Nonlinear model predictive control of an inverted pendulum

Authors:
Adam Mills;Adrian Wills;Brett Ninness
Affiliations:
School of Electrical Engineering and Computer Science, University of Newcastle, Callaghan, NSW, Australia;School of Electrical Engineering and Computer Science, University of Newcastle, Callaghan, NSW, Australia;School of Electrical Engineering and Computer Science, University of Newcastle, Callaghan, NSW, Australia
Venue:
ACC'09 Proceedings of the 2009 conference on American Control Conference
Year:
2009

Citing 1
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Abstract

In this paper, nonlinear model predictive control is applied to an inverted pendulum apparatus. The sample interval for control calculations is 25 milli-seconds and the associated non-convex constrained optimisation problem involves 61-variables with 241-constraints. Despite this being a challenging problem, it was solved on-line using a standard sequential quadratic programming approach on a modest hardware platform. The efficacy of the control algorithm is validated via experimental results.