A fuzzy-neural multi-model for mechanical systems identification and control

Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)

Volumn 2972, Issue , 2004, Pages 774-783

  Baruch, Ieroham S ^a   Beltran, Rafael L ^a   Olivares, Jose Luis ^a   Garrido, Ruben ^a  

^a DEPARTAMENTO DE FÍSICA   (Mexico)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SIMULATION; CONVERGENCE OF NUMERICAL METHODS; FRICTION; FUZZY CONTROL; KNOWLEDGE BASED SYSTEMS; NEURAL NETWORKS; PARAMETER ESTIMATION; ARTIFICIAL INTELLIGENCE; COMPLEX NETWORKS; CONTROL SYSTEMS; CONTROL THEORY; FUZZY INFERENCE; FUZZY LOGIC; RECURRENT NEURAL NETWORKS;

AUTOREGRESSIVE MODEL; MECHANICAL SYSTEMS; PLANT MODELS; TAP-DELAYS; ADAPTIVE TRAJECTORY; FUZZY RULE BASED; FUZZY-NEURAL; LOCAL CONTROL; LOCAL RECURRENT NEURAL NETWORKS; MECHANICAL PLANTS; SYSTEMS IDENTIFICATION;

IDENTIFICATION (CONTROL SYSTEMS); ADAPTIVE CONTROL SYSTEMS;

EID: 9444227613     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/978-3-540-24694-7_80     Document Type: Conference Paper

References (9)

1. Narendra K. S., Parthasarathy K.: Identification and Control of Dynamic Systems using Neural Networks. IEEE Transactions on NNs, 1 (1990), 4-27
2. Sastry P. S., Santharam G., Unnikrishnan K.P.: Memory Networks for Identification and Control of Dynamical Systems. IEEE Transactions on NNs, 5 (1994), 306-320.
3. Hunt K.J., Sbarbaro D., Zbikowski R., Gawthrop P. J.: Neural Network for Control Systems-A Survey. Automatica, 28 (1992), 1083-1112.
4. Baruch I., Flores J.M., Nava F., Ramirez I.R., Nenkova B.: An Adavanced Neural Network Topology and Learning, Applied for Identification and Control of a D.C. Motor. Proc. of the First Int. IEEE Symposium on Intelligent Systems, Sept. (2002), Varna, Bulgaria, 289-295.
5. Baruch I., Gortcheva E.: Fuzzy Neural Model for Nonlinear Systems Identification, Proc. of the IFAC Worshop on Algorithms and Architectures for Real-Time Control, AARTC'98, 15-17 April, (1998), Cancun, Mexico, 283-288.
6. Baruch I., Garrido R., Mitev A., Nenkova B.: A Neural Network Approach for Stick-Slip Model Identification. Proc. of the 5-th Int. Conf. on Engineering Applications of Neural Networks, EANN'99, 13-15 Sept, (1999), Warsaw, Poland, 183-188.
7. Baruch, I., Flores, J.M., Martinez, J.C., Nenkova, B.: Fuzzy- Neural Models for Real-Time Identification and control of a Mechanical System. (St.Cerri, D.Dochev-Eds.) Artificial Intelligence: Methodology, Systems and Applications, 9-th International conference, AIMSA 2000, Varna, Bulgaria, September 2000. Lecture Notes in Artificial Intelligence 1904, Springer, Berlin, (2000), 292-300.
8. Mastorocostas P.A., Theocharis J.B.: A Recurrent Fuzzy-Neural Model for Dynamic System Identification. IEEE Trans. on SMC - Part B: Cybernetics, 32 (2002), 176-190.
9. S.W. Lee, J.H. Kim.: Robust adaptive stick-slip friction compensation. IEEE Trans. on Ind. Electr., 42 (1995), 474-479.