Enhanced Fruit Fly Optimization Algorithm Based Backstepping-HOSMC for Integrated Guidance and Control of Hypersonic Gliding Vehicle

In this article, a three-dimensional integrated guidance and control (IGC) scheme is proposed for the hypersonic gliding vehicle (HGV), of which the control parameters are determined by enhanced fruit fly optimization algorithm (EFOA). Based on the dynamic and kinematical models, the IGC mathematical model of HGV is established. The control scheme is achieved using a dual-loop control structure. The backstepping-based guidance law can generate the commands of attack angle, sideslip angle, and bank angle, while the attitude control utilizes high-order sliding mode control to track the desired flight attitude angles. Additionally, the extended state observer is designed to estimate the uncertainties arising from the aerodynamic parameters and model dynamics. To obtain satisfactory control performance, the EFOA is introduced to search for optimal control parameters, which divides the whole fruit fly swarm into two subgroups, and introduces the chaotic mapping mechanism as well as the exponential decay search strategy to improve the ability of overall searching and local optimum jumping. The effectiveness and robustness of the proposed EFOA and IGC scheme are, respectively, verified through comparative experiments under different scenarios and Monte Carlo simulations.