This paper presents the experimental implementation of a gradient-based nonlinear model predictive control (NMPC) algorithm to the swing-up control of a rotary inverted pendulum. The key attribute of the NMPC algorithm used here is that it only seeks to reduce the error at the end of the prediction horizon rather than finding the optimal solution. This reduces the computation load and allows real-time implementation. We discuss the implementation strategy and experimental results. In addition to NMPC based swing-up control, we also present results from a gradient based iterative learning control, which is the basis our NMPC algorithm.
Nonlinear Model Predictive Control for the Swing-Up of a Rotary Inverted Pendulum
Contributed by the Dynamic Systems, Measurement, and Control Division of THE AMERICAN SOCIETY OF MECHANICAL ENGINEERS for publication in the ASME JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received by the ASME Dynamic Systems and Control Division December 17, 2003. Associate Editor: F. Ghorbel.
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Jung , S., and Wen , J. T. (December 3, 2004). "Nonlinear Model Predictive Control for the Swing-Up of a Rotary Inverted Pendulum ." ASME. J. Dyn. Sys., Meas., Control. September 2004; 126(3): 666–673. https://doi.org/10.1115/1.1789541
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