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This article concerns optimal control and stabilization for some Fisher-like models with control acting in a subdomain ω. We investigate the optimal position of ω for some optimal harvesting problems. First, we refer to a logistic model with diffusion. We remember the necessary optimality conditions, and then obtain an iterative method to improve the position of ω for the optimal harvesting effort (for a simplified model without logistic term). Next, we consider the null stabilization for a controlled Fisher model and obtain a descent method to improve the position of ω in order to get a faster stabilization to zero. Numerical tests illustrating the effect of the last method are given. We also studied the null stabilization for a prey-predator system and have reduced it to the study of the null stabilizability for a related Fisher model.

In this article, a new method is proposed for solving symmetric nonlinear equations, which can ensure that the search direction is descent for the norm function without carrying any line search technique. Under mild conditions, the global convergence of the given method is established. Numerical results show that the proposed method is effective for the given test problems.

Global convergence theorems for a class of descent methods for unconstrained optimization problems in normed spaces, using multidirectional search, are proved. Exact and inexact search are considered and the results allow to define a globally convergent algorithm for an unconstrained optimal control problem which operates, at each step, on discrete approximations of the original continuous problem.

The problem of time-continuous meteorological data assimilation is addressed. An optimal control method is proposed and studied for a simple well-posed 2D atmospheric model and continuous in time and space observations. An existence result for the optimal control problem is given. Then the first order necessary conditions of optimality are explicited using a forced version of the linearized adjoint model; allowing the use of a classical descent method to solve the problem. The reliability of the method is shown on some numerical tests. Finally, the existence and characterization results of an optimal control are extended to the case of observations distributed in time.

This paper is concerned with the numerical solution of optimal control problems for which each optimal control is bang-bang. Especially, the results apply to parabolic boundary control Problems. Starting from a sequence of feasible solutions converging to an optimal control u, a sequence of bang-bang controls converging to u is constructed. Bang-bang approximations of u are desirable for certain numerical reasons. Sequences of arbitrary feasible controls converging to u may be obtained by discretization or by a descent method. Numerical examples are also given.