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为减少OGY方法前期等待时间,结合自适应混沌粒子群算法(ACPOS)设计一种新的OGY控制器(ACPOS-OGY).用ACPOS对混沌系统轨道做初始引导,将其引导到不稳定不动点的邻域内,然后再对系统参数进行微调,最终使系统轨道达到稳定的轨道上.ACPOS-OGY不仅吸取粒子群算法和OGY方法的优点,而且自适应调整策略和混沌化处理粒子群算法过程也避免了粒子群算法的缺点,使前期引导轨道更快更准.仿真实验结果表明:改进算法是有效的,并且克服了PSO引导中的人为因素的影响.
In order to reduce the early waiting time of OGY method, a new OGY controller (ACPOS-OGY) is designed based on adaptive chaotic particle swarm optimization algorithm (ACPOS). Using ACPOS to initialize the orbit of chaotic system, Point system, and then the system parameters are fine-tuned to finally make the orbit of the system reach a stable orbit.ACPOS-OGY not only absorbs the advantages of particle swarm optimization and OGY methods, but also adaptively adjusts the strategy and the process of chaotic particle swarm optimization But also avoids the disadvantages of PSO and makes the pre-orbit guidance faster and more accurate.The simulation results show that the improved algorithm is effective and overcomes the influence of human factors in PSO guidance.