Model based extremum-seeking controller via modelling-error compensation approach
(2019) Journal of Process Control — Vol. 80, p. 193-201 (2019)
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- Authors
Lara-Cisneros, Gerardo 
Dochain, Denis
- Abstract
- This paper is focused on the design of a robust model based extremum-seeking controller (ESC) aimed at the online optimization of a class of uncertain nonlinear systems. The ESC scheme is based on the modeling-error compensation approach using a robust input–output linearizing control law coupled with a first-order gradient estimator. The feedback control scheme is able to drive the closed-loop system into a vicinity of the optimal operating set-point. In contrast with perturbation-based ESC algorithms, the control scheme includes an observer-based uncertain estimator for computing unknown components related to model uncertainties and a continuous gradient estimator, while avoiding the use of a perturbation signal for achieving closed-loop convergence to the optimal neighborhood. The convergence of the closed-loop system to the unknown optimal set-point is analyzed. Numerical simulations illustrate the effectiveness of the proposed ESC scheme in two different nonlinear systems.
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Citations
Lara-Cisneros, G., Dochain, D., & Alvarez-Ramírez, J. (2019). Model based extremum-seeking controller via modelling-error compensation approach. Journal of Process Control, 80, 193-201. https://doi.org/10.1016/j.jprocont.2019.04.014 (Original work published 2019)