A Discretizing Levenberg-Marquardt Scheme for Solving Nonlinear Ill-Posed Integral Equations

To reduce the computational cost, we propose a regularizing modified Levenberg-Marquardt scheme via multiscale Galerkin method for solving nonlinear ill-posed problems. Convergence results for the regularizing modified Levenberg-Marquardt scheme for the solution of nonlinear ill-posed problems have been proved. Based on these results, we propose a modified heuristic parameter choice rule to terminate the regularizing modified Levenberg-Marquardt scheme. By imposing certain conditions on the noise, we derive optimal convergence rates on the approximate solution under special source conditions. Numerical results are presented to illustrate the performance of the regularizing modified Levenberg-Marquardt scheme under the modified heuristic parameter choice.     

A Multigrid Scheme for Elliptic Constrained Optimal Control Problems

A multigrid scheme for the solution of constrained optimal control problems discretized by finite differences is presented. This scheme is based on a new relaxation procedure that satisfies the given constraints pointwise on the computational grid. In applications, the cases of distributed and boundary control problems with box constraints are considered. The efficient and robust computational performance of the present multigrid scheme allows to investigate bang-bang control problems.AMS Subject Classification: 49J20, 65N06, 65N12, 65N55Supported in part by the SFB 03 “Optimization and Control”     

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.     

Optimal control computation for parabolic systems with boundary conditions involving time delays

In this paper, we consider a class of optimal control problems involving a second-order, linear parabolic partial differential equation with Neumann boundary conditions. The time-delayed arguments are assumed to appear in the boundary conditions. A necessary and sufficient condition for optimality is derived, and an iterative method for solving this optimal control problem is proposed. The convergence property of this iterative method is also investigated.On the basis of a finite-element Galerkin's scheme, we convert the original distributed optimal control problem into a sequence of approximate problems involving only lumped-parameter systems. A computational algorithm is then developed for each of these approximate problems. For illustration, a one-dimensional example is solved.     

A general theorem on error estimates with application to a quasilinear elliptic optimal control problem

A theorem on error estimates for smooth nonlinear programming problems in Banach spaces is proved that can be used to derive optimal error estimates for optimal control problems. This theorem is applied to a class of optimal control problems for quasilinear elliptic equations. The state equation is approximated by a finite element scheme, while different discretization methods are used for the control functions. The distance of locally optimal controls to their discrete approximations is estimated.     

Time optimal control computation with application to ship steering

An efficient computational scheme for solving a general class of linear time optimal control problems, where the target set is a compact and convex set with nonempty interior in the state space, is presented. The scheme is applied to solve the ship steering control problem, and excellent results are obtained.     

Approximation schemes for nonlinear neutral optimal control systems

We discuss methods of approximating stable neutral functional differential equations and associated optimal control problems by sequences of optimal control problems for ordinary differential equations. By introducing a class of “mollified” neutral functional differential equations, convergence of the linear interpolating spline and the averaging approximation scheme is proved. A number of numerical examples are included.     

A FEM-Multigrid Scheme for Elliptic Nash-Equilibrium Multiobjective Optimal Control Problems

A finite-element multigrid scheme for elliptic Nash-equilibrium multiobjective optimal control problems with control constraints is investigated. The multigrid computational framework implements a nonlinear multigrid strategy with collective smoothing for solving the multiobjective optimality system discretized with finite elements. Error estimates for the optimal solution and two-grid local Fourier analysis of the multigrid scheme are presented. Results of numerical experiments are presented to demonstrate the effectiveness of the proposed framework.     

Optimal control computation for nonlinear time-lag systems

In this paper, a computational scheme using the technique of control parameterization is developed for solving a class of optimal control problems involving nonlinear hereditary systems with linear control constraints. Several examples have been solved to test the efficiency of the technique.     

A computational successive improvement scheme for adaptive optimal control processes

To computationally solve an adaptive optimal control problem by means of conventional dynamic programming, a backward recursion must be used with an optimal value and optimal control determined for all conceivable prior information patterns and prior control histories. Consequently, almost all problems are beyond the capability of even large computers.As an alternative, we develop in this paper a computational successive improvement scheme which involves choosing a nominal control policy and then improving it at each iteration. Each improvement involves considerable computation, but much less than the straightforward dynamic programming algorithm. As in any local-improvement procedure, the scheme may converge to something which is inferior to the absolutely optimal control.This paper has been supported by the National Science Foundation under Grant No. GP-25081.     

A limited-feedback approximation scheme for optimal switching problems with execution delays

We consider a type of optimal switching problems with non-uniform execution delays and ramping. Such problems frequently occur in the operation of economical and engineering systems. We first provide a solution to the problem by applying a probabilistic method. The main contribution is, however, a scheme for approximating the optimal control by limiting the information in the state-feedback. In a numerical example the approximation routine gives a considerable computational performance enhancement when compared to a conventional algorithm.     

MPC for the Burgers Equation Based on an LQG Design

We consider optimal control problems for semilinear parabolic PDEs where process and measurement noise can occur. We discuss the solution of such problems by using a Model Predictive Control (MPC) strategy. For the resulting sub-problems we will use a Linear Quadratic Gaussian (LQG) design. Thus we will discuss the efficient implementation of the LQG approach since it is the major computational part in the MPC scheme for this class of optimal control problems. We will present some numerical results for the Burgers equation. (© 2006 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Extremal points and optimal control theory

Summary An optimal control problem is considered in a setting akin to that of the theory. of generalized curves. Rather than minimizing a functional depending on pairs of trajectories and controls subject to some constraints, a functional defined on a set of Radon measures is considered; the set of measures is determined by the constraints. An approximation scheme is developed, so that the solution of the optimal control problems can be effected by solving a sequence of nonlinear programming problems. Several existence theorems for this kind of generalized control problems are then proved; the most interesting is the one concerning problems in which the set of allowable controls is unbounded. Entrata in Redazione il 5 febbraio 1975.     

Analysis and Computational Methods of Dirichlet Boundary Optimal Control Problems for 2D Boussinesq Equations

We study Dirichlet boundary optimal control problems for 2D Boussinesq equations. The existence of the solution of the optimization problem is proved and an optimality system of partial differential equations is derived from which optimal controls and states may be determined. Then, we present some computational methods to get the solution of the optimality system. The iterative algorithms are given explicitly. We also prove the convergence of the gradient algorithm.     

Long-term average control of a continuous,monotone process

We analyze optimal control problems for systems subject to random deterioration and failure. The system is replaced at failure and our objective is to optimize the utilization of the system between failures. The problems are new in that the payoff depends on the running maximum of a diffusion. This provides an intuitively appealing model for naturally monotone phenomena such as wear. The long-term average control problem is reduced to a family of simpler, single-cycle problems, a formula for the invariant measure for the (controlled) process is determined and a computational scheme based on the decomposition and formula is given.     

Optimal control computation for linear time-lag systems with linear terminal constraints

A computational scheme using the technique of control parameterization is developed for solving a class of optimal control problems involving linear hereditary systems with bounded control region and linear terminal constraints. Several examples have been solved to illustrate the efficiency of the technique.The authors wish to thank Dr. B. D. Craven for pointing out an error in an earlier version of this paper.From January 1985, Associate Professor, Department of Industrial and Systems Engineering, National University of Singapore, Kent Ridge, Singapore.     

On a Class of Optimal Control Problems with State Jumps

In this paper, we consider a class of optimal control problems in which the dynamical system involves a finite number of switching times together with a state jump at each of these switching times. The locations of these switching times and a parameter vector representing the state jumps are taken as decision variables. We show that this class of optimal control problems is equivalent to a special class of optimal parameter selection problems. Gradient formulas for the cost functional and the constraint functional are derived. On this basis, a computational algorithm is proposed. For illustration, a numerical example is included.     

Approximate solution of nonlinear problems of optimal control of oscillatory processes using the method of canonical separation of motions : PMM vol.40, n 6, 1976, pp. 1024–1033

An asymptotic method of solving certain problems of optimal control of motion of the standard type systems with rotating phase is developed. It is assumed that the controls enter only the small perturbing terms, and that the fixed time interval over which the process is being considered is long enough to ensure that the slow variables change essentially. Assuming also that the system and the controls satisfy the necessary requirements of smoothness, the method of canonical averaging [1] is used to construct a scheme for deriving a simplified boundary value problem of the maximum principle. The structure of the set of solutions of the boundary value problem is investigated and a scheme for choosing the optimal solution with the given degree of accuracy in the small parameter is worked out. The validity of the approximate method of solving the boundary value problem is proved. The method suggested in [2] for constructing a solution in the first approximation for similar problems of optimal control is developed.     

Solution of optimal control problems by a variational method

An algorithm for numerically solving optimal control problems by methods applied to ill-posed problems is discussed. The stable algorithms for solving such problems on compact sets developed by Academician A.N. Tikhonov in the twentieth century can be applied to problems of optimal control. The special feature of optimal control problems is the discontinuity of a control function. This difficulty is overcome by introducing a moving computational grid. The step size of the grid is determined by solving the speed problem.     

<Emphasis Type="Italic">ε</Emphasis>-Uniform error estimate of hybrid numerical scheme for singularly perturbed parabolic problems with nterior layers

This article is devoted to the study of a hybrid numerical scheme for a class of singularly perturbed parabolic convection-diffusion problems with discontinuous convection coefficients. In general, the solutions of this class of problems possess strong interior layers. To solve these problems, we discretize the time derivative by the backward-Euler method and the spatial derivatives by a hybrid finite difference scheme (a proper combination of the midpoint upwind scheme in the outer regions and the classical central difference scheme in the interior layer regions) on a layer resolving piecewise-uniform Shishkin mesh. It is proved that the method converges uniformly in the discrete supremum norm with almost second-order spatial accuracy. Moreover, an optimal order of convergence (up to a logarithmic factor) is obtained inside the layer regions. Extensive numerical experiments are conducted to support the theoretical results and also, to demonstrate the accuracy of this method.