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Automated design of multi-mode fuzzy controllers

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dc.contributor.advisor Du Plessis JJ en
dc.contributor.author Hugo EM en
dc.date.accessioned 2016-09-22T08:32:18Z
dc.date.available 2016-09-22T08:32:18Z
dc.date.submitted 2000 en
dc.identifier.uri http://hdl.handle.net/20.500.11892/28810
dc.description.abstract A standard fuzzy logic controller is not robust enough to guarantee consistent closed-loop performance for highly non-linear plants. A finely tuned closed-loop response loses relevance as the system dynamics change with operating conditions. The self-adaptive fuzzy logic controller can track changes in the system parameters and modify the controller parameters accordingly. In most cases, self-adaptive fuzzy logic controllers are complex and rely on some form of mathematical plant model. The multi-mode fuzzy logic controller extends the working range of a standard fuzzy logic controller by incorporating knowledge of the non-linear system dynamics into the control rule-base. The complexity of the controller and difficulty finding control rules have limited the application of multi-mode fuzzy logic controllers. An automated design algorithm is proposed for the design of a multi-mode control rule-base using qualitative plant knowledge. The design algorithm is cost-functioned. The closed-loop response, local to a domain of the non-linear stale space, can he tuned by manipulation of the cost function weights. Global closed-loop response tuning can he done by manipulation of the controller input gains. Alternatively, a self-learning or self-adaptive algorithm can be used in a model reference adaptive control architecture to optimise the control rule-base. Control rules responsible for unacceptable closed-loop performance are identified and their consequences modified. The validity of the proposed design method is evaluated in Five case studies. The case studies illustrate the advantages of the multi-mode fuzzy logic controller. The results indicate that the proposed self-adaptive algorithm can be used to optimise a rule-base given a required closed-loop specification. If the system does not conform to the model reference adaptive architecture then the intuitive nature of the cost function based design algorithm proves to be an effective method for rule-base tuning. en
dc.language English en
dc.subject Electrical and Electronic engineering en
dc.title Automated design of multi-mode fuzzy controllers en
dc.type Doctoral degree en
dc.description.degree PhD en


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