Abstract
This paper proposes a Fuzzy Fault Tolerant Predictive Control (FFTPC) with integral action method for a class of nonlinear systems. The Takagi-Sugeno (T-S) fuzzy approach is introduced as a modelling technique in order to consider the active control methods adapted to linear models. The proposed control strategy is based on a combination between Parallel Distributed Compensation (PDC) control law and Model Predictive Control (MPC) where the T-S fuzzy aspect uses the Unmeasurable Premise Variables (UPV). A T-S fuzzy observer provides an L2 norm estimation of system state vector and faults. The controller and observer gains are obtained by solving Linear Matrix Inequalities (LMIs) derived from the Lyapunov theory. The validity of the proposed Fault Tolerant Control (FTC) strategy is illustrated through an application to a Diesel Engine Air Path (DEAP) system.
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Recommended by Associate Editor Choon Ki Ahn under the direction of Editor Euntai Kim. The authors gratefully thank “Ecole Doctorale Sciences et Techniques de l’Ingénieur de Tunis,” MESRST and “Région Haute Normandie,” FEDER for financially supporting this work within the framework of the VIRTUOSE project. Likewise, authors are grateful to the associate editor and reviewers for their constructive comments based on which the presentation of this paper has been greatly improved.
Lamia Ben Hamouda received a Ph.D. degree in Electrical Engineering and Physics in 2015 from the National School of Engineers of Tunis (ENIT), LA.R.A, Tunisia and from University of Rouen, IRSEEM, FRANCE. She received her Master degree in Automatic and Signal Processing in 2011 from ENIT. She is currently Research professor in Cnam of Paris, France. Her research is related to predictive control, Faulttolerant control, stability and stabilization of non linear systems described by T-S fuzzy model, diagnostic and prognostic.
Mounir Ayadi graduated from Ecole Nationale d’Ingénieurs de Tunis in 1998 and received his Ph.D. degree in Automatic Control from the Institut National Polytechnique de Toulouse in 2002. He was a post-doctoral fellow at the Ecole Supérieure d’Ingéni-eurs en Génie Electrique de Rouen in 2003. He is currently Maître de Conférences at the Ecole Nationale d’Ingénieurs de Tunis and the head of Electrical Engineering Department in ENIT. His research interests are in the area of control system theory, predictive and adaptive control and flat systems.
Nicolas Langlois received the Ph.D. degree in Automatic Control and signal processing from the University of Rouen, Rouen, France in 2001. In 2000, he joined the graduate school of electrical engineering ESIGELEC, Rouen, France. At present, he is the head in charge of skills acquisition through research of ESIGELEC where he currently teaches control systems and digital signal processing. He is also the head of the “Automatic Control and Systems” research team at the research institute IRSEEM since 2008. His research interests include fault tolerant control. He is the co-author of over 90 publications in the field of control systems theory during these 10 last years.
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Hamouda, L.B., Ayadi, M. & Langlois, N. Fuzzy fault tolerant predictive control for a diesel engine air path. Int. J. Control Autom. Syst. 14, 443–451 (2016). https://doi.org/10.1007/s12555-014-0533-2
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DOI: https://doi.org/10.1007/s12555-014-0533-2