Research on robot balance based on Kalman filter algorithm and LQR controller

With the development of science and technology, the convenience brought by robots to people has been countless. During the development of the robot, the body shape of the robot is becoming slimmer, which leads to the unstable condition of the top when the lower end moves. In order to improve the accuracy and robustness of the robot, a control strategy based on Kalman filter and LQR algorithm is proposed to solve the problem. When some slender robots move, their equilibrium model is similar to inverted pendulum, which is a typical representative of nonlinear system. Therefore, in this paper, LQR controller is designed to realize its stability control. In view of the problem that the measurement noise and system state are not completely measurable in the controller design of robot balance, this paper designs a controller based on the continuous time Kalman filter and LQR control theory, which has a good effect in noise filtering and output estimation. Simulation and experimental results show that the controller is feasible and effective.