Ensuring monotonic gain characteristics in estimated models by fuzzy model structures

Automatica

Volumn 36, Issue 2, 2000, Pages 311-317

  Lindskog, Peter ^a,b   Ljung, Lennart ^a,c,d,e,f,g  

^a LINKÖPING UNIVERSITY   (Sweden)

^b Atero AB   (Sweden)

^c Department of Automatic Control ^*  (Sweden)

^d Competence Center Information Systems for Industrial Control and Supervision ^*  (Sweden)

^e IEEE   (Sweden)

^f The Royal Swedish Academy of Engineering Sciences (IVA)   (Sweden)

^g ROYAL SWEDISH ACADEMY OF SCIENCES   (Sweden)

Author keywords

[No Author keywords available]

Indexed keywords

CONSTRAINT THEORY; FUZZY SETS; MATHEMATICAL MODELS; MEMBERSHIP FUNCTIONS; PARAMETER ESTIMATION; STEP RESPONSE;

FUZZY MODELING; MONOTONICITY; PARAMETRIC CONSTRAINTS;

NONLINEAR CONTROL SYSTEMS;

EID: 0034140584     PISSN: 00051098     EISSN: None     Source Type: None    
DOI: 10.1016/S0005-1098(99)00154-5     Document Type: Article

References (12)

1. Bohlin, T. (1991). Interactive system identification: Prospects and pitfalls. Berlin: Springer.
2. Driankov, D., Hellendoorn, H., & Reinfrank, H. (1993). An introduction to fuzzy control., Berlin: Springer.
3. Fletcher, R. (1987). Practical methods of optimization. New York: Wiley.
4. Koivisto, H. (1995). A practical approach to model based neural network control. Ph.D. Thesis 170, Tampere University of Technology, Tampere, Finland.
5. Lee, C. C. (1990). Fuzzy logic in control systems: fuzzy logic controller - parts I and II. IEEE Transactions on Systems, Man, and Cybernetics, SMC-20(2), 404-435.
6. Lindskog, P. (1996). Methods, algorithms and tools for system identification based on prior knowledge. Ph.D. Thesis 436, Department of Electrical Engineering, Linköping University, Linköping, Sweden.
7. Ljung, L. (1999). System identification - theory for the user (2nd ed.). Upper Saddle River, NJ: Prentice-Hall.
8. RogerJang, J.-S., & Sun, C.-T. (1995). Neuro-fuzzy modeling and control. Proceedings of the IEEE, 83(3), 378-406.
9. Scales, L. E. (1985). Introduction to non-linear optimization, Computer Science Series. Macmillan.
10. Sjöberg, J., Zhang, Q., Ljung, L., Benveniste, A., Delyon, B., Glorennec, P.-Y., Hjalmarsson, H., & Juditsky, A. (1995). Non linear black-box modeling in system identification: a unified overview. Automatica, 31(12), 1691-1724.
11. Takagi, T., & Sugeno, M. (1985). Fuzzy identification of systems and its applications to modeling and control. IEEE Transactions on Systems, Man, and Cybernetics, SMC-15(1), 116-132.
12. Wang, L.-X. (1994). Adaptive fuzzy systems and control: Design and stability analysis. Englewood Cliffs, NJ: Prentice-Hall.