Due to the introduction of fast non-dominated sorting algorithms,crowding operators and elitestrategy,the probability of repetition individual increased significantly in every population of NSGA-II algorithm, reducing the Pareto efficiency. It has been improved for this defect,removed the repeating individual and maintained the number of populations unchanged. According to the genetic algorithm crossover and mutation method and differential evolution algorithm DE,the improved NSGA-II and DE are combined to construct a new multiobjective optimization algorithm. The algorithm takes DE as the main optimization method,and uses the basic idea and crossover and mutation method of genetic algorithm. The optimization algorithm was verified by MATLAB. The results show that the optimized algorithm has been improved in both distribution and convergence,and the capacity of search solution has also been improved. At last ,the optimization algorithm is used to complete the hardwaresoftware partitioning of task management part in μC /OS-II.
Application of Differential Evolution Algorithm in Quadrotors Attitude
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Related Author
XUE Ping
ZHOU Ren-he
WANG Hong-min
LI Lan-ying
KONG Yin
CHEN De-yun
LIU Yong-jie
YU Xiao-yu
Related Institution
School of Automation, Harbin University of Science and Technology
School of Computer Science and Technology,Harbin University of Science and Technology
Harbin University of Science and Technology, School of Measurement and Control Technology and Communication Engineering, Key Laboratory of Measurement and Control technology and Instrument in Heilongjiang Province, Haerbin
School of Material Science and Engineering,Harbin University of Science and Technology
School of Civil Engineering and Architecture, Harbin University of Science and Technology