Genetic Simulation Tool for the Robustness Optimization of Controllers

Abstract

When designing controllers for complex systems, it is not only necessary to stabilize the system but to improve the robustness in order to get a better response. Some indexes allow to measure this robustness of the system response, such as the gain and phase margins. In this paper a computational tool that implements a Multi-Objective Genetic Algorithm (MOGA) is designed and applied to optimize the robustness of different controllers. So, it is possible to analyse how the variation of the controller parameters influences the robustness of the system. The tool is applied to the optimization of a Linear Quadratic (LQ) and Eigenvalues assignment (EA) controllers for a MIMO autonomous vehicle, a helicopter, with satisfactory results.