Designing structure-specified mixed H2/H∞ optimal controllers using an intelligent genetic algorithm IGA

This brief proposes an efficient method for designing accurate structure-specified mixed H-2/H-infinity optimal controllers for systems with uncertainties and disturbance using an intelligent genetic algorithm (IGA). The newly-developed IGA with intelligent crossover based on orthogonal experimental design (OED) is efficient for solving intractable engineering problems with lots of design parameters. The IGA-based method without using prior domain knowledge can efficiently solve design problems of multi-input-multi-output (MIMO) optimal control systems, which is very suitable for practical engineering designs. High performance and validity of the proposed method are evaluated by two test problems, a MIMO distillation column model and a MIMO super maneuverable F18/HARV fighter aircraft system. It is shown empirically that the IGA-based method has good tracking performance, robust stability and disturbance attenuation for both controllers, compared with the existing methods.