Linear matrix inequalities and evolutionary optimization in multiobjective control
The multiobjective problems of H-2 optimal control (LQG case) and mixed H-2/H-infinity are addressed using two different approaches: Evolutionary Algorithms and Linear Matrix Inequalities (LMIs). This study illustrates with numerical examples how both approaches can be used to find the trade-off between different signal sensitivities to noise and to find the trade-off of the mixed H-2/H-infinity problem. For the mixed H-2/H-infinity example, this paper shows how a Multiobjective Genetic Algorithm (MOGA) could find an improved Pareto-optimal front compared to the LMI approach.
linear matrix inequalities multiobjective control genetic algorithms