优化模糊控制算法的四轮差速机器人运动控制
Optimized Fuzzy Control Algorithm for Motion Control of a Four-Wheeled Differential Robot
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摘要: 针对直线运动状态下轮式移动机器人出现打滑的情况,提出了一种基于遗传算法优化模糊比例、积分和微分(Proportional Integral Derivative,PID)控制器的速度控制策略。首先,建立轮式移动机器人逆运动学模型,对四轮差速型轮式机器人出现车轮打滑的运动状态展开分析;然后,设计了基于遗传算法优化的模糊PID控制器及机器人控制策略,并选取了其中影响直线运动的两种主要打滑状态开展仿真与实验分析;经分析,相较于传统PID控制,该控制策略整体加速响应时间减少了0.58 s,超调量低于1.5%,这表明该控制策略的收敛速度和稳定性均取得了较明显的提升,验证了该方法的有效性,解决了轮式移动机器人打滑的难题,实现了运动控制的准确性、时效性和鲁棒性目标。Abstract: In order to address the situation of wheel slip in wheeled mobile robot under linear motion state, a speed control strategy based on genetic algorithm optimized fuzzy proportional, integral and differential (PID) controller is proposed in this article. Through establishment of the wheeled mobile robot inverse kinematics model, the motion state analysis on the four-wheel differential wheeled robot with wheel slipping is carried out, the fuzzy PID controller and robot control strategy based on the genetic algorithm optimization are designed. Two main slipping conditions affecting linear motion are selected for simulation and experimental analysis. Through the analysis, it is shown that compared to the traditional PID control, the overall acceleration response time of the control strategy is reduced by 0.58 s, and the overshoot amount is less than 1.5%. The results show that the convergence speed and stability of the control strategy have achieved a more significant improvement, which verifies the effectiveness of the method, solves the slipping problem of the wheeled mobile robot, and realizes the goal of accuracy, timeliness and robustness of the motion control.