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Real-time control of an inverted pendulum system using complementary neural network and optimal techniques

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2 Author(s)
Nelson, J. ; Dept. of Electr. & Comput. Eng., New Hampshire Univ., Durham, NH, USA ; Kraft, L.G.

Inverted pendulum is a simple, inherently unstable system which exhibits the fundamental characteristics of balance. This paper explores the control of a robotic pole-balancing system using complementary optimal and neural network techniques. A full state feedback linear regulator type optimal controller was developed from the approximate system model. When applied to the real physical system, this controller produced a relatively large limit cycle, due primarily to unmodelled system nonlinearities. The CMAC neural network was then introduced into the controller to learn any nonlinearities, reject residual noise, and, as a result, shrink the system limit cycle.

Published in:

American Control Conference, 1994  (Volume:3 )

Date of Conference:

29 June-1 July 1994