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Robust observer design for Sugeno systems with incremental quadratic nonlinearity in the consequent

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Abdelmalek, I., Golea, N. and Hadjili, M.L. (2007). A new fuzzy Lyapunov approach to non-quadratic stabilization of Takagi-Sugeno fuzzy models, International Journal of Applied Mathematics and Computer Science 17(1): 39-51, DOI: 10.2478/v10006-007-0005-4.10.2478/v10006-007-0005-4Search in Google Scholar

Açikmese, A.B. and Corless, M. (2011). Observers for systems with nonlinearities satisfying incremental quadratic constraints, Automatica 47(7): 1339-1348.10.1016/j.automatica.2011.02.017Search in Google Scholar

Asemani, M.H. and Majd, V.J. (2013). A robust observer-based controller design for uncertain T-S fuzzy systems with unknown premise variables via LMI, Fuzzy Sets and Systems 212: 21-40.10.1016/j.fss.2012.07.008Search in Google Scholar

Bernal, M. and Huˇsek, P. (2005). Non-quadratic performance design for Takagi-Sugeno fuzzy systems, International Journal of Applied Mathematics and Computer Science 15(3): 383-391.Search in Google Scholar

Boyd, S., Ghaoui, L.E., Feron, E. and Balakrishnan, V. (1994). Linear Matrix Inequalities in System and Control Theory, SIAM Studies in Applied Mathematics, Philadelphia, PA.10.1137/1.9781611970777Search in Google Scholar

Chadli, M. and Guerra, T.M. (2012). LMI solution for robust static output feedback control of discrete Takagi-Sugeno fuzzy models, IEEE Transactions on Fuzzy Systems 20(6): 1160-1165.10.1109/TFUZZ.2012.2196048Search in Google Scholar

Dong, J., Wang, Y. and Yang, G.H. (2011). H∞ and mixed H2/H∞ control of discrete-time T-S fuzzy systems with local nonlinear models,, Fuzzy Sets and Systems 164(1): 1-24.10.1016/j.fss.2010.09.014Search in Google Scholar

Dong, J., Wang, Y. and Yang, G.H. (2010). Output feedback fuzzy controller design with local nonlinear feedback laws for discrete-time nonlinear systems, IEEE Transactions on Systems, Man and Cybernetics, B: Cybernetics 40(6): 1447-1459.10.1109/TSMCB.2009.203964220172831Search in Google Scholar

Faria, F.A., Silva, G.N. and Oliveira, V.A. (2012). Reducing the conservatism of LMI-based stabilisation conditions for T-S fuzzy systems using fuzzy Lyapunov functions, International Journal of Systems Science 44(10): 1956-1969, DOI: 10.1080/00207721.2012.670307.10.1080/00207721.2012.670307Search in Google Scholar

Guerra, T.M. and Bernal, M. (2012). Strategies to exploit non-quadratic local stability analysis, International Journal of Fuzzy Systems 14(3): 372-379.Search in Google Scholar

Guerra, T.M., Bernal, M., Guelton, K. and Labiod, S. (2012). Non-quadratic local stabilization for continuous-time Takagi-Sugeno models, Fuzzy Sets and Systems 201(16): 40-54.10.1016/j.fss.2011.12.003Search in Google Scholar

Guerra, T.M., Kruszewski, A. and Lauber, J. (2009). Discrete Tagaki-Sugeno models for control: Where are we?, Annual Reviews in Control 33(1): 37-47.10.1016/j.arcontrol.2009.01.004Search in Google Scholar

Ichalal, D., Marx, B., Ragot, J. and Maquin, D. (2012). New fault tolerant control strategies for nonlinear Takagi-Sugeno systems, International Journal of Applied Mathematics and Computer Science 22(1): 197-210, DOI: 10.2478/v10006-012-0015-8.10.2478/v10006-012-0015-8Search in Google Scholar

Karagiannis, D., Jiang, Z., Ortega, R. and Astolfi, A. (2005). Output-feedback stabilization of a class of uncertain non-minimum phase nonlinear systems, Automatica 41(9): 1609-1615.10.1016/j.automatica.2005.04.013Search in Google Scholar

Löfberg, J. (2004). Yalmip: A toolbox for modeling and optimization in MATLAB, IEEE International Symposium on Computer Aided Control Systems Design, Taipei, Taiwan, pp. 284-289.Search in Google Scholar

Lee, C. (2004). Stabilization of nonlinear non-minimum phase system: Adaptive parallel approach using recurrent fuzzy neural network, IEEE Transactions on Systems, Man and Cybernetics, Part B 34(2): 1075-1088.10.1109/TSMCB.2003.82059215376853Search in Google Scholar

Manai, Y. and Benrejeb, M. (2011). New condition of stabilization for continuous Takagi-Sugeno fuzzy system based on fuzzy Lyapunov function, International Journal of Control and Automation 4(3): 61-64.10.1109/CCCA.2011.6031521Search in Google Scholar

Mozelli, L.A., Palhares, R.M. and Avellar, G.S.C. (2009). A systematic approach to improve multiple Lyapunov function stability and stabilization conditions for fuzzy systems, Information Sciences 179(8): 1149-1162.10.1016/j.ins.2008.12.002Search in Google Scholar

Rajesh, R. and Kaimal, M.R. (2007). T-S fuzzy model with nonlinear consequence and PDC controller for a class of nonlinear control systems, Applied Soft Computing 7(3): 772-782.10.1016/j.asoc.2006.01.014Search in Google Scholar

Rhee, B.J. and Won, S. (2006). A new fuzzy Lyapunov function approach for a Takagi-Sugeno fuzzy control system design, Fuzzy Sets and Systems 157(9): 1211-1228.10.1016/j.fss.2005.12.020Search in Google Scholar

Sala, A. (2009). On the conservativeness of fuzzy and fuzzy-polynomial control of nonlinear systems, Annual Reviews in Control 33(1): 48-58.10.1016/j.arcontrol.2009.02.001Search in Google Scholar

Sala, A. and Arino, C. (2009). Polynomial fuzzy models for nonlinear control, a Taylor series approach, IEEE Transactions on Fuzzy Systems 17(6): 1284-1295.10.1109/TFUZZ.2009.2029235Search in Google Scholar

Tanaka, K. and Wang, H.O. (2001). Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach, John Wiley and Sons, Inc., New York, NY.Search in Google Scholar

Tseng, C.S., Chen, B.S. and Li, Y.F. (2009). Robust fuzzy observer-based fuzzy control design for nonlinear systems with persistent bounded disturbances: A novel decoupled approach, Fuzzy Sets and Systems 160(19): 2824-2843.10.1016/j.fss.2009.02.006Search in Google Scholar

Tuan, H.D., Apkarian, P., Narikiyo, T. and Yamamoto, Y. (2001). Parameterized linear matrix inequality techniques in fuzzy control system design, IEEE Transactions on Fuzzy Systems 9(2): 324-332.10.1109/91.919253Search in Google Scholar

Xu, D., Jiang, B. and Shi, P. (2012). Nonlinear actuator fault estimation observer: An inverse system approach via a T-S fuzzy model, International Journal of Applied Mathematics and Computer Science 22(1): 183-196, DOI: 10.2478/v10006-012-0014-9.10.2478/v10006-012-0014-9Search in Google Scholar

Yoneyama, J. (2009). H∞ filtering for fuzzy systems with immeasurable premise variables: An uncertain system approach, Fuzzy Sets and Systems 160(12): 1738-1748 10.1016/j.fss.2008.09.012Search in Google Scholar

ISSN:
1641-876X
Lingua:
Inglese
Frequenza di pubblicazione:
4 volte all'anno
Argomenti della rivista:
Mathematics, Applied Mathematics