Application of Kalman Filtering and PID Control for Direct Inverted Pendelum Control
José L. Miranda · California State University ScholarWorks (system-wide DSpace) · 2010
ABSTRACT APPLICATION OF KALMAN FILTERING AND PID CONTROL FOR DIRECT INVERTED PENDULUM CONTROL by Jos?? Luis Corona Miranda Master of Science in Electrical and Computer Engineering Electronic Engineering Option California State University, Chico Spring 2009 Robotic mobility technologies over the past few years have gain popularly in both commercial and government sectors. There been a variety of techniques suggested to increase robotic mobility on dynamic environments. One such popular technique used to provide greater mobility to a robotic platform is based on the inverted pendulum model. The presented document will demonstrate the techniques involved in balancing an unstable robotic platform. The objective is to design a complete discrete digital control system that will provide the needed stability. The platform will be an ideal test bed for the implementations of both PID digital control and Kalman filter algorithms. Both algorithms will provide the necessary control for the system. Therefore the presented viii project will investigate the performance of both PID digital control and Kalman filter algorithms. Test software was written to gather performance results for both the PID controller and Kalman filter. The control system performance is directly dependent on Kalman filter and PID controller input parameters. The results clearly show how the adjustable parameters on the control system directly affected the overall system performance. The results also demonstrate the performance and the need of the Kalman filter to remove sensor noise. The almost reliable sensor data increases PID controller performance to drive the robotic platform to vertical equilibrium. The gathered results for the Kalman filter were compared against the raw noisy sensor data. The plots for such comparison are shown on the Kalman filter results section. PID controller output response data was also collected and plotted. The PID output response results were used in the controller tuning process.