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This paper outlines the cognitive mechanisms employed in the development of a new class of fuzzy logic controllers called the Clearness Transformation Fuzzy Logic Controller "a-FLC". This controller employs a new scheme for approximate reasoning which gives better time performance and yield high control quality than the currently existing fuzzy umtrollers. The paper reports on the performance of the CT-FLC using results of simulation studies on the control of complex nonlinear systems.

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The paper outlines the feature of a new development station for automated design of fuzzy controller applications. The station supports such functions as automated knowledge base (KB) generation and tuning. The station represents the new generation of tools to support rapid design and development of fuzzy controller applications.