Necessary conditions for optimality of singular controls in systems governed by partial differential equations

In this paper, we present a method to obtain necessary conditions for optimality of singular controls in systems governed by partial differential equations (distributed-parameter systems). The method is based on the one developed earlier by the author for singular control problems described by ordinary differential equations. As applications, we consider conditions for optimality of singular controls in a Darboux-Goursat system and in control systems that describe chemical processes.This research was supported in part by the National Science Foundation under Grant No. NSF-MCS-80-02337 at the University of Michigan.The author wishes to express his deep gratitude to Professor L. Cesari for his valuable guidance and constant encouragement during the preparation of this paper.     

Necessary conditions for optimality of singular controls

The present paper is concerned with the study of controls which are singular in the sense of the maximum principle. We obtain necessary conditions for optimality of singular controls in systems governed by ordinary differential equations. A useful feature of the method considered here is that it can be applied to optimal control problems with distributed parameters.this research was supported in part by the National Science Foundation under Grant No. NSF-MCS-80-02337 at the University of Michigan.The author wishes to express his deep gratitude to Professor L. Cesari for his valuable guidance and constant encouragement during the preparation of this paper.     

Approximation of nonlinear functional differential equation control systems

We develop a general approximation framework for use in optimal control problems governed by nonlinear functional differential equations. Our approach entails only the use of linear semigroup approximation results, while the nonlinearities are treated as perturbations of a linear system. Numerical results are presented for several simple nonlinear optimal control problem examples.This research was supported in part by the US Air Force under Contract No. AF-AFOSR-76-3092 and in part by the National Science Foundation under Grant No. NSF-GP-28931x3.     

On the relative leadership property of Stackelberg strategies

The relative leadership property of Stackelberg strategies has been investigated via a scalar nonzero-sum, two-person differential game problem. It is shown that, depending on the parameters of the game, there exist three different types of solutions for his class of games.This work was partially supported by the National Science Foundation, Grant No. GK-31511, and the U.S. Office of Naval Research under the Joint Services Electronics Program, Contract No. N00014-67-A-0298-0006. The author would like to thank Professor Y. C. Ho for several valuable discussions.     

A second-order method for the general nonlinear programming problem

This paper presents a multiplier-type method for nonlinear programming problems with both equality and inequality constraints. Slack variables are used for the inequalities. The penalty coefficient is adjusted automatically, and the method converges quadratically to points satisfying second-order conditions.The work of the first author was supported by NSF RANN and JSEP Contract No. F44620-71-C-0087; the work of the second author was supported by the National Science Foundation Grant No. ENG73-08214A01 and US Army Research Office Durham Contract No. DAHC04-73-C-0025.     

SomeL 1 existence and dependence results for semilinear elliptic equations under nonlinear boundary conditions

In this paper we study questions of existence, uniqueness, and continuous dependence for semilinear elliptic equations with nonlinear boundary conditions. In particular, we obtain results concerning the continuous dependence of the solutions on the nonlinearities in the problem, which in turn implies analogous results for a related parabolic problem. Such questions arise naturally in the study of potential theory, flow through porous media, and obstacle problems.Sponsored by the United States Army under Contract Nos. DAAG29-80-C-0041 and DAAL03-87-K-0043, and by the Air Force Office of Scientific Research under Contract No. AFOSR 84-0252 and by the National Science Foundation under Grant No. DMS-8505531. Research of the third author was carried out in part while visiting the Institute for Mathematics and Its Applications at the University of Minnesota.     

A note on exploiting structure when using slack variables

We show how to exploit the structure inherent in the linear algebra for constrained nonlinear optimization problems when inequality constraints have been converted to equations by adding slack variables and the problem is solved using an augmented Lagrangian method.This research was supported in part by the Advanced Research Projects Agency of the Department of Defense and was monitored by the Air Force Office of Scientific Research under Contract No F49620-91-C-0079. The United States Goverment is authorized to reproduce and distribute reprints for governmental purposes notwithstanding any copyright notation hereon.Corresponding author.     

On iterative methods for solving nonlinear least squares problems over convex sets

Nonlinear least squares problems over convex sets inR ⁿ are treated here by iterative methods which extend the classical Newton, gradient and steepest descent methods and the methods studied recently by Pereyra and the author. Applications are given to nonlinear least squares problems under linear constraint, and to linear and nonlinear inequalities. Part of the research underlying this report was undertaken for the Office of Naval Research, Contract Nonr-1228(10), Project NR047-021, and for the U.S. Army Research Office — Durham, Contract No. DA-31-124-ARO-D-322 at Northwestern University. Reproduction of this paper in whole or in part is permitted for any purpose of the United States Government.     

An interior point potential reduction method for constrained equations

We study the problem of solving a constrained system of nonlinear equations by a combination of the classical damped Newton method for (unconstrained) smooth equations and the recent interior point potential reduction methods for linear programs, linear and nonlinear complementarity problems. In general, constrained equations provide a unified formulation for many mathematical programming problems, including complementarity problems of various kinds and the Karush-Kuhn-Tucker systems of variational inequalities and nonlinear programs. Combining ideas from the damped Newton and interior point methods, we present an iterative algorithm for solving a constrained system of equations and investigate its convergence properties. Specialization of the algorithm and its convergence analysis to complementarity problems of various kinds and the Karush-Kuhn-Tucker systems of variational inequalities are discussed in detail. We also report the computational results of the implementation of the algorithm for solving several classes of convex programs. The work of this author was based on research supported by the National Science Foundation under grants DDM-9104078 and CCR-9213739 and the Office of Naval Research under grant N00014-93-1-0228. The work of this author was based on research supported by the National Science Foundation under grant DMI-9496178 and the Office of Naval Research under grants N00014-93-1-0234 and N00014-94-1-0340.     

Application of viscosity solutions of infinite-dimensional Hamilton-Jacobi-Bellman equations to some problems in distributed optimal control

We apply the recently developed Crandall and Lions theory of viscosity solutions for infinite-dimensional Hamilton-Jacobi equations to two problems in distributed control. The first problem is governed by differential-difference equations as dynamics, and the second problem is governed by a nonlinear divergence form parabolic equation. We prove a Pontryagin maximum principle in each case by deriving the Bellman equation and using the fact that the value function is a viscosity supersolution.This work was supported by the Air Force Office for Scientific Research, Grant No. AFOSR-86-0202. The author would like to thank R. Jensen for several helpful conversations regarding the problems discussed here. He would also like to thank M. Crandall for providing early preprints of his work in progress with P. L. Lions on infinite-dimensional problems.     

On conforming finite element methods for the inhomogeneous stationary Navier-Stokes equations

Summary We consider the stationary Navier-Stokes equations, written in terms of the primitive variables, in the case where both the partial differential equations and boundary conditions are inhomogeneous. Under certain conditions on the data, the existence and uniqueness of the solution of a weak formulation of the equations can be guaranteed. A conforming finite element method is presented and optimal estimates for the error of the approximate solution are proved. In addition, the convergence properties of iterative methods for the solution of the discrete nonlinear algebraic systems resulting from the finite element algorithm are given. Numerical examples, using an efficient choice of finite element spaces, are also provided.Supported, in part, by the U.S. Air Force Office of Scientific Research under Grant No. AF-AFOSR-80-0083Supported, in part, by the same agency under Grant No. AF-AFOSR-80-0176-A. Both authors were also partially supported by NASA Contract No. NAS1-15810 while they were in residence at the Institute for Computer Applications in Science and Engineering, NASA Langley Research Center, Hampton, VA 23665, USA     

On the solution of large,structured linear complementarity problems: The block partitioned case

This paper delineates the underlying theory of an efficient method for solving a class of specially-structured linear complementarity problems of potentially very large size. We propose a block-iterative method in which the subproblems are linear complementarity problems. Problems of the type considered here arise in the process of making discrete approximations to differential equations in the presence of special side conditions. This problem source is exemplified by the free boundary problem for finite-length journal bearings. Some of the authors' computational experience with the method is presented.Research partially supported by the Office of Naval Research under contract N-00014-67-A-0112-0011; U.S. Atomic Energy Commission Contract AT (04-3)-326 PA No. 18.Research partially supported by U.S. Atomic Energy Commission Contract AT(04-3)-326 PA No. 30; and National Science Foundation Grant GJ 35135X.     

A note on duality in disjunctive programming

We state a duality theorem for disjunctive programming, which generalizes to this class of problems the corresponding result for linear programming.This work was supported by the National Science Foundation under Grant No. MPS73-08534 A02 and by the US Office of Naval Research under Contract No. N00014-75-C-0621-NR047-048.     

A note on a sufficient-decrease criterion for a non-derivative step-length procedure

A step-length algorithm is an essential part of many descent methods for unconstrained and constrained optimization. In this note we present a criterion that defines an acceptable step length when only function values are available at trial step lengths.This research was supported by the U.S. Department of Energy Contract DE-AC03-76SF00326, PA No. DE-AT03-76ER72018; National Science Foundation Grants MCS-7926009 and ECS-8012974; the Office of Naval Research Contract N00014-75-C-0267; and the U.S. Army Research Office Contract DAAG29-79-C-0110.     

Optimal control of infinite-dimensional uncertain systems

In this paper, we consider a minimax problem of optimal control for a class of strongly nonlinear uncertain evolution equations on a Banach space. We prove the existence of optimal controls. A nontrivial example of a class of systems governed by a nonlinear partial differential equation with uncertain spatial parameters is presented for illustration.This work was supported in part by the National Science and Engineering Research Council of Canada under Grant No. A7109 and The Engineering Faculty Development Fund, University of Ottawa.The authors would like to thank the anonymous reviewers for their valuable comments and suggestions.     

Local convergence of interior-point algorithms for degenerate monotone LCP

Most asymptotic convergence analysis of interior-point algorithms for monotone linear complementarity problems assumes that the problem is nondegenerate, that is, the solution set contains a strictly complementary solution. We investigate the behavior of these algorithms when this assumption is removed.The work of this author was based on research supported by the National Science Foundation under grant DDM-9109404 and the Office of Naval Research under grant N00014-93-1-0234.The work of this author was based on research supported by the Office of Scientific Computing, U.S. Department of Energy, under Contract W-31-109-Eng-38.     

Reflection principles for linear elliptic second order partial differential equations with constant coefflcients

Summary Reflection principles, analogous to the classicalSchwarz reflection principle for harmonic functions, are obtained for solutions of linear elliptic second order partial differential equations with constant coefficients. The boundary conditions employed are supposed to be satisfied in a limiting sense only, and do not require (a priori) the existence of derivatives on the boundary. To Mauro Picone on his 70^th birth day. This research was supported in part by the United States Air Force under Contract N^o. AF(600)-573 — monitored by the Office of Scientific Research, Air Research and Development Command. The work of this author was sponsored by the Office of Ordnance Research, U.S. Army, under the Contract DA-36-034-ORD-1486.     

Adaptive control of discounted Markov decision chains

In this paper, we consider discounted-reward finite-state Markov decision processes which depend on unknown parameters. An adaptive policy inspired by the nonstationary value iteration scheme of Federgruen and Schweitzer (Ref. 1) is proposed. This policy is briefly compared with the principle of estimation and control recently obtained by Schäl (Ref. 4).This research was supported in part by the Consejo Nacional de Ciencia y Tecnología under Grant No. PCCBBNA-005008, in part by a grant from the IBM Corporation, in part by the Air Force Office of Scientific Research under Grant No. AFOSR-79-0025, in part by the National Science Foundation under Grant No. ECS-0822033, and in part by the Joint Services Electronics Program under Contract No. F49620-77-C-0101.     

Critical point theorems for indefinite functionals

A variational principle of a minimax nature is developed and used to prove the existence of critical points for certain variational problems which are indefinite. The proofs are carried out directly in an infinite dimensional Hilbert space. Special cases of these problems previously had been tractable only by an elaborate finite dimensional approximation procedure. The main applications given here are to Hamiltonian systems of ordinary differential equations where the existence of time periodic solutions is established for several classes of Hamiltonians.Supported in part by the U.S. Army under Contract No. DAAG-29-75-C-0024 and by the Conseglio Nazionale delle Ricerche-Gruppo Nazionale Analisi Funzionale e ApplicazioneSupported in part by the J.S. Guggenheim Memorial Foundation, and by the Office of Naval Research under Contract No. N00014-76-C-0300. Reproduction in whole or in part is permitted for any purpose of the U.S. Government     

Tensor-Krylov methods for large nonlinear equations

In this paper, we describe tensor methods for large systems of nonlinear equations based on Krylov subspace techniques for approximately solving the linear systems that are required in each tensor iteration. We refer to a method in this class as a tensor-Krylov algorithm. We describe comparative testing for a tensor-Krylov implementation versus an analogous implementation based on a Newton-Krylov method. The test results show that tensor-Krylov methods are much more efficient and robust than Newton-Krylov methods on hard nonlinear equations problems.Part of this work was performed while the author was research associate at CERFACS (Centre Européen de Recherche et de Formation Avancée en Calcul Scientifique).Research supported in part by the Office of Scientific Computing, U.S. Department of Energy, under Contract W-31-109-Eng-38.