非线性最优控制的反馈逼近

本文将在线性最优控制中经典的Ｋｌｅｉｎｍａｎ－Ｎｅｗｔｏｎ［１］方法推广到非线性的最优控制问题。我们证明,由一个稳定反馈控制生成的反馈控制序列在原点附近会一致逼近最优控制,并指出这一研究在Ｈ∞－非线性最优控制中的作用。     

Nonsmooth and discontinuous speed-gradient algorithms

In this article, nonsmooth extensions of the Speed-Gradient (SG) algorithms in differential and finite forms are proposed. The conditions ensuring achievement of the control goal (convergence of the goal function to zero) are established. Furthermore, conditions under which the control goal is achieved in finite time with the use of nonsmooth or discontinuous SG algorithms are obtained. Theoretical results are illustrated by example of nonsmooth energy-based control for a non-affine in control pendulum-like system.     

Weak lower semicontinuity of integral functionals

A lower semicontinuity theorem for integral functionals is proved underL ₁-strong convergence of the trajectories andL ₁-weak convergence of the control functions. An alternative statement is also proved under pointwise convergence of the trajectories.     

Superlinear Convergence of the GMRES for PDE-Constrained Optimization Problems

Optimal control problems for PDEs arise in many important applications. A main step in the solution process is the solution of the arising linear system, where the crucial point is usually finding a proper preconditioner. We propose both proper block diagonal and more involved preconditioners, and derive mesh independent superlinear convergence of the preconditioned GMRES iterations based on a compact perturbation property of the underlying operators.     

Homogenization of periodic optimal control problems via multi-scale convergence

The aim of this paper is to provide an alternate treatment of the homogenization of an optimal control problem in the framework of two-scale (multi-scale) convergence in the periodic case. The main advantage of this method is that we are able to show the convergence of cost functionals directly without going through the adjoint equation. We use a corrector result for the solution of the state equation to achieve this.     

Constrained LQR problems in elliptic distributed control systems with point observations—convergence results

In this paper constrained LQR problems in distributed control systems governed by the elliptic equation with point observations are studied. A variational inequality approach coupled with potential theory in a Banach space setting is adopted. First the admissible control set is extended to be bounded by two functions, and feedback characterization of the optimal control in terms of the optimal state is derived; then two numerical algorithms proposed in [5] are modified, and the strong convergence and uniform convergence in Banach space are proved. This verifies that the numerical algorithm is insensitive to the partition number of the boundary. Since our control variables are truncated below and above by two functions inL ^p and in our numerical computation only the layer density not the control variable is assumed to be piecewise smooth, uniform convergence guarantees a better convergence. Finally numerical computation for an example is carried out and confirms the analysis. This research was supported in part by NSF Grant DMS-9404380 and by an IRI Award of Texas A&M University. The current address of the first author is the Department of Mathematical Science, University of Nevada at Las Vegas, Las Vegas, NV 89154, USA.     

Homogenization of Optimal Control Problems for Functional Differential Equations

The paper deals with the variational convergence of a sequence of optimal control problems for functional differential state equations with deviating argument. Variational limit problems are found under various conditions of convergence of the input data. It is shown that, upon sufficiently weak assumptions on convergence of the argument deviations, the limit problem can assume a form different from that of the whole sequence. In particular, it can be either an optimal control problem for an integro-differential equation or a purely variational problem. Conditions are found under which the limit problem preserves the form of the original sequence.     

Two Convergence Problems for Monotone Sequences

Eight measures of rate of convergence of monotone sequences of real numbers have been proposed and discussed in a paper by Beyer, Ebanks, and Qualls (Acta Appl. Math. 20 (1990), 267–284). These rates arose in discussions of dynamical systems. In the comparisons of these rates, two problems remained. A complete answer is given to one of the problems and a partial answer is given to the other problem.     

非线性互补问题的SQP方法

In this paper, the nonlinear complementarity problem is transformed into the least squares problem with nonnegative constraints ,and a SQP algorithm for this reformulation based on a damped Gauss-Newton type method is presented. It is shown that the algorithm is globally and locally superlinearly (quadratically) convergent without the assumption of monotonicity.     

一类连续最优控制问题的有限维近似

1　引　　言本文考虑具有状态终端约束、控制受限的非线性连续最优控制问题min　h0(x(0))+∫T0f0(x(t),u(t))dt+g0(x(T))(1.1)s.t.　x(t)=f(x(t),u(t)),　　t∈[0,T](1.2)D(x(0))=0,(1.3)E(x(T))=0,(1.4)S(u(t))≤0,　　t∈[0,T](1.5)其中,h0:Rn→R,f0:Rn×Rm→R,f:Rn×Rm→Rn,g0:Rn→R,D:Rn→Rp,E:Rn→Rq,S:Rm→Rr均为二次连续可微函数.T为终端时间(固定),p,q≤n,x(t)∈W1,∞[0,T]n,u(t)∈L∞[0,T]m分别为状态函数和控制函数.U(t)={u:S(u(t))≤0}为紧凸集.问题(1.1)—(1.5)要求寻找最佳控制u(t)使得目标函数(1.1)达到极小.…     

Algorithms for Unconstrained Optimization Problems via Control Theory

Existing algorithms for solving unconstrained optimization problems are generally only optimal in the short term. It is desirable to have algorithms which are long-term optimal. To achieve this, the problem of computing the minimum point of an unconstrained function is formulated as a sequence of optimal control problems. Some qualitative results are obtained from the optimal control analysis. These qualitative results are then used to construct a theoretical iterative method and a new continuous-time method for computing the minimum point of a nonlinear unconstrained function. New iterative algorithms which approximate the theoretical iterative method and the proposed continuous-time method are then established. For convergence analysis, it is useful to note that the numerical solution of an unconstrained optimization problem is none other than an inverse Lyapunov function problem. Convergence conditions for the proposed continuous-time method and iterative algorithms are established by using the Lyapunov function theorem.     

Characterisation of compactness through convergence in Tychonoff spaces

In this article we first give a characterisation of compact spaces among spaces by improving a theorem of J. Ewert. Then, with the aid of a new type of convergence, we give a characterisation of the pseudocompact and of the Lindelöf spaces.

     

受控AR模型中参数估计误差的一致有界性分析

本针对系统为受控AR模型，其参数估计采用随机梯度算法时，用鞅收敛定理的推广形式分析了它的收敛性，得到了参数估计误差一致有界的结果．     

Finite-Time Optimal Control of Polynomial Systems Using Successive Suboptimal Approximations

It is shown in this paper that the finite-time optimal control of polynomial systems can be obtained by solving a sequence of optimal control problems for the linearized problem. The paper provides proof of convergence as well as illustration of the procedure by two examples.     

A computational method for a class of optimal relaxed control problems

In the present paper, we propose a computational scheme for solving a class of optimal relaxed control problems, using the concept of control parametrization. Furthermore, some important convergence properties of the proposed computational scheme are investigated. For illustration, a numerical example is also included.     

Further arguments for slice convergence in nonreflexive spaces

It is shown that no notion of set convergence at least as strong as Wijsman convergence but not as strong as slice convergence can be preserved in superspaces. We also show that such intermediate notions of convergence do not always admit representations analogous to those given by Attouch and Beer for slice convergence, and provide a valid reformulation. Some connections between bornologies and the relationships between certain gap convergences for nonconvex sets are also observed.Research supported in part by an NSERC research grant and by the Shrum endowment.NSERC postdoctoral fellow.     

一类时滞非线性系统的采样迭代学习控制

本文针对一类时滞非线性系统提出一种采样迭代学习控制算法,严格证明了该算法的指数收敛性.当系统满足所给出的条件时,跟踪误差以指数速率收敛至一个与采样周期有关的误差范围内.     

A sequential subspace projection method for extreme Z‐eigenvalues of supersymmetric tensors

Z‐eigenvalues of tensors, especially extreme ones, are quite useful and are related to many problems, such as automatic control, quantum physics, and independent component analysis. For supersymmetric tensors, calculating the smallest/largest Z‐eigenvalue is equivalent to solving a global minimization/maximization problem of a homogenous polynomial over the unit sphere. In this paper, we utilize the sequential subspace projection method (SSPM) to find extreme Z‐eigenvalues and the corresponding Z‐eigenvectors. The main idea of SSPM is to form a 2‐dimensional subspace at the current point and then solve the original optimization problem in the subspace. SSPM benefits from the fact that the 2‐dimensional subproblem can be solved by a direct method. Global convergence and linear convergence are established for supersymmetric tensors under certain assumptions. Preliminary numerical results over several testing problems show that SSPM is very promising. Besides, the globalization strategy of random phase can be easily incorporated into SSPM, which promotes the ability to find extreme Z‐eigenvalues. Copyright © 2014 John Wiley & Sons, Ltd.     

A Completion of \mathbb{Z} is a Field

We define various ring sequential convergences on and . We describe their properties and properties of their convergence completions. In particular, we define a convergence on by means of a nonprincipal ultrafilter on the positive prime numbers such that the underlying set of the completion is the ultraproduct of the prime finite fields Further, we show that is sequentially precompact but fails to be strongly sequentially precompact; this solves a problem posed by D. Dikranjan.     

切换系统的自适应广义预测控制

针对一类切换系统研究了含有输出预测误差的自适应广义预测控制问题．切换律由有限个子系统的输出预测误差确定．对于单个子系统和多个子系统两种情况,证明了所提出的广义预测控制直接算法能够保证系统的全局收敛性．该算法克服了传统自适应控制固有的收敛速度慢且暂态误差较大的缺点．