Most of the existing parameter estimation methods require much auxiliary information and is not easy to handle for practical applications. In this paper , we use genetic algorithms, which are becoming an important tool for optimization problems, to estimate parameters in nonlinear regression models. The computational experiments indicate that this genetic based method is useful, eeective and ad...

The focus in this report is set on adaptive control systems with practical application. Five different papers and their adaptive control design are presented and evaluated. The introduction gives a small impression why adaptive control systems are essential in most applications. The second part is a theoretical part that introduces some of the basic adaptive control characteristics. In the thir...

In this paper, we study adaptive finite element discretisation schemes for a class of parameter estimation problem. We propose to use adaptive multi-meshes in developing efficient algorithms for the estimation problem. We derive equivalent a posteriori error estimators for both the state and the control approximation, which particularly suit an adaptive multi-mesh finite element scheme. The err...

In this paper, we study adaptive finite element discretisation schemes for a class of parameter estimation problem. We propose to use adaptive multi-meshes in developing efficient algorithms for the estimation problem. We derive equivalent a posteriori error estimators for both the state and the control approximation, which particularly suit an adaptive multi-mesh finite element scheme. The err...