Improvement Of Pigeon-inspired Optimization Algorithm And Its Application In Hypersonic Flight Control

Due to the distinctive flight characteristics with large Mach number and high altitude,hypersonic vehicles are very valuable for military and civilian application.Hypersonic flight system integrates multidisciplinary advanced technologies and is featured by the complicated multi-disciplinary interaction.Therefore,the integrated optimization design is vital to achieve the optimal flight performance.Based on the novel Pigeon-inspired optimization(PIO)algorithm,this paper investigates the improved strategy of PIO and the relevant application to use the control optimization of the hypersonic vehicle.As a result,a feasible and effective optimization strategy is provided for the integrated optimization design.The main work of this paper is as follows:Firstly,two improved strategies of the PIO algorithm are proposed.First,considering the high population dispersion of quantum evolutionary algorithm(QEA)and fast convergence of PIO,a hybrid algorithm of QEA and PIO is presented to improve the global searching ability of the basic PIO algorithm;After that,another improvement is conducted by introducing the Gaussian mutation into the basic PIO algorithm to maintain the swarm diversity,and the mutation is only triggered when the diversity is below a certain threshold,thus avoiding premature convergence.Finally,the results of the Benchmark functions verify the effectiveness of both improved algorithms.Furthermore,the improved PIO algorithms are applied to flight control system design and trajectory optimization of the hypersonic vehicle.First,the surrogate aerodynamic model based on the waverider configuration is built for mathematical modeling and dynamic analysis.After that,the improved PIO is used for searching the optimal cruise state,at which a flight control system is designed and tuned using the improved PIO algorithms.Finally,considering the optimal cruise state as the final state,the optimized climbing trajectory in relation to the minimum fuel cost is obtained using the improved PIO algorithm.Finally,the trajectory sensitivity is analyzed and the LQR controller for tracking the trajectory is designed to eliminate the trajectory deviation.Results show that the improved PIO algorithms are feasible and effective for the control and trajectory optimization design of the hypersonic vehicle,and that this optimization algorithm is valuable for the engineering application.