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

作　　者：Qi BIAN Brett NENER Xinmin WANG 

机构地区：[1]School of Automobile,Chang’an University,Xi’an 710064,China [2]Department of Electrical,Electronics,and Computer Engineering,The University of Western Australia,Crawley 6009,WA,Australia [3]School of Automation,Northwestern Polytechnical University,Xi'an 710129,China

出　　处：《Chinese Journal of Aeronautics》2019年第11期2480-2488,共9页中国航空学报（英文版）

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.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.

关 键 词：Flight control system Genetic algorithm Multimodal optimization Quantum inspired algorithm Wind disturbance alleviation 

分 类 号：TP1[自动化与计算机技术—控制理论与控制工程]