Observer based robust H∞ fuzzy tracking control: application to an activated sludge process
Author(s) -
Abdelmounaim Khallouq,
Asma Karama,
Mohamed Abyad
Publication year - 2021
Publication title -
peerj computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.806
H-Index - 24
ISSN - 2376-5992
DOI - 10.7717/peerj-cs.458
Subject(s) - control theory (sociology) , fuzzy logic , observer (physics) , fuzzy control system , controller (irrigation) , computer science , separation principle , control engineering , state observer , trajectory , linear matrix inequality , convergence (economics) , nonlinear system , lyapunov function , mathematics , mathematical optimization , engineering , control (management) , artificial intelligence , physics , quantum mechanics , astronomy , economic growth , agronomy , economics , biology
The design of an observer-based robust tracking controller is investigated and successfully applied to control an Activated Sludge Process (ASP) in this study. To this end, the Takagi–Sugeno (TS) fuzzy modeling is used to describe the dynamics of a nonlinear system with disturbance. Since the states of the system are not fully available, a fuzzy observer is designed. Based on the observed states and a reference state model, a reduced fuzzy controller for trajectory tracking purposes is then proposed. While the controller and the observer are developed, the design goal is to achieve the convergence and a guaranteed H ∞ performance. By using Lyapunov and H ∞ theories, sufficient conditions for synthesis of a fuzzy observer and a fuzzy controller for TS fuzzy systems are derived. Using some special manipulations, these conditions are reformulated in terms of linear matrix inequalities (LMIs) problem. Finally, the robust and effective tracking performance of the proposed controller is tested through simulations to control the dissolved oxygen and the substrate concentrations in an activated sludge process.
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