A quantum inspired genetic algorithm for multimodal optimization of wind disturbance alleviation flight control system

作     者：Qi BIAN Brett NENER Xinmin WANG 

作者机构：School of AutomobileChang’an UniversityXi’an 710064China Department of ElectricalElectronicsand Computer EngineeringThe University of Western AustraliaCrawley 6009WAAustralia School of AutomationNorthwestern Polytechnical UniversityXi'an 710129China 

出 版 物：《Chinese Journal of Aeronautics》 (中国航空学报（英文版）)

年 卷 期：2019年第32卷第11期

页      面：2480-2488页

核心收录：

学科分类：0711[理学-系统科学] 07[理学] 08[工学] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 071102[理学-系统分析与集成] 081103[工学-系统工程] 

主　　题：Flight control system Genetic algorithm Multimodal optimization Quantum inspired algorithm Wind disturbance alleviation 

摘      要：This paper develops a Quantum-inspired Genetic Algorithm(QGA) to find the sets of optimal parameters for the wind disturbance alleviation Flight Control System(FCS). To search the problem domain more evenly and uniformly, the lattice rule based stratification method is used to create new chromosomes. The chromosomes are coded and updated according to quantuminspired strategies. A niching method is used to ensure every chromosome can converge to its corresponding local minimum in the optimization process. A parallel archive system is adopted to monitor the chromosomes on-line and save all potential feasible solutions in the optimization process. An adaptive search strategy is used to gradually adjust the search domain of each niche to finally approach the local minima. The solutions found by the QGA are compared with some other Multimodal Optimization(MO) algorithms and are tested on the FCS of the Boeing 747 to demonstrate the effectiveness of the proposed algorithm.