Abstract:
ABSTRACT
APPLICATION OF KALMAN FILTERING AND PID CONTROL FOR
DIRECT INVERTED PENDULUM CONTROL
by
José 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
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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.
