Abstract
In this paper, we propose a novel fuzzy logic controller, called linguistic hedge fuzzy logic controller, to simplify the membership function constructions and the rule developments. The design methodology of linguistic hedge fuzzy logic controller is a hybrid model based on the concepts of the linguistic hedges and the genetic algorithms. The linguistic hedge operators are used to adjust the shape of the system membership functions dynamically, and can speed up the control result to fit the system demand. The genetic algorithms are adopted to search the optimal linguistic hedge combination in the linguistic hedge module. According to the proposed methodology, the linguistic hedge fuzzy logic controller has the following advantages: 1) it needs only the simple-shape membership functions rather than the carefully designed ones for characterizing the related variables; 2) it is sufficient to adopt a fewer number of rules for inference; 3) the rules are developed intuitionally without heavily depending on the endeavor of experts; 4) the linguistic hedge module associated with the genetic algorithm enables it to be adaptive; 5) it performs better than the conventional fuzzy logic controllers do; and 6) it can be realized with low design complexity and small hardware overhead. Furthermore, the proposed approach has been applied to design three well-known nonlinear systems. The simulation and experimental results demonstrate the effectiveness of this design.
Original language | English |
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Pages (from-to) | 32-53 |
Number of pages | 22 |
Journal | IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics |
Volume | 31 |
Issue number | 1 |
DOIs | |
Publication status | Published - 2001 Feb |
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Software
- Information Systems
- Human-Computer Interaction
- Computer Science Applications
- Electrical and Electronic Engineering