Robust genetic algorithm approach to modelling and control

The paper deals with robust intelligent control of linear dynamical systems using algebraic polynomial theory in combination with the genetic algorithms (GA). It shows that the conventional robust polynomial synthesis approach can be successfully modified so as to improve performance by applying genetic algorithms for tuning controller parameters. A general algorithm has been developed for optimal polynomial controller tuning that enables to generate optimal and robust control actions for both SISO and MIMO systems. Moreover, the proposed methodology guarantees finding global optimum and enables achieving a higher performance compared with the conventional approaches. The proposed robust intelligent algorithm involving the intelligent searching procedure has been tested on a case study (control of a servo system with a changing momentum of inertia). Obtained results verify the possibility to improve the performance using combination of a polynomial algebraic controller and a genetic algorithm.