控制器的鲁棒设计。以小增益定理分析得到该模糊 PID控制系统稳定性条件。针对参数摄动系统的“最坏点”,用该稳定性条件作为约束 ,采用遗传算法对标称系统的性能进行优化 ,求得优化鲁棒控制器。以倒立摆为例进行鲁棒模糊 PID控制器的设计 ,实验结果表明了该方法的有效性     

BOOK REVIEW

Abstract

For an unknown, unstable linear time invariant (LTI) plant with output disturbances, an effective scheme for finding a stabilizing controller is proposed in terms of successive data-based plant identification and model-based controller design. The identification is performed by using an optimal parameter selection technique, and the controller design is based on a robust controller design technique. The main feature of this scheme is that there is almost no requirement of a priori information about the plant. Extensive simulation studies confirm that the scheme is both reliable and efficient. For illustration, a numerical example is presented.     

The optimal design of a discrete-time controller for a single-input,single-output system with time delays

The design of an optimal controller for a discrete-time single-input, single-output system is well documented in a number of textbooks (e.g. Bryson and Ho 1969). It has been shown by Hem (1969), using a procedure similar to that proposed by Lee (1964), and later by Bryson and Ho. that the optimal controller may be represented by its z-transfer function and therefore may be simply implemented as the ratio of two polynomials in z_?1, thus reducing appreciably the amount of on-line computation. Unfortunately, the method of Lee for the computation of the coefficients of the z-transfer function has been found to break down when the structure of the plant includes a finite time delay which creates a singularity in the plant transition matrix. In this paper it is shown that the existence of the singularity induces an orthogonality in the structure of the optimal controller equations which invalidates the application of Lee's method. An alternative, computationally robust, technique is presented for the computation of the coefficients of the z-transfer function of the optimal controller.     

Robust reliability method for non-fragile guaranteed cost control of parametric uncertain systems

The problem of non-fragile guaranteed cost control of uncertain systems is studied from a new point of view of reliability against uncertainties. An efficient robust reliability method for the analysis and design of non-fragile guaranteed cost controller of parametric uncertain systems is presented systematically. By the method, a robust reliability measure of an uncertain control system satisfying required robust performance can be obtained, and the robustness bounds of uncertain parameters such that the control cost of a system is guaranteed can be provided. The optimal non-fragile guaranteed cost controller obtained in the paper may possess optimal guaranteed cost performance satisfying the precondition that the system is robustly reliable with respect to uncertainties occurring in both the controlled plant and controller gain. The presented formulations are in the framework of linear matrix inequality and thus can be carried out conveniently. The presented method provides an essential basis for the tradeoff between reliability and control cost in controller design of uncertain systems. Two numerical examples are provided to demonstrate the efficiency and feasibility of the presented method. It is shown that the coordination and simultaneous realization of the system performance, control cost, and robust reliability in control design of uncertain systems are significant.     

Parameter space design of robust control systems

Find a state or output feedback with fixed gains such that nice stability (defined by a region in the eigenvalue plane) is robust with respect to large plant parameter variations, sensor failures, and quantization effects in the controller. Keep the required magnitude of control inputs small in this design. A tool for tackling such problems by design in the controller parameter spaceKis introduced. Pole placement is formulated as an affine map from the spacePof characteristic polynomial coefficients to theKspace. This allows determining the regions in theKspace, which place all eigenvalues in the desired region in the eigenvalue plane. Then tradeoffs among a variety of different design specifications can be made inKspace. The use of this tool is illustrated by the design of a crane control system. Several open research problems result from this approach: graphical computer-aided design of robust systems, algebraic robustness conditions, and algorithms for iterative design of robust control systems.