A practical parameter determination strategy based on improved hybrid PSO algorithm for higher-order sliding mode control of air-breathing hypersonic vehicles

A hybrid particle swarm optimization (PSO) algorithm for longitudinal dynamic models of air-breathing hypersonic flight vehicles (HFV) is proposed and applied to determine design parameters for a higher-order sliding model controller (HOSMC) while considering the effects of parameter uncertainty on trajectory tracking control. The input and output linearization of air-breathing HFV longitudinal dynamic models were achieved using the feedback linearization approach. Also, an HOSMC was designed for air-breathing HFV trajectory tracking control, and the design parameters were determined based on stochastic robustness analysis and hybrid PSO algorithm. Simulations revealed that the HOSMC design parameters can be optimized effectively and easily using the parameter determination strategy based on an improved hybrid PSO algorithm. The proposed HOSMC was used to stabilized the trajectory tracking of air-breathing HFV and the controller proposed exhibited great robustness.