Model based extremum-seeking controller via modelling-error compensation approach. (August 2019)

• Record Type: Journal Article
• Authors: Lara-Cisneros, Gerardo; Dochain, Denis; Alvarez-Ramírez, José
• Is Part Of: Journal of process control. Volume 80(2019)
• Page Start: 193
• Page End: 201
• Publication Date: 2019-08
• Subjects: Extremum-seeking control -- Gradient-based ESC -- Uncertain nonlinear systems; Process control -- Periodicals; Fabrication -- Contrôle -- Périodiques; Process control; Periodicals; Electronic journals; 660.281
• DOI: 10.1016/j.jprocont.2019.04.014
• Languages: English
• ISSNs: 0959-1524

Abstract

Highlights: Novel gradient based extremum-seeking control scheme. The ESC scheme is not using exogenous perturbation signals. The ESC technique is based on the modeling-error compensation approach using the input–output linearizing methodology. Robustness despite modeling errors and external perturbations is achieved. 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.