Application of Grey Wolf Optimization Algorithm in Tuning Controller Parameters of Hypersonic Vehicle

There are many adjustable parameters in the control method of predictive sliding mode control(PSMC) law and linear extended state observer(LESO) for hypersonic vehicle speed and altitude, and the adjustable parameters influence each other on the control effect, and the speed and altitude channels of the aircraft are coupled with each other, so the controller parameters cannot be independently tuned. A method of automatically tuning controller parameters by using grey wolf optimization (GWO) algorithm is proposed. Firstly, the fitness function containing the desired control effect is designed, and then the appropriate number of search agent and iteration times are selected. The simulation results show that the control effect of the controller with GWO tuning parameters is obviously better than that of the controller with experience tuning parameters, and the expected control effect can be achieved under the condition of adding parameter deviation and actuator limitation.