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arXiv · 1906.02580

Model predictive control with stage cost shaping inspired by reinforcement learning

Lukas Beckenbach·Pavel Osinenko·Stefan Streif
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Abstract

This work presents a suboptimality study of a particular model predictive control with a stage cost shaping based on the ideas of reinforcement learning. The focus of the suboptimality study is to derive quantities relating the infinite-horizon cost function under the said variant of model predictive control to the respective infinite-horizon value function. The basis control scheme involves usual stabilizing constraints comprising of a terminal set and a terminal cost in the form of a local Lyapunov function. The stage cost is adapted using the principles of Q-learning, a particular approach to reinforcement learning. The work is concluded by case studies with two systems for wide ranges of initial conditions.

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Lukas Beckenbach, Pavel Osinenko, Stefan Streif. 2020-04-27. Model predictive control with stage cost shaping inspired by reinforcement learning. https://arxiv.org/abs/1906.02580

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