Efficient fuzzy control of a rotary inverted pendulum based on LQR mapping

J Krishen, VM Becerra - 2006 IEEE Conference on Computer …, 2006 - ieeexplore.ieee.org
J Krishen, VM Becerra
2006 IEEE Conference on Computer Aided Control System Design, 2006 …, 2006ieeexplore.ieee.org
This paper develops fuzzy methods for control of the rotary inverted pendulum, an
underactuated mechanical system. Two control laws are presented, one for swing up and
another for the stabilization. The pendulum is swung up from the vertical down stable
position to the upward unstable position in a controlled trajectory. The rules for the swing up
are heuristically written such that each swing results in greater energy build up. The
stabilization is achieved by mapping a stabilizing LQR control law to two fuzzy inference …
This paper develops fuzzy methods for control of the rotary inverted pendulum, an underactuated mechanical system. Two control laws are presented, one for swing up and another for the stabilization. The pendulum is swung up from the vertical down stable position to the upward unstable position in a controlled trajectory. The rules for the swing up are heuristically written such that each swing results in greater energy build up. The stabilization is achieved by mapping a stabilizing LQR control law to two fuzzy inference engines, which reduces the computational load compared with using a single fuzzy inference engine. The robustness of the balancing control is tested by attaching a bottle of water at the tip of the pendulum.
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