Hierarchical aggregation of multiple fuzzy controllers for global complex control problems |
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| Affiliation: | 1. CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application Systems, University of Science and Technology of China, Hefei, China;2. USTC-Birmingham Joint Research Institute in Intelligent Computation and Its Applications (UBRI), University of Science and Technology of China, Hefei, China;1. Department of ICE, Kalasalingam University, India;2. Department of Electronics and Communication Engineering, Kalasalingam University, India;3. Gopalan College of Engineering and Management, Bangalore, India;4. KLN College of Engineering, India |
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| Abstract: | In this paper, we illustrate a proposed method for control that combines the outputs of several individual controllers to improve global control of complex nonlinear plants. In the first part of this paper, we illustrate the proposed method that consists of two levels, where in the top level a fuzzy system represents a superior control that is designed for adjusting the behavior of the individual fuzzy controllers at the lower level. To test the approach, we consider the problem of flight control because it requires several individual controllers. Also a comparison is performed, where the hierarchical control strategy is compared with a simple control approach using the t student test. In this paper, we show that the proposed method outperforms the conventional fuzzy control approach. In the optimal design of the proposed control architecture a genetic algorithm was also applied to tune the parameters of the fuzzy systems in an optimal fashion. |
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| Keywords: | Fuzzy systems Genetic algorithms Fuzzy control Hierarchical fuzzy control |
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