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Gradient-Based Model Predictive Control in a Pendulum System

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Author

Summary, in English

Model predictive control (MPC) is applied to a physical pendulum system consisting of a pendulum and a cart. The objective of the MPC controller is to steer the system towards precomputed, time-optimal feedforward trajectories that move the system from one stationary point to another. The sample time of the controller sets hard limitations on the execution time of the optimization algorithm in the MPC controller. The MPC optimization problem is stated as a quadratic program, which is solved using the algorithm presented in [10]. The algorithm in [10] is an accelerated gradient method that is applied to solve a dual formulation of the MPC optimization problem. Experiments show that the optimization algorithm is efficient enough to be implemented in a real-time pendulum application.

Publishing year

2012

Language

English

Publication/Series

Technical Reports TFRT-7624

Document type

Report

Publisher

Department of Automatic Control, Lund Institute of Technology, Lund University

Topic

  • Control Engineering

Keywords

  • Model Predictive Control
  • Pendulum system
  • Gradient-Based Optimization

Status

Published

Research group

  • LCCC

ISBN/ISSN/Other

  • ISSN: 0280-5316