Robust Output Tracking Control of an Uncertain Linear System via a Modified Optimal Linear-Quadratic Method

This study investigates the robust output tracking problem for a class of uncertain linear systems. The uncertainties are assumed to be time invariant and to satisfy the matching conditions. According to the selected nominal parameters, an optimal solution with a prescribed degree of stability is determined. Then, an auxiliary input via the use of an adapting factor, connected to the nominal optimal control, is introduced to guarantee the robustness and prescribed degree of stability for the output tracking control of the uncertain linear systems. This method is very simple and effective and can reject bounded uncertainties imposed on the states. A maglev vehicle model example is given to show its effectiveness.     

Hilbert空间线性二次最优控制问题中的一个算子的可逆性

对于如下出现在Hilbert空间线性二次最优控制问题中的线性算子■其中F_3,F_5是自伴算子．本文得到了它具有有界逆的充分必要条件,并举例验证了结果的有效性．     

Semi-Infinite Programming Approach to Continuously-Constrained Linear-Quadratic Optimal Control Problems

Consider the class of linear-quadratic (LQ) optimal control problems with continuous linear state constraints, that is, constraints imposed on every instant of the time horizon. This class of problems is known to be difficult to solve numerically. In this paper, a computational method based on a semi-infinite programming approach is given. The LQ optimal control problem is formulated as a positive-quadratic infinite programming problem. This can be done by considering the control as the decision variable, while taking the state as a function of the control. After parametrizing the decision variable, an approximate quadratic semi-infinite programming problem is obtained. It is shown that, as we refine the parametrization, the solution sequence of the approximate problems converges to the solution of the infinite programming problem (hence, to the solution of the original optimal control problem). Numerically, the semi-infinite programming problems obtained above can be solved efficiently using an algorithm based on a dual parametrization method.     

伊藤-泊松型随机微分方程的线性二次控制

本文研究伊藤-泊松型随机微分方程的线性二次控制问题,利用动态规划方法、伊藤公式等技巧,通过解HJB方程,我们得到了随机Riccati方程及另外两个微分方程,求出控制变量,解决了线性二次最优控制最优问题.     

Optimal Control of Linear Time-Varying Systems via Haar Wavelets

This paper introduces the application of Haar wavelets to the optimal control synthesis for linear time-varying systems. Based upon some useful properties of Haar wavelets, a special product matrix, a related coefficient matrix, and an operational matrix of backward integration are proposed to solve the adjoint equation of optimization. The results obtained by the proposed Haar approach are almost the same as those obtained by the conventional Riccati method.     

由发展算子确定的具有控制不等式约束的LQCP的最优反馈控制

研究由发展算子定义的具有控制函数积分不等式约束的线性二次控制问题（LQCP）,借助无约束线性二次控制系统推导出了最优控制的反馈形式。     

Control problems with random and progressively known targets

The situation considered is of optimally controlling a deterministic system from a given state to an initially unknown targety in a fixed time interval [T ₀,T]. The target will be certainly known at a random time in [T ₀,T]. The controller knows the distributions ofy and . We derive the Bellman equation for the problem, prove a verification theorem for it, and demonstrate how the distribution influences the optimal control. We show that, in the linear-quadratic case, the optimal control is given by a feedback law that does not depend on the distribution of .The author wishes to express his gratitude to Prof. Wendell H. Fleming and Prof. Steven Orey for fruitful discussion concerning this work.This research was supported in part by the Institute for Mathematics and Its Applications with funds provided by the National Science Foundation.     

Revisit of Linear-Quadratic Optimal Control

The classical finite-dimensional linear-quadratic optimal control problem is revisited. A new linear-quadratic control problem with linear state penalty terms but without quadratic state penalty terms, is introduced. An optimal control exists and the closed-form optimal solution is given. It is remarkable that feedback action plays no role and state information does not feature in the optimal control. The optimal cost function, rather than being quadratic, is linear in the initial state.     

广义时变系统的鲁棒容错控制

针对广义时变系统的鲁棒容错控制问题,基于矩阵不等式及建立Lyapunov方程的方法,首先,在系统出现执行器故障的情况下,分别给出了两种广义时变系统模型鲁棒镇定的充要条件.接着,在系统出现外部干扰的情况下,给出了相应模型鲁棒镇定的充分条件,同时给出了相应的容错控制器的设计方法.     

State Analysis and Optimal Control of Time-Varying Discrete Systems via Haar Wavelets

The state analysis and optimal control of time-varying discrete systems via Haar wavelets are the main tasks of this paper. First, we introduce the definition of discrete Haar wavelets. Then, a comparison between Haar wavelets and other orthogonal functions is given. Based upon some useful properties of the Haar wavelets, a special product matrix and a related coefficient matrix are proposed; also, a shift matrix and a summation matrix are derived. These matrices are very effective in solving our problems. The local property of the Haar wavelets is applied to shorten the calculation procedures.     

Robust Equilibria in Indefinite Linear-Quadratic Differential Games

Equilibria in dynamic games are formulated often under the assumption that the players have full knowledge of the dynamics to which they are subject. Here, we formulate equilibria in which players are looking for robustness and take model uncertainty explicitly into account in their decisions. Specifically, we consider feedback Nash equilibria in indefinite linear-quadratic differential games on an infinite time horizon. Model uncertainty is represented by a malevolent input which is subject to a cost penalty or to a direct bound. We derive conditions for the existence of robust equilibria in terms of solutions of sets of algebraic Riccati equations.     

具有终端不等式约束的线性二次控制问题

本文研究具有终端不等式约束的线性二次控制问题,得到了最优控制的反馈形式.所得到的反馈形式与相应的无约束问题的Riccati微分方程和一个函数矩阵的线性方程的解有关.     

Suboptimal Control of Time-Varying Neutral Control Systems

In this paper,the optimal control of time-varying neutral control systems is investigated by means of the Maxmium Principle of time-delay systems.optimal control law is given. Then sub-optimal control of time-varying neutral control systems is studied by using sensitivity approach. Algorithm for suboptimal control is given.     

一类不确定时变时滞系统的鲁棒自适应稳定控制

研究了一类不确定时变时滞系统的鲁棒自适应稳定控制问题.系统包含多变时滞非线性扰动.基于Lyapunov稳定性理论和Lyapunov-K rasovsk ii型泛函设计出了一种无记忆的自适应状态反馈控制器,并证明了满足一定条件时,此控制器使得闭环系统最终一致有界.     

线性时变系统二次最优控制问题的保辛近似求解

状态空间的最优控制体系是保守的,其近似算法应当保辛．提出了基于分段常值精细积分方法的保辛摄动近似方法,在同一框架下求解了线性时变LQ最优控制中的计算问题,即变系数矩阵Riccati方程和状态反馈方程．该算法是保辛的,具有很好的数值稳定性和精度．算例验证了算法的有效性．     

Remarks on bang-bang control in a Hilbert space

The control of a linear system, whose performance index is the sum of a linear term and a quadratic term, is considered. A necessary and sufficient condition is given for the optimal control to be bang-bang, and this is used to extend and clarify the results of Refs. 1–2. As an illustration, an application to an elliptic boundary-value problem is given.This research was supported by the SFB 72 of the DFG, West Germany.     

A Variational Discretization Concept in Control Constrained Optimization: The Linear-Quadratic Case

A new discretization concept for optimal control problems with control constraints is introduced which utilizes for the discretization of the control variable the relation between adjoint state and control. Its key feature is not to discretize the space of admissible controls but to implicitly utilize the first order optimality conditions and the discretization of the state and adjoint equations for the discretization of the control. For discrete controls obtained in this way an optimal error estimate is proved. The application to control of elliptic equations is discussed. Finally it is shown that the new concept is numerically implementable with only slight increase in program management. A numerical test confirms the theoretical investigations.     

Control of linear processes with distributed lags using dynamic programming from first principles

A simple dynamic programming argument is presented for the quadratic-cost controller synthesis problem for discrete-time linear processes with delay. Distributed delays are allowed in both state and control. The solution obtained has a discrete-time Riccati difference structure closely analogous to the Riccati differential structure associated with delay problems in continuous time. Extensions are provided for the cases of varying lag-limits, performance criterion dependent on past variables, and the time-invariant regulator problem. A feedback solution is also obtained for a continuous-time problem with distributed delays in the control, by passage to limit from the discrete results.This work was supported by the Operations Research Center, University of California, Berkeley, California, under NSF Grant No. GP-30961X2. The author would like to thank Professor S. E. Dreyfus for guidance and helpful suggestions.     

Turnpike Properties for Stochastic Linear-Quadratic Optimal Control Problems*

This paper analyzes the limiting behavior of stochastic linear-quadratic optimal control problems in finite time-horizon [0, T ] as T → ∞. The so-called turnpike properties are established for such problems, under stabilizability condition which is weaker than the controllability, normally imposed in the similar problem for ordinary differential systems.In dealing with the turnpike problem, a crucial issue is to determine the corresponding static optimization problem. Intuitively mimicking the deterministic situations, it seems to be natural to include both the drift and the diffusion expressions of the state equation to be zero as constraints in the static optimization problem. However, this would lead us to a wrong direction. It is found that the correct static problem should contain the diffusion as a part of the objective function, which reveals a deep feature of the stochastic turnpike problem.     

Optimal feedback control laws using nonlinear programming

A procedure of parametrizing feedback controls when solving the optimal control problem using nonlinear programming is considered. The maximum principle is utilized to determine the forms of the parametrized feedback control. Applications are demonstrated by numerical examples.