Genetic algorithm application to controller optimization problems with non-analytic solutions

Linear feedback designed problems were previously solved using modern optimal control theory not capable of accommodating desired system performance constraints, thereby providing undesirable results. Hence, genetic algorithms (GA\u27s) that offer a numerical search method that does not require a statement of the mathematical relationship between the performance criteria and the parameter update have been considered as a better alternative. The present study demonstrates that GA\u27s provide a method of optimizing control system problems with analytically intractable constraints