基于粒子群优化的串级模糊PID水下机器人定深控制

Guwen Ren, Shaojie Xin
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引用次数: 0

摘要

针对传统PID控制器在ROV运动控制中调节时间长、鲁棒性差的问题,提出了一种基于粒子群优化的串联级模糊PID控制方法用于ROV恒深控制。对六自由度ROV进行了运动学和动力学分析,得到了ROV在固定深度下运动的数学模型。在串级模糊PID控制条件下,采用改进的粒子群算法对控制器参数进行优化,得到控制器参数的最优值。通过仿真验证了控制算法的有效性。结果表明,基于粒子群优化的串级模糊PID控制相对于传统控制方法具有抗干扰能力强、超调量小、调整时间短等显著优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PSO Optimization-Based Series-Level Fuzzy PID Underwater Robot Fixed Depth Control
A series-level fuzzy PID control method based on PSO optimization is proposed for ROV constant depth control to address the problems of long adjustment time and poor robustness of traditional PID controllers in ROV motion control. The kinematic and dynamic analysis of the six-degree-of-freedom ROV is carried out to obtain the mathematical model of the ROV motion with a fixed depth. The optimal values of the controller parameters are obtained by optimizing the controller parameters with the improved particle swarm algorithm under the string-level fuzzy PID control conditions. The effect of the control algorithm is verified by simulation. The results show that the series-level fuzzy PID control based on PSO optimization has significant advantages over traditional control methods, with strong anti-interference capability, minor overshoot, and shorter adjustment time.
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