Tran Huu-Khoa, Chiou Juing-Shian
Department for Management of Science and Technology Development, Ton Duc Thang University, Ho Chi Minh City, Vietnam.
Faculty of Electrical & Electronic Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam.
Micromachines (Basel). 2016 Sep 15;7(9):168. doi: 10.3390/mi7090168.
Due to the rapid development of science and technology in recent times, many effective controllers are designed and applied successfully to complicated systems. The significant task of controller design is to determine optimized control gains in a short period of time. With this purpose in mind, a combination of the particle swarm optimization (PSO)-based algorithm and the evolutionary programming (EP) algorithm is introduced in this article. The benefit of this integration algorithm is the creation of new best-parameters for control design schemes. The proposed controller designs are then demonstrated to have the best performance for nonlinear micro air vehicle models.
由于近年来科学技术的飞速发展,许多有效的控制器被设计出来并成功应用于复杂系统。控制器设计的一项重要任务是在短时间内确定优化的控制增益。出于这个目的,本文引入了基于粒子群优化(PSO)算法和进化规划(EP)算法的组合。这种集成算法的好处是为控制设计方案创建新的最佳参数。然后证明所提出的控制器设计对于非线性微型飞行器模型具有最佳性能。