基于GA的模糊技术在“牧羊”机器人驱动系统中的应用

    Application of fuzzy technique based on genetic algorithm in drive system of robot sheepdog

    • 摘要: 针对“牧羊”机器人研究中的理想系统与实际系统的模型匹配问题,为提高机器人的运动精度,在控制器的设计中,将模糊控制和遗传算法结合起来进行优化,实现了对机器人两个驱动电机的协调控制。在优化遗传算子的基础上,根据训练样本,自动生成模糊规则,从而提出了一种模型不确知的复杂系统过程控制方法,在优化隶属函数后,能生成模糊规则,最后用仿真试验证明了该方法的有效性。

       

      Abstract: Focused on the problem of modeling matching between ideal systems and virtual systems in the research on robot sheepdog, during the design of robot driving controller, fuzzy control theory and genetic algorithm are syncretized and optimized to improve robot moving precision. Finally a harmonious control of robot two drive motors is achieved. In this paper, GA operators are optimized, and a new method is proposed to control many complex systems whose models are unknown, using this method fuzzy rules can be acquired automatically according to training samples. The simulation result shows the effectiveness and feasibility of the method.

       

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