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Volume 10 Issue 5
May  2023

IEEE/CAA Journal of Automatica Sinica

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Article Contents
A. D. Carnerero, D. R. Ramirez, D. Limon, and  T. Alamo,  “Kernel-based state-space kriging for predictive control,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 5, pp. 1263–1275, May 2023. doi: 10.1109/JAS.2023.123459
Citation: A. D. Carnerero, D. R. Ramirez, D. Limon, and  T. Alamo,  “Kernel-based state-space kriging for predictive control,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 5, pp. 1263–1275, May 2023. doi: 10.1109/JAS.2023.123459

Kernel-Based State-Space Kriging for Predictive Control

doi: 10.1109/JAS.2023.123459
Funds:  A preliminary version of this paper was presented at the 2022 IEEE Conference on Decision and Control. This work was supported by the Agencia Estatal de Investigación (AEI)-Spain (PID2019-106212RB-C41/AEI/10.13039/501100011033) and also by Junta de Andalucía and FEDER funds (P20_00546)
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  • In this paper, we extend the state-space kriging (SSK) modeling technique presented in a previous work by the authors in order to consider non-autonomous systems. SSK is a data-driven method that computes predictions as linear combinations of past outputs. To model the nonlinear dynamics of the system, we propose the kernel-based state-space kriging (K-SSK), a new version of the SSK where kernel functions are used instead of resorting to considerations about the locality of the data. Also, a Kalman filter can be used to improve the predictions at each time step in the case of noisy measurements. A constrained tracking nonlinear model predictive control (NMPC) scheme using the black-box input-output model obtained by means of the K-SSK prediction method is proposed. Finally, a simulation example and a real experiment are provided in order to assess the performance of the proposed controller.


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    • This paper presents novel black-box models for nonlinear dynamical systems
    • A Kalman filter can be easily added to improve the quality of the predictions
    • A Tracking MPC controller is built by using the previously obtained models
    • The stability of the closed-loop system is proven by means of some mild assumptions
    • The controller attained very good results in a set of simulated and real experiments


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