Liu, Y. and Kiss, M. and Tóth, Roland and Schoukens, M. (2025) On Space-Filling Input Design for Nonlinear Dynamic Model Learning: A Gaussian Process Approach. IEEE CONTROL SYSTEMS LETTERS, 9. pp. 1868-1873. ISSN 2475-1456 10.1109/LCSYS.2025.3582509

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Abstract

While optimal input design for linear systems has been well-established, no systematic approach exists for nonlinear systems where robustness to extrapolation/interpolation errors is prioritized over minimizing estimated parameter variance. To address this issue, we develop a novel space-filling input design strategy for nonlinear system identification that ensures data coverage of a given region of interest. By placing a Gaussian Process (GP) prior on the joint input-state space, the proposed strategy leverages the GP posterior variance to construct a cost function that promotes space-filling input design. Consequently, this enables maximization of the coverage in the region of interest, thereby facilitating the generation of informative datasets. Furthermore, we theoretically prove that minimization of the cost function implies the space-filling property of the obtained data. Effectiveness of the proposed strategy is demonstrated on both an academic and a mass-spring-damper example, highlighting its potential practical impact on efficient exploration of the dynamics of nonlinear systems. © 2017 IEEE.

Item Type:	Article
Uncontrolled Keywords:	DYNAMICS; Learning systems; nonlinear systems; Identification (control systems); Linear systems; Dynamic models; Gaussian distribution; Gaussian process; Filling; Cost functions; Gaussian noise (electronic); Regions of interest; Process approach; Gaussian Processes; non-linear system identification; Nonlinear system identification; input design; input design; Region-of-Interest; Cost-function; Dynamics model learning; Nonlinear dynamic models; Space filling;
Subjects:	Q Science > QA Mathematics and Computer Science > QA75 Electronic computers. Computer science / számítástechnika, számítógéptudomány
Divisions:	Systems and Control Lab
SWORD Depositor:	MTMT Injector
Depositing User:	MTMT Injector
Date Deposited:	07 Aug 2025 06:52
Last Modified:	07 Aug 2025 06:52
URI:	https://eprints.sztaki.hu/id/eprint/10959

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