Ensemble Kalman filter and PID controller implementation on self balancing robot

Abstract

One technique that is commonly used for mobile robots is an inverted pendulum based model. This research has been implementing a mobile robot technique in an unstable environment. The goal is to design and implementing a discrete digital control system that will provide robot stability. The PID controller algorithm and Ensemble Kalman filter (EnKF) implementation would be an ideal test model of this robot. Both of these algorithms are able to improve the performance of control systems. This robot already tested the performance of the PID control system and the EnKF algorithm. The performance of the PID controller algorithm and EnKF is tested by software. The Control system performance is directly dependent on the EnKF algorithm and input parameters of PID controller. Research uses EnKF algorithm and PID controller as a balancing robot. The covariance filter tuned by manually. Experiments carried out by the method of trial and error by varying the process noise covariance matrix. The system overshoot can be reduced by processing noise covariance matrix. The experiment results showed system optimal on Q_accelerometer: 0001, Q_gyroscope: 0.05 R_measurement: 12:03, P = 1790,005, I = 0.129 and D = 96 881.