Performance Criteria: Classical and Fuzzy Design

The design of a control system generally involves different steps. First, the system to be controlled is studied in order to decide about the types of sensors and actuators to be used and their proper insertion in the system. Second, a model of the resulting system is derived using first principles or an identification procedure. The identification of a system involves usually the simplification and validation of the obtained model. Once the model is derived, the design specifications must be established, and the controller meeting the desired specifications can be designed. With the model and the controller, the resulting control system can be simulated and implemented (Doyle et al., 1992).

[1]  Robert Babuska,et al.  Some Computational Issues in Fuzzy Predictive Control , 1996 .

[2]  Weiping Li,et al.  Applied Nonlinear Control , 1991 .

[3]  David W. Clarke,et al.  Generalized predictive control - Part I. The basic algorithm , 1987, Autom..

[4]  J. Richalet,et al.  Industrial applications of model based predictive control , 1993, Autom..

[5]  R. Yager.  On a general class of fuzzy connectives , 1980 .

[6]  Richard Bellman,et al.  Decision-making in fuzzy environment , 2012 .

[7]  Bruce A. Francis,et al.  Feedback Control Theory , 1992 .

[8]  Ebrahim Mamdani,et al.  Applications of fuzzy algorithms for control of a simple dynamic plant , 1974 .

[9]  Stephen P. Boyd,et al.  Linear controller design: limits of performance , 1991 .

[10]  Robert Babuska,et al.  Fuzzy predictive control applied to an air-conditioning system , 1997 .

[11]  Uzay Kaymak,et al.  Branch-and-Bound Optimization in Predictive Control with Fuzzy Decision Functions , 1997 .

[12]  J. Doyle,et al.  Robust and optimal control , 1995, Proceedings of 35th IEEE Conference on Decision and Control.

[13]  Uzay Kaymak,et al.  Convex optimization in fuzzy predictive control , 1996, Proceedings of 35th IEEE Conference on Decision and Control.

[14]  J. Baldwin,et al.  Dynamic programming for fuzzy systems with fuzzy environment , 1982 .

[15]  George J. Klir,et al.  Fuzzy sets and fuzzy logic - theory and applications , 1995 .

[16]  Philip E. Gill,et al.  Practical optimization , 1981 .