H<sub>∞</sub> Static Output-Feedback Control Design for Discrete-Time Systems Using Reinforcement Learning.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 31021775.
- Also identified by DOI 10.1109/TNNLS.2019.2901889.
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Abstract
This paper provides necessary and sufficient conditions for the existence of the static output-feedback (OPFB) solution to the H<sub>∞</sub> control problem for linear discrete-time systems. It is shown that the solution of the static OPFB H<sub>∞</sub> control is a Nash equilibrium point. Furthermore, a Q-learning algorithm is developed to find the H<sub>∞</sub> OPFB solution online using data measured along the system trajectories and without knowing the system matrices. This is achieved by solving a game algebraic Riccati equation online and using the measured data. A simulation example shows the effectiveness of the proposed method.