Robust Suboptimal Control of HiMAT Vehicle Based on Improved Genetic Algorithm

In this work, a robust suboptimal controller for the longitudinal-motion of highly maneuverable technology (HiMAT) vehicle is presented. The controller design is centered around a linearized short period rigid model at a Mach 0.9, altitude 20,000 ft and angle of attack 1.19 deg flight condition. The weighting matrices with respect to the suboptimal control scheme, which are used to synthesize a performance index, are selected by an improved genetic algorithm. In addition, in order to improve the robust performance of HiMAT vehicle, parameter uncertainties are considered in the process of genetic search. The simulation results show that both the system states of the HiMAT vehicle and control inputs are all desirable, and the robust performance is acceptable as well, which demonstrates the effectiveness of the proposed method.