基于模糊自适应整定PID控制的机器人路径跟踪方法设计
2024,32(12):146-152
摘要：常规机器人路径跟踪算法在机器人运动过程中无法实时调整PID控制器的参数,导致机器人的路径跟踪性能较差。为解决这一问题,提出了机器人路径跟踪的模糊自适应整定PID算法设计。首先构建机器人系统模型,计算机器人的运动航向角,并根据机器人测量系统利用基准坐标系中的离散坐标来描述机器人在运动过程中的曲面法向量。然后结合转动离散惯性系数对路径特征点进行匹配。基于此基础,引入模糊自适应整定PID算法设计控制器,通过优化控制器的内部参数,调整控制器的增益输出,从而实现机器人的路径跟踪。实例应用结果表明,该方法能够准确跟踪机器人的移动路径,路径跟踪偏移较小,跟踪性能较好。
关键词：模糊自适应整定PID;机器人;路径跟踪;期望路径;跟踪偏移量;离散惯性系数;
Design of a Robot Path Tracking Method Based on Fuzzy Adaptive Tuning PID Control
Abstract：Conventional robot path tracking algorithms are unable to adjust the parameters of the PID controller in real-time during robot motion, resulting in poor path tracking performance of the robot. To solve this problem, a fuzzy adaptive tuning PID algorithm design for robot path tracking is proposed. Firstly, construct a robot system model, calculate the motion heading angle of the robot, and use the discrete coordinates in the reference coordinate system to describe the surface normal vector of the robot during the motion process based on the robot measurement system. Then, combined with the rotational discrete inertia coefficient, match the path feature points. Based on this, a fuzzy adaptive tuning PID algorithm is introduced to design a controller. By optimizing the internal parameters of the controller and adjusting the gain output of the controller, the path tracking of the robot is achieved. The application results of the example show that this method can accurately track the movement path of the robot, with small path tracking offset and good tracking performance.
Key words：Fuzzy adaptive PID tuning; Robots; Path tracking; Expected path;Tracking offset; Discrete inertia coefficient;
收稿日期：2024-06-28
基金项目：
