Open Access Open Access  Restricted Access Subscription or Fee Access

Robust Adaptive Generalized Predictive Control Based on Takagi-Sugeno Fuzzy Model

(*) Corresponding author

Authors' affiliations



Predictive adaptive algorithms are powerful tools for controlling time varying systems. In particular, the Adaptive Generalized Predictive Control is widely used in different plants or processes. Nevertheless, a lack of robustness is often observed especially in case of large uncertainties in the model and in the presence of strong nonlinearities. Better solutions have been proposed using fuzzy modelling. In this paper, a direct adaptive version of the generalized predictive controller is developed. This allows an automatic online and real-time adjustment of local controller settings in order to maintain a proper level of performance. The contributions presented in this paper lie in the merging of local controllers using a fuzzy technique in order to produce a global controller using on-line parameters identification by a recursive lest squares type strategy. The stability of the closed-loop control system is demonstrated through the Lyapunov Stability Theory. Highly improved results are confirmed by simulation on an example of the commonly used Continuous Stirred Tank Reactor system.
Copyright © 2021 Praise Worthy Prize - All rights reserved.


Predictive Control; Adaptive Control; Fuzzy Model; Lyapunov Stability; Nonlinear Systems

Full Text:



D.W. Clarke, C. Mohtadi, and P.S. Tuffs, Generalized predictive control part I and II, Automatica, Vol 23(2), pp. 137-190, 1987.

C.R. Cutler, B.L. Ramaker, Dynamic matrix control- A computer control algorithm, In: Joint Automatic Control Conf. San Francisco, California, 1980.

C.E. Garcíaa, D.M. Prett and M. Morari. Model predictive control: Theory and practice - a survey. Automatica, Vol 25(3), pp. 335-348, 1989.

Mossa, M., Zaki Diab, A., Effective Model Predictive Control Approach for a Faulty Induction Motor Drive, (2019) International Review of Electrical Engineering (IREE), 14 (5), pp. 314-327.

E.F. Camacho, C. Bordons, Model Predictive Control in the Process Industry. Advances in Industrial Control, Springer Verlag, 1995.

L. Zadeh. Outline of a new approach to the analysis of complex systems and decision processes. IEEE Trans. Syst., Man, Cybern, Part B, Vol 3(1), 28-44, 1973.

D. Driankov, H. Hellendoorn and M. Reinfrank. An Introduction to Fuzzy Control, Springer-Verlag, 1993.

L.S. Cheng, M. Linab and L. Ping, Direct Adaptive Fuzzy Predictive Control and Its Application to CSTR Process,Applied Mechanics and Materials, vol 241-244, pp.1191-1194, 2013.

A. Flores, D. Sáez, J. Araya, M. Berenguel and A. Cipriano. Fuzzy predictive control of a solar power plant. IEEE Transactions on Fuzzy Systems, Vol 13(1), pp. 58-68, 2005.

Reddipogu, J., Elumalai, V., Multi-Objective Model Predictive Control for Vehicle Active Suspension System, (2020) International Review of Automatic Control (IREACO), 13 (5), pp. 255-263.

N. Liu, X. Tang, L. Deng, Constrained model predictive control for T-S fuzzy system with randomly occurring actuator saturation and packet losses via PDC and non-PDC strategies, Transactions of the Institute of Measurement and Control, vol 42(8), pp. 1437-144 , 2018.

M. H. Khooban, N. Vafamand, T. Niknam, T. Dragicevic, Model Predictive Control based on T-S Fuzzy model For Electrical Vehicles Delayed Model, IET Electric Power Applications, Vol 11(5), pp. 918-934, 2018.

A. Evsukoff, A. C. S. Branco, and S. Galichet. Structure identification and parameter optimization for non-linear fuzzy modeling. Fuzzy Sets & Systems, Vol 132(2), pp. 173-188, 2002.

S. Mollov, R. Babuska and H.B. Verbruggen. Effective optimization for fuzzy model predictive control. IEEE Transactions on Fuzzy Systems, Vol 12(5), pp. 661-675, 2004.

S. Bououden, M. Chadli, F. Allouani, S. Filali, A new approach for fuzzy predictive adaptive controller design using particle swarm optimization algorithm, International Journal of Innovative Computing, Information and Control, vol9(9), pp. 3741-3758, 2013.

I. Skrjanc, D. Matko,Predictive functional control based on fuzzy model for heat-exchanger pilot plant,IEEE Transactions on Fuzzy Systems,vol 8(6), pp. 705-712, 2000.

S. Doudou, F. Khaber, Adaptive fuzzy sliding mode control for a class of uncertain no affine nonlinear strict-feedback systems. Iranian Journal of Science and Technology, Transactions of Electrical Engineering, vol 43(1), pp. 33-45, 2019.

Y.L. Huang, H.H. Lou, J.P. Gongand T.F. Edgar. Fuzzy Model Predictive Control. IEEE Trans on Fuzzy Systems, Vol 8(6), pp. 665-678, 2000.

J.M. Da Costa Sousa, U. Kaymak. Model predictive control using fuzzy decision functions. IEEE Transactions on Systems, Vol 31(1), pp.54-65,2001.

L. Dalhoumi, M. Djemel, M. Chtourou. Fuzzy predictive control based on Takagi-Sugeno model for nonlinear systems. 7th International Multi-Conference on Systems, Signals and Devices, IEEE Xplore,2010.

H. Xie, J. Wang, X. Tang, Robust constrained model predictive control for discrete time uncertain system in Takagi Sugeno's form, Asian Journal of Control, vol 20(4), pp. 1566-1581. 2018.

I. C. Franco, J. E. Schmitz, T. Costa, A. M. F. Fileti, Development of a Predictive Control Based on Takagi-Sugeno Model Applied in a Non-Linear System of Industrial Refrigeration, Journal Chemical Engineering Communications, Vol 204(1), pp. 39-54, 2017.

B. Wang, J.Y. Xue, D.Y. Chen. Takagi-Sugeno fuzzy control for a wide class of fractional-order chaotic systems with uncertain parameters via linear matrix inequality. J. Vib. Control, Vol 22(10), pp. 2356-2369, 2016.

O. Bourebia, K. Belarbi, Fuzzy Generalized Predictive Control for Nonlinear Systems with Coordination Technique, International Review of Automatic Control (Theory and Applications), vol 1(2), pp.169-176, 2008.

Y. Dong, Y. Song, B. Zhang. Model predictive control for nonlinear systems in Takagi-Sugeno form under round-robin protocol, Journal of the Franklin Institute, Vol 357(12), pp. 7597-7616, 2020.

C. Su, P. Li, and S. Wang, A direct adaptive predictive functional control based on T-S fuzzy model, In Proceedings of the Sixth International Conference on Intelligent Systems Design and Applications, pp. 92-97, Washington, DC, USA, IEEE Computer Society, 2006.

G. Ramond, D. Dumur, A. Libaux, P. Boucher, Direct Adaptive Predictive control of anhydro-electric plant, Proceedings 10th IEEE Conference on Control Applications, Mexico, pp. 606-611, Mexique, 2001.

X. Xia, L. Cheng, Adaptive Takagi-Sugeno Fuzzy Model for Pneumatic Artificial Muscles, 13th International Conference on Advanced Computational Intelligence (ICACI), 2021.

Adetola and M. Guay, Adaptive receding horizon control of nonlinear systems, In Proc. of IFAC Symposium on Nonlinear Control systems, pp. 1055-1060, Stuttgart, 2008.

F. Jia, X. Wang, X. Zhou, Robust adaptive prescribed performance control for a class of nonlinear pure-feedback systems. International Journal of Robust and Nonlinear Control. vol 29(12), pp. 3971-3987, 2019.

K. Shi, B. Wang, L. Yang, Takagi-Sugeno fuzzy generalized predictive control for a class of nonlinear systems. SpringerNonlinear Dynamics, vol 89(1), pp. 169-177, 2017.

Yong-Lin Kuo, I. E. Citra Resmi, Model Predictive Control Based on a Takagi-Sugeno Fuzzy Model for Nonlinear Systems, International Journal of Fuzzy Systems, vol 21(2). 2019.

L. Gutiérrez, D. Muñoz-Carpintero, F. Valencia and D. Sáez. A new method for identification of fuzzy models with controllability constraints. Applied Soft Computing Elsevier. Vol 73, pp. 254-262. 2018.

Massaq, Z., Chbirik, G., Abounada, A., Brahmi, A., Ramzi, M., Control of Photovoltaic Water Pumping System Employing Non-Linear Predictive Control and Fuzzy Logic Control, (2020) International Review on Modelling and Simulations (IREMOS), 13 (6), pp. 373-382.

Fas, M. L., Filali, S., Kazed, B., Robustification of a Generalised Predictive Control under LMI Constraints Setting Using a Dual Youla-Kučera Parameterisation, (2011) International Review of Automatic Control (IREACO), 4 (4), pp. 510-519.

K. Han, J. Feng, Q. Zhao, P. Jiang, X. Wang, Robust constrained predictive fault tolerant control with generalized input parameterization and event-triggered regulation: Design and experimental results. IEEE Transactions on Industrial Electronics. 2020.

P. Ioannou, A. Petros and B. Fidan, Adaptive Control Tutorial, Society for Industrial and Applied Mathematics, 2006.

A. Vafamand, A. Fatehi, S. M. Emad Oliaee . A fuzzy generalized predictive controller to optimal drug dosage therapy of mathematical modeling of HIV. Iranian Journal of Fuzzy Systems. 2021.

T. Tang, R. Qi, B. Jiang, Adaptive nonlinear generalized predictive control for hypersonic vehicle with unknown parameters and control constraints, SAGE journals, vol 233, pp.510-532. 2017.

I. Boulkaibet, K. Belarbi, S. Bououden, T. Marwala, A. Chadli, New T-S fuzzy model predictive control for nonlinear processes, Elsevier, Expert Systems With Applications, vol. 88, pp.132-151, 2017.

J.Köhler, P.Kötting, R.Soloperto, F. Allgöwer, M. A. Müller. A robust adaptive model predictive control framework for nonlinear uncertain systems, International Journal of Robust and Nonlinear Control, vol 4(4), pp. 510-519. 2020.

W. Hu, G. Zhang, Y. Zheng. A novel optimal control design for unknown nonlinear systems based on adaptive dynamic programming and nonlinear model predictive control, Asian Journal of Control, 2021.

J. Zhou; N. Zhang; C. Li; Y. Zhang; X. Lai, An Adaptive Takagi-Sugeno Fuzzy Model-Based Generalized Predictive Controller for Pumped-Storage Unit. IEEE Access, vol 7, pp. 103538-103555, 2019.


  • There are currently no refbacks.

Please send any question about this web site to
Copyright © 2005-2023 Praise Worthy Prize