采用改进粒子群算法优化的两关节移动机器人滑模控制研究

Study on the sliding mode control of two-joint mobile robot using improved particle swarm optimization

为了提高移动机器人关节运动轨迹控制精度,在滑模控制器的基础上,采用支持向量机耦合改进粒子群算法优化滑模控制器.创建移动机器人简图模型,给出移动机器人手臂动力学模型.引用支持向量机对滑模控制器参数进行评估,推导出支持向量机模型.采用改进粒子群算法优化滑模控制器,并给出具体优化过程.在Matlab软件中对移动机器人改进滑模控制器进行仿真实验,并与滑模控制器跟踪误差进行对比.仿真结果显示:在无波形干扰时,滑模控制器与改进滑模控制器相差不大,都能较好地实现轨迹跟踪任务;在有波形干扰时,改进滑模控制器反应速度较快,输出误差较小.移动机器人关节采用改进滑模控制器,抗干扰能力较强,控制精度较高.

In order to improve the accuracy of joint trajectory control of mobile robot,the support vector machine coupled with improved particle swarm optimization was used to optimize the sliding mode controller based on the sliding mode controller.A sketch model of mobile robot is established,and the arm dynamics model of mobile robot is given.Support vector machine is used to evaluate the parameters of the sliding mode controller,and the support vector machine model is deduced.The improved particle swarm optimization algorithm is used to optimize the sliding mode controller and the optimization process is given.In Matlab software,the improved sliding mode controller of mobile robot is simulated and compared with the tracking error of sliding mode controller.The simulation results show that the sliding mode controller and the improved sliding mode controller have little difference in the absence of waveform disturbance,and can achieve the trajectory tracking task better.In the presence of waveform disturbance,the improved sliding mode controller has faster response speed and smaller output error.An improved sliding mode controller is adopted for mobile robot joints,which has strong anti-interference ability and high control accuracy.