Koopman Operator Dynamical Models: Learning, Analysis and Control?
Koopman Operator Dynamical Models: Learning, Analysis and Control? Petar Bevandaa,∗, Stefan Sosnowskia, Sandra Hirchea aChair of Information-oriented Control, Department of Electrical and Computer Engineering, Technical University of Munich, D-80333 Munich, Germany Abstract The Koopman operator allows for handling nonlinear systems through a (glob- ally) linear representation. In general, the operator is infinite-dimensional - ne- cessitating finite approximations - for which there is no overarching framework. Although there are principled ways of learning such finite approximations, they are in many instances overlooked in favor of, often ill-posed and unstructured methods. Also, Koopman operator theory has long-standing connections to known system-theoretic and dynamical system notions that are not universally recognized. Given the former and latter realities, this work aims to bridge the gap between various concepts regarding both theory and tractable realizations. Firstly, we review data-driven representations (both unstructured and struc- tured) for Koopman operator dynamical models, categorizing various existing methodologies and highlighting their differences. Furthermore, we provide con- cise insight into the paradigm's relation to system-theoretic notions and analyze the prospect of using the paradigm for modeling control systems. Additionally, we outline the current challenges and comment on future perspectives. Keywords: Koopman operator, dynamical models, representation learning, system analysis, data-based control 1. INTRODUCTION Efficient control and analysis are inherently challenging when dealing with complex dynamical systems. For such complex systems, models coming from arXiv:2102.02522v1 [eess.SY] 4 Feb 2021 first-principles often times are not available or do not fully resemble the true system due to unmodeled phenomena. Thus, there is great value in develop- ing effective techniques with the ability to discover, analyze and control such systems.
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