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Model Predictive Q-Learning (MPQ-L) for Bilinear Systems

In: Modeling, Simulation and Optimization of Complex Processes HPSC 2018

Author

Listed:
  • Minh Q. Phan

    (Dartmouth College, Thayer School of Engineering)

  • Seyed Mahdi B. Azad

    (Dartmouth College, Thayer School of Engineering)

Abstract

This paper provides a conceptual framework to design an optimal controller for a bilinear system by reinforcement learning. Model Predictive Q-Learning (MPQ-L) combines Model Predictive Control (MPC) with Q-Learning. MPC finds an initial sub-optimal controller from which a suitable parameterization of the Q-function is determined. The Q-function and the controller are then updated by reinforcement learning to optimality.

Suggested Citation

  • Minh Q. Phan & Seyed Mahdi B. Azad, 2021. "Model Predictive Q-Learning (MPQ-L) for Bilinear Systems," Springer Books, in: Hans Georg Bock & Willi Jäger & Ekaterina Kostina & Hoang Xuan Phu (ed.), Modeling, Simulation and Optimization of Complex Processes HPSC 2018, pages 97-115, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-55240-4_5
    DOI: 10.1007/978-3-030-55240-4_5
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