Numerical Solution of Optimal Control Problems with Discrete-Valued System Parameters

In this paper, we propose a new approach to solve a class of optimal control problems involving discrete-valued system parameters. The basic idea is to formulate a problem of this type as a combination of a discrete global optimization problem and a standard optimal control problem, and then solve it using a two-level approach. Numerical results show that the proposed method is efficient and capable of finding optimal or near optimal solutions.     

Dynamic Sampling Applied to Problems in Optimal Control

Dynamic sampling utilizes the option of varying the sampling rates according to the situation of the systems, thus obtaining procedures with improved efficiencies. In this paper, the technique is applied to a typical problem in optimal control theory, that of tracking and controlling the position of an object. It is shown that the dynamic sampling results in a significantly improved procedure for this case, even when applying a suboptimal policy which can be analyzed in closed form.     

Real-Time Solution of Bi-Level Optimal Control Problems

Bi-level optimal control problems are presented as an extension to classical optimal control problems. Hereby, additional constraints for the primary problem are considered, which depend on the optimal solution of a secondary optimal control problem. A demanding problem is the numerical complexity, since at any point in time the solution of the optimal control problem as well as a complete solution of the secondary problem have to be determined. Hence we deal with two dependent variables in time. The numerical solution of the bi-level problem is illustrated by an application of a container crane. Jerk and energy optimal trajectories with free final time are calculated under the terminal condition that the crane system comes to be at rest at a predefined location. In enlargement additional constraints are investigated to ensure that the crane system can be brought to a rest position by a safety stop at a free but admissible location in minimal time from any state of the trajectory. (© 2005 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Conditions and Algorithm for Optimal Solution of Probabilistic Constrained Programming

1.IntroductionAsweknow,theerroralwaysexistsinmeasurementanditisnormallydistributed,soweconsideraprobabilisticconstrainedprogrammingasbelow:WhereAeRTxnisastochaJsticmatrix,A1)A2,...,A.aretherowsofAandeachAinormallydistributedwithmeanmiandcovariancematrixDi,BER"x"isdeterministicmatrix,xisann-dimensionaldecisionvariable,b,c,daredeterministicvectorsofdimensionrtnfmrespectively,pisconstantreliabilitylevel,1相似文献   

Sufficiency for Optimal Control Problems Involving Parameters

The optimal control problem is extended to the case where the performance index, the differential constraints, and the prescribed final conditions contain parameters. The sufficient condition for a minimum is derived for nonsingular problems using the sweep method. As expected, it involves the finiteness of a matrix or the location of the conjugate point. The minimum-time navigation problem is solved as a fixed final time problem to illustrate the application of the theory.     

Solution Extensions: Optimal Parameter Method in Optimal Control Problems

Using the extension of solution by the optimal parameter method, we obtain a numerical solution for a certain class of optimal control problems.     

判别分析参量的优化选择及其应用

针对复杂地球物理数据集合,应用判别分析技术构建不同集合体识别函数时,需要优选出能敏感反映各类集合体特征的测量参量.声波、电阻率、自然伽马等地球物理测井项目对于岩层中的油、水性质反映能力各不相同,以卫星油田葡萄花油藏的20个油层、10个油水同层、15个水层为研究对象,依据构建集合内参量均匀度参数及集合间距离参数,优选出识别3类岩层的敏感测量项目,并依据这些参量建立贝叶斯判别函数,相对于所有测量参量均参与计算的情况,方法识别精度提高了9.7%.     

Variational Calculus and Approximate Solution of Optimal Control Problems

Variational calculus is a differential process whereby Taylor series expansions can be developed on a term-by-term basis. Therefore, it can be used to obtain the equations which must be solved for the various-order terms arising from the application of regular perturbation theory to problems involving a small parameter. Variational calculus is summarized and applied to the approximate analytical solution of the optimal control problem. First, the various-order equations are obtained directly for a particular problem. Then, assuming that the zeroth-order solution is almost good enough, the equations for the first-order correction are obtained for the general optimal control problem and applied to the particular problem. The first-order solution is the same as the neighboring extremal for the given value of the parameter.     

一类随机最优控制问题的单调控制解

讨论了一类可允许控制策略满足单调非降条件的随机最优控制问题,给出了值函数v(t,x,y,)满足一类受梯度限制的Hamilton-Jacobi-Bellman(HJB)方程:max{Lv(t,x,y), v(t,x,y)/ y}=0,其中Lv(t,x,y)= v/ t b(t,x,y,) v/ x 1/2σ2(t,x,y) 2v/ x2 f(t,x,y).借助粘性解的思想,定义了该类HJB方程的粘性解并在此意义下证明了v(t,x,y)是唯一粘性解,这类方程在随机控制,金融数学等领域内有重要应用.     

An Adaptive Newton Algorithm for Optimal Control Problems with Application to Optimal Electrode Design

In this work, we present an adaptive Newton-type method to solve nonlinear constrained optimization problems, in which the constraint is a system of partial differential equations discretized by the finite element method. The adaptive strategy is based on a goal-oriented a posteriori error estimation for the discretization and for the iteration error. The iteration error stems from an inexact solution of the nonlinear system of first-order optimality conditions by the Newton-type method. This strategy allows one to balance the two errors and to derive effective stopping criteria for the Newton iterations. The algorithm proceeds with the search of the optimal point on coarse grids, which are refined only if the discretization error becomes dominant. Using computable error indicators, the mesh is refined locally leading to a highly efficient solution process. The performance of the algorithm is shown with several examples and in particular with an application in the neurosciences: the optimal electrode design for the study of neuronal networks.     

Solution of a Certain Class of Problems of Optimal Control Theory in Domains of an Arbitrary Form

To solve optimal control problems for elliptic systems in domains that have an arbitrary form, we use a combination of the method of dummy domains and the grid method. We show that the proposed difference scheme has precision of order O(h ^1/2) with respect to the grid norm of W₂ ².     

动态投入产出最优控制模型

本文建立了一个新的具有上下限约束的投入产出问题的最优控制模型 ,并把最优控制问题转化为动态规划问题 ,利用动态最优化的方法给出了该问题的求解方法     

Asymptotic Solution of a Boundary-Value Problem for Linear Singularly-Perturbed Functional Differential Equations Arising in Optimal Control Theory

The Hamiltonian boundary-value problem, associated with a singularly-perturbed linear-quadratic optimal control problem with delay in the state variables, is considered. A formal asymptotic solution of this boundary-value problem is constructed by application of the boundary function method. The justification of this asymptotic solution is done. The asymptotic solution of the Hamiltonian boundary-value problem is constructed and justified assuming boundary-layer stabilizability and detectability.