Neuro-fuzzy adaptive control based on dynamic inversion for robotic manipulators

Fuzzy Sets and Systems

Volumn 134, Issue 1, 2003, Pages 117-133

  Sun, Fuchun ^a,b   Sun, Zengqi ^a   Li, Lei ^c   Li, Han Xiong ^d  

^a State Key Laboratory of Tribology   (China)

^b SHENYANG INSTITUTE OF AUTOMATION   (China)

^c TSINGHUA UNIVERSITY   (China)

^d CITY UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

Adaptive control; Dynamic inversion; Fuzzy clustering; Neuro fuzzy systems; Robotics

Indexed keywords

ADAPTIVE CONTROL SYSTEMS; APPROXIMATION THEORY; COMPUTER SIMULATION; ERROR ANALYSIS; FUZZY CONTROL; LEARNING ALGORITHMS; MANIPULATORS; NEURAL NETWORKS; TRAJECTORIES;

FUZZY CLUSTERING;

ROBOTICS;

EID: 0037448737     PISSN: 01650114     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0165-0114(02)00233-6     Document Type: Conference Paper

References (23)

1. Babuska R., Verbruggen H.B. Constructing fuzzy models by product space clustering. Hellendoorn H., Driankov D. Fuzzy Model Identification - Selected Approaches. 1997;53-90 Springer, Berlin.
2. Cao S.G., Rees N.W., Feng G. Quadratic stability analysis and design of continuous-time fuzzy control systems. Internat. J. Systems Sci. 27:1996;193-203.
3. ∞ control of uncertain fuzzy continuous-time systems Fuzzy Sets and Systems. 115:2000;171-190.
4. Chen D.G., Paden B. Stable inversion of nonlinear nonminimum phase systems. Internat. J. Control. 64:1996;81-97.
5. Jagannathan S. Adaptive fuzzy logic control of feedback linearizable discrete-time dynamical systems under persistence of excitation. Automatica. 34:1998;1295-1310.
6. Johansen T.A., Shorten R., Murray-Smith R. On the interpretation and identification of dynamic Takagi-Sugeno fuzzy models. IEEE Trans. Fuzzy Systems. 8:2000;297-313.
7. Juang C.F., Lin C.T. A recurrent self-organizing neural fuzzy inference network. IEEE Trans. Neural Networks. 10:1999;828-845.
8. Kim E., Park M., Ji S., Park M. A new approach to fuzzy modeling. IEEE Trans. Fuzzy Systems. 5:1997;328-336.
9. Lee J.X., Vukovich G. The dynamic fuzzy logic system. nonlinear system identification and application to robotic manipulators J. Robotic Systems. 14:1997;391-405.
10. Lin C.T., Lee C.S.G. Neural Fuzzy Systems. A Neural-Fuzzy Synergism to Intelligent Systems:1996;Prentice-Hall, Englewood Cliffs, NJ.
11. Poznyak A.S., Yu W., Sanchez E.N., Perez J.P. Nonlinear adaptive trajectory tracking using dynamical neural networks. IEEE Trans. Neural Networks. 10:1999;1402-1411.
12. Rovithakis G.A. Tracking control of multi-input affine nonlinear dynamical systems with unknown nonlinearities using dynamical neural networks. IEEE Trans. Systems Man Cybernet. Part B. 29:1999;179-189.
13. Rovithakis G.A., Christodoulou M.A. Adaptive control of unknown plants using dynamical neural networks. IEEE Trans. Systems Man Cybernet. 24:1994;400-412.
14. Shorten R., Murray-Smith R., Bjorgan R., Gollee H. On the interpretation of local models in blended multiple model structure. Internat. J. Control. 72:1999;620-628.
15. Slotine J.J.E. Sliding mode controller design for nonlinear systems. Internat. J. Control. 40:1984;421-434.
16. Spooner J.T., Passino K.M. Stable adaptive control using fuzzy systems and neural networks. IEEE Trans. Fuzzy Systems. 4:1996;339-359.
17. Sun F.C., Sun Z.Q., Feng G. An adaptive fuzzy controller based on sliding mode for robot manipulators. IEEE Trans. Systems Man Cybernet. Part B. 29:1999;661-667.
18. Sun F.C., Sun Z.Q., Li N., Zhang L.B. Robot adaptive control based on dynamic inversion using dynamical neural networks. Mach. Intell. Robot Control. 1:1999;71-78.
19. Sun F.C., Sun Z.Q., Woo P.Y. Stable neural network-based adaptive control for sampled-data nonlinear systems. IEEE Trans. Neural Networks. 9:1998;956-968.
20. Sun F.C., Sun Z.Q., Zhang R.J., Chen Y.B. Neural adaptive tracking controller for robot manipulators with unknown dynamics. IEEE Proc. Part D. 147:2000;366-370.
21. Vidyasagar M. Nonlinear Systems Analysis. 1993;Prentice-Hall, Englewood Cliffs, NJ.
22. H.O. Wang, J. Li, D. Niemann, K. Tanaka, T-S model with linear rule consequence and PDC controller: a universal framework for nonlinear control systems, Proc. IEEE Internat. Conf. on Fuzzy Systems, 2000, pp. 549-554.
23. Wang H.O., Tanaka K., Griffin M.F. An approach to fuzzy control of nonlinear systems. stability and design issues IEEE Trans. Fuzzy Systems. 4:1996;14-23.