2022/10/18 by Tomonori Sadamoto, Sadamoto, Tomonori, Takumi Hirai +1 · 2 citations
Engineering · Medicine · #Advanced Control Systems Optimization #Cardiovascular Function and Risk Factors #FOS: Electrical engineering #Real-time simulation and control systems #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2210.09735
openalex publication_date 2022/10/18 · openalex created_date 2023/02/13 · openalex updated_date 2026/07/28
This paper proposes model-based and model-free policy gradient methods (PGMs) for designing dynamic output feedback controllers for discrete-time partially observable systems. To fulfill this objective, we first show that any dynamic output feedback controller design is equivalent to a state-feedback controller design for a newly introduced system whose internal state is a finite-length input-output history (IOH). Next, based on this equivalency, we propose a model-based PGM and show its global linear convergence by proving that the Polyak-Lojasiewicz inequality holds for a reachability-based lossless projection of the IOH dynamics. Moreover, we propose two model-free implementations of the PGM: the multi- and single-episodic PGM. The former is a Monte Carlo approximation of the model-based PGM, whereas the latter is a simplified version of the former for ease of use in real systems. A sample complexity analysis of both methods is also presented. Finally, the effectiveness of the model-based/model-free PGMs is investigated through a numerical simulation.