Model predictive control allocation: design and experimental results on a thermal management system

  • Authors:
  • Chris Vermillion;Jing Sun;Ken Butts

  • Affiliations:
  • Electrical Engineering and Computer Science Department and Naval Architecture and Marine Engineering Department, University of Michigan, Ann Arbor, MI;Electrical Engineering and Computer Science Department and Naval Architecture and Marine Engineering Department, University of Michigan, Ann Arbor, MI;Toyota Technical Center, Ann Arbor, MI

  • Venue:
  • ACC'09 Proceedings of the 2009 conference on American Control Conference
  • Year:
  • 2009

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Abstract

In this paper, we consider the challenge of controlling an overactuated engine thermal management system where two actuators, with different dynamic authorities and saturation limits, are used to obtain tight temperature regulation. We propose a modular control strategy that combines model predictive control allocation (MPCA) with the concepts of model reference control to design an inner loop controller that closely matches a dynamic specification for the inner loop input-output performance while addressing actuator dynamics and saturation constraints. We present the design and implementation strategy and illustrate the effectiveness of the proposed solution through real-time simulation and experimental results.