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http://dx.doi.org/10.6109/jkiice.2011.15.9.1871

Neural Network PID Controller for Angle and Speed Control of Two Wheeled Inverted Pendulum Robot  

Kim, Young-Doo (부산대학교 대학원 전자전기공학과)
An, Tae-Hee (부산대학교 대학원 전자전기공학과)
Jung, Gun-Oo (부산대학교 대학원 전자전기공학과)
Choi, Young-Kiu (부산대학교 전자전기공학부)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.15, no.9, 2011 , pp. 1871-1880 More about this Journal
Abstract
In this paper, a controller for two wheeled inverted pendulum robot, i.e., Segway type robot that is a convenient and easily handled vehicle is designed to have more stable balancing and faster velocity control compared to the conventional method. First, a widely used PID control structure is applied to the two wheeled inverted pendulum robot and proper PID control gains for some specified weights of users are obtained to get accurate balancing and velocity control by use of experimental trial-and-error method. Next, neural network is employed to generate appropriate PID control gains for arbitrarily selected weight. Here the PID gains based on the trial-and-error method are used as training data. Simulation study has been carried out to find that the performance of the designed controller using the neural network is more excellent than the conventional PID controller in terms of faster balancing and velocity control.
Keywords
two wheeled inverted pendulum type mobile robot; neural network; balancing control; PID control gain;
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