两轮自平衡机器人控制系统设计与实现

Design and implementation of control system for two-wheeled self-balancing robot

提出了一种使用PID优化LQR的两轮自平衡机器人控制方案。首先建立自平衡机器人的动态模型,使用卡尔曼滤波实现加速度计及陀螺仪的信息融合,然后设计了一种具有PID动态调节及LQR跟踪功能的PID-LQR控制器,解决了机器人在大角度范围内不能快速稳定地达到设定状态效果的问题,最后搭建了以K60微控制器为核心的机器人软硬件平台。仿真结果表明当设定速度为1m/s时,PID-LQR控制器比LQR控制器动态响应速度减少接近1 s。实际应用测试结果表明当机器人受冲击后,重新回到平衡位置的时间减少接近1s,平衡位置的扰动大小减小50%左右。

A control scheme using PID to optimize LQR for two-wheels self-balancing robot is proposed.Firstly,the dynamic model of self-balancing robot is established,and Kalman filter is used to implement the information fusion of accelerometer and gyroscope.Then,a PID-LQR controller with PID dynamic adjustment and LQR tracking function is designed to solve the problem that the robot can＇t change fast and steady enough to set the state in a large angular range.Finally,a robot hardware and software platform based on K60 micro controller is built.Comparing with LQR controller,the simulation results demonstrate that when the set speed of robot is 1 m/s,PID-LQR controller＇s dynamic response speed is reduced by nearly 1 s.The practical test results show that when the robot got be hit,the time used to back to the equilibrium position is reduced by almost 1 s and the perturbation size of equilibrium position is decreases by about 50%.