A differential flatness theory approach to observer-based adaptive fuzzy control of MIMO nonlinear dynamical systems

Nonlinear Dynamics

Volumn 76, Issue 2, 2014, Pages 1335-1354

  Rigatos, Gerasimos G ^a  

^a INDUSTRIAL SYSTEMS INSTITUTE   (Greece)

Author keywords

Adaptive fuzzy control; Advanced robotic systems; Differential flatness theory; Lyapunov stability; MIMO dynamical systems; Observer based control

Indexed keywords

ALGORITHMS; DYNAMICAL SYSTEMS; MIMO SYSTEMS; NONLINEAR DYNAMICAL SYSTEMS; SYSTEM STABILITY;

ADAPTIVE FUZZY CONTROL; DIFFERENTIAL FLATNESS THEORIES; LYAPUNOV STABILITY; MIMO DYNAMICAL SYSTEMS; OBSERVER BASED CONTROL; ROBOTIC SYSTEMS;

FUZZY CONTROL;

EID: 84899658040     PISSN: 0924090X     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11071-013-1213-0     Document Type: Article

References (46)

1. Rigatos, G.G.: Adaptive fuzzy control for field-oriented induction motor drives, Neural Comput. Appl. 21(1), 9-23 (2012)
2. Rigatos, G.G.: Flatness-based adaptive fuzzy control for nonlinear dynamical systems, AIM 2011, IEEE/ASME, International Conference on Advanced Intelligent Mechatronics, Budapest, Hungary, July (2011)
3. Rigatos, G.G.: Adaptive fuzzy control of MIMO dynamical systems using differential flatness theory. IEEE ISIE 2012, 21st International Symposium on Industrial Electronics. Hangzhou, China (May 2012)
4. Wang, L.X.: Adaptive Fuzzy Systems and Control: Design and Stability Analysis. Prentice Hall, Englewood Cliffs (1994)
5. Wang, L.X.: A Course in Fuzzy Systems and Control. Prentice-Hall, Englewood Cliffs (1998)
6. Tong, S.; Li, H.-X.; Chen, G.: Adaptive fuzzy decentralized control for a class of large-scale nonlinear systems. IEEE Trans. Syst. Cybern. B 34(1), 770-775 (2004)
7. Li, H.X.; Tong, S.: A hybrid adaptive fuzzy control for a class of nonlinear MIMO systems. IEEE Trans. Fuzzy Syst. 11(1), 24-35 (2003)
8. Song, T.; Bin, C.; Wang, Y.: Fuzzy adaptive output feedback control for MIMO nonlinear systems. Fuzzy Sets Syst. 156, 285-299 (2005)
9. Chen, C.S.: Dynamic structure adaptive neural fuzzy control for MIMO uncertain nonlinear systems. Inf. Sci. 179, 2676-2688 (2009)
10. Tong, S.; Li, Y.: Observer-based adaptive control for strict-feedback nonlinear systems. Fuzzy Sets Syst. 160, 1749-1764 (2009)
11. Chen, C.H.; Lin, C.M.; Chen, T.Y.: Intelligent adaptive control for MIMO uncertain nonlinear systems. Expert Syst. Appl. 35, 865-877 (2008)
12. Suresh, S.; Kannan, N.; Sundararajan, N.; Saratchandran, P.: Neural adaptive control for vibration suppression in composite fin-tip of aircraft. Int. J. Neural Syst. 18(3), 219-231 (2008)
13. ∞ controllers for discrete-time nonlinear systems based on unified models. Int. J. Neural Syst. 18(5), 443-452 (2008)
14. Alanis, A.Y.; Sanchez, E.N.; Ricalde, R.J.; Perez-Cisneros, M.A.: Discrete-time reduced order neural observers for uncertain nonlinear systems. Int. J. Neural Syst. 20(1), 29-38 (2010)
15. Puscasu, G.; Codres, B.: Nonlinear system identification and control based on modular neural networks. Int. J. Neural Syst. 21(4), 319-334 (2011)
16. Lin, C.M.; Ting, A.B.; Hsu, C.F.; Chung, C.M.: Adaptive control for MIMO uncertain nonlinear systems using recurrent wavelet neural network. Int. J. Neural Syst. 21(6), 37-50 (2011)
17. Lin, Y.J.; Wang, W.: Adaptive fuzzy control for a class of uncertain non-affine nonlinear systems. Inf Sci 177, 3901-3917 (2007)
18. Tong, S.; Chen, B.; Wang, Y.: Fuzzy adaptive output feedback control for MIMO nonlinear systems. Fuzzy Sets Syst. 156, 285-299 (2005)
19. Chiu, C.S.: Mixed feedforward/feedback adaptive fuzzy control for a class of MIMO nonlinear systems. IEEE Trans. Fuzzy Syst. 14(6), 716-727 (2006)
20. Purwar, S.; Kar, I.N.; Jha, A.N.: Adaptive control of robot manipulators using fuzzy logic systems under actuator constraints. Fuzzy Sets Syst. 152, 651-664 (2004)
21. Gao, Y.; Er, M.J.: Online adaptive fuzzy neural identification and control of a class of MIMO nonlinear systems. IEEE Trans. Fuzzy Syst. 11(4), 462-477 (2003)
22. Chen, B.; Liu, X.; Tong, S.: Adaptive fuzzy output tracking control of MIMO nonlinear uncertain systems. IEEE Trans. Fuzzy Syst. 15(2), 287-300 (2007)
23. Chen, C.S.: Robust self-organising neural-fuzzy control with uncertainty observer for MIMO nonlinear systems. IEEE Trans. Fuzzy Syst. 19(4), 694-706 (2011)
24. Li, T.S.; Tong, S.C.; Feng, G.: A novel robust adaptive-fuzzy-tracking control for a class of nonlinear multi-input multi-output systems. IEEE Trans. Fuzzy Syst. 18(1), 150-160 (2010)
25. Rudolph, J.: Flatness based control of distributed Parameter systems: examples and computer exercises from various technological domains. Shaker, Aachen (2003)
26. Sira-Ramirez, H.; Agrawal, S.: Differentially Flat Systems. Marcel Dekker, New York (2004)
27. Rigatos, G.G.: Modelling and Control for Intelligent Industrial Systems: Adaptive Algorithms in Robotcs and Industrial Engineering. Springer, Berlin (2011)
28. Lévine, J.: On necessary and sufficient conditions for differential flatness. Appl. Algebra Eng. Commun. Comput. 22(1), 47-90 (2011)
29. Hagenmeyer, V.; Delaleau, E.: Robustness analysis of exact feedforward linearization based on differential flatness. Automatica 39, 1941-1946 (2003)
30. Hagenmeyer, V.; Delaleau, E.: Robustness analysis with respect to exogenous perturbations for flatness-based exact feedforward linearization. IEEE Trans. Autom. Control 55(3), 727-731 (2010)
31. Fliess, M.; Mounier, H.: Tracking control and π -freeness of infinite dimensional linear systems, In: Picci, G.; Gilliam, D.S. (eds.), Dynamical Systems, Control, Coding and Computer Vision, vol. 258, pp. 41-68. Birkhaüser (1999)
32. Rigatos, G.G.: Extended Kalman and Particle Filtering for sensor fusion in motion control of mobile robots. Math. Comput. Simul. 81(3), 590-607 (2010)
33. Villagra, J.; d'Andrea-Novel, B.; Mounier, H.; Pengov, M.: Flatness-based vehicle steering control strategy with SDRE feedback gains tuned via a sensitivity approach. IEEE Trans. Control Syst. Technol. 15, 554-565 (2007)
34. Laroche, B.; Martin, P.; Petit, N.: Commande par platitude: Equations différentielles ordinaires et aux derivées partielles. Ecole Nationale Supérieure des Techniques Avancées, Paris (2007)
35. Martin, Ph.; Rouchon, P.: Systèmes plats: planification et suivi des trajectoires. Journées X-UPS, École des Mines de Paris, Centre Automatique et Systèmes, Mai (1999)
36. ∞ tracking of SISO nonlinear systems. Int. J. Neural Syst. 18(4), 1-16 (2008)
37. Rigatos, G.G.; Tzafestas, S.G.: Adaptive fuzzy control for the ship steering problem. J. Mech. 16(6), 479-489 (2006)
38. Rigatos, G.G.: Adaptive fuzzy control of DC motors using state and output feedback. Electr. Power Syst. Res. 79(11), 1579-1592 (2009)
39. Bououden, S.; Boutat, D.; Zheng, G.; Barbot, J.P.; Kratz, F.: A triangular canonical form for a class of 0-flat nonlinear systems. Int. J. Control Taylor Francis 84(2), 261-269 (2011)
40. Rigatos, G.G.: A derivative-free Kalman Filtering approach to state estimation-based control of nonlinear dynamical systems. IEEE Trans. Ind. Electron. 59(10), 3987-3997 (2012)
41. Kurylowicz, A.; Jaworska, I.; Tzafestas, S.G.: Robust stabilizing control: an overview, applied control: current trends and modern methodologies. In Tzafestas S.G. (ed.), Marcel Dekker, pp. 289-324 (1993)
42. Lublin, L.; Athans, M.: An experimental comparison of and designs for interferometer testbed. In: Francis, B.; Tannenbaum, A. (eds.) Lectures Notes in Control and Information Sciences: Feedback Control, Nonlinear Systems and Complexity. Springer, pp. 150-172 (1995)
43. ∞ control problems. IEEE Trans. Autom. Control 34, 831-847 (1989)
44. Yousef, H.A.; Hamdy, M.; Shafiq, M.: Flatness-based adaptive fuzzy output tracking excitation control for power system generators. J. Franklin Inst. 350, 2334-2353 (2013)
45. Yang, Y.; Zhou, C.; Jia, X.: Robust adaptive fuzzy control and its application to ship roll stabilization. Inf. Sci. 142, 177-194 (2002)
46. Qi, R.; Tao, G.; Tan, C.; Yao, X.: Adaptive control of discrete-time state-space TS fuzzy systems with general relative degree. Fuzzy Sets Syst. 217, 22-40 (2013)