Low Cost Mobile Inverted Pendulum Using Kalman Filter with Fuzzy Based PID Controller

In the “Mobile Inverted Pendulum (MIP),” the robot with two-wheels can move front and back in a horizontal path and take the role of the cart in the basic inverted pendulum system. The usage of expensive sensors, like the SCC2130-D08-05 Murata, is a flaw in the current system. Our work includes modeling the MIP's State Space equation and utilizing MATLAB to examine the system's observability and controllability. To estimate the angular position of the MIP, a combination gyro sensor, accelerometer sensor along with Kalman filter is developed thereby reducing the cost of the model. PID controllers with FUZZY tuning are used in the proposed system. The MIP is stabilized using the PID. The PID gain settings in this case are tuned using a fuzzy method.