Hierarchical Genetic Algorithms for Type-2 Fuzzy System Optimization Applied to Pattern Recognition and Fuzzy Control

2014 ◽  
pp. 19-35 ◽  
Author(s):  
Daniela Sánchez ◽  
Patricia Melin
Keyword(s):  
Pattern Recognition ◽  
Genetic Algorithms ◽  
Fuzzy Control ◽  
Fuzzy System ◽  
System Optimization

scholarly journals Adaptive Backstepping Fuzzy Control Based on Type-2 Fuzzy System

2012 ◽  
Vol 2012 ◽  
pp. 1-27 ◽  
Author(s):  
Ll Yi-Min ◽  
Yue Yang ◽  
Li Li
Keyword(s):  
Fuzzy Control ◽  
Fuzzy System ◽  
External Disturbance ◽  
Approximation Error ◽  
Adaptive Backstepping ◽  
Control Approach ◽  
Type Reduction ◽  
Adaptive Laws

A novel indirect adaptive backstepping control approach based on type-2 fuzzy system is developed for a class of nonlinear systems. This approach adopts type-2 fuzzy system instead of type-1 fuzzy system to approximate the unknown functions. With type-reduction, the type-2 fuzzy system is replaced by the average of two type-1 fuzzy systems. Ultimately, the adaptive laws, by means of backstepping design technique, will be developed to adjust the parameters to attenuate the approximation error and external disturbance. According to stability theorem, it is proved that the proposed Type-2 Adaptive Backstepping Fuzzy Control (T2ABFC) approach can guarantee global stability of closed-loop system and ensure all the signals bounded. Compared with existing Type-1 Adaptive Backstepping Fuzzy Control (T1ABFC), as the advantages of handling numerical and linguistic uncertainties, T2ABFC has the potential to produce better performances in many respects, such as stability and resistance to disturbances. Finally, a biological simulation example is provided to illustrate the feasibility of control scheme proposed in this paper.

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