Title :
Fuzzy model predictive control: techniques, stability issues, and examples
Author :
Nounou, Hazem N. ; Passino, Kevin M.
Author_Institution :
Dept. of Electr. Eng., Ohio State Univ., Columbus, OH, USA
Abstract :
Fuzzy model predictive control (FMPC) algorithms presented here are model-based control schemes in which the models used for prediction are Takagi-Sugeno fuzzy systems (TSFS). Three approaches to FMPC design are discussed. The fuzzy model in the first approach can be represented as a time-varying affine model that is used for control. In the second approach, the fuzzy system is a convex combination of multiple affine models, where the control is a convex combination of multiple controllers. Lastly, the control of the third algorithm is obtained when only the model with the highest certainty is used in the design. Also, we extend the idea to have an adaptive controller for the first algorithm, where the parameters of the fuzzy model are updated online
Keywords :
control system synthesis; fuzzy control; model reference adaptive control systems; predictive control; stability; time-varying systems; FMPC; TSFS; Takagi-Sugeno fuzzy systems; fuzzy model predictive control; model-based control schemes; multiple affine models; multiple controllers; stability; time-varying affine model; Adaptive control; Algorithm design and analysis; Fuzzy control; Fuzzy systems; Prediction algorithms; Predictive control; Predictive models; Programmable control; Stability; Takagi-Sugeno model;
Conference_Titel :
Intelligent Control/Intelligent Systems and Semiotics, 1999. Proceedings of the 1999 IEEE International Symposium on
Conference_Location :
Cambridge, MA
Print_ISBN :
0-7803-5665-9
DOI :
10.1109/ISIC.1999.796692
