Abstract
An integration of a cognitive map and a fuzzy inference engine is presented, as a cognitive–fuzzy model, targeting online fuzzy logic controller (FLC) design and self fine-tuning. The proposed model is different than previous proposed fuzzy cognitive maps in that it presents a hierarchical architecture in which the cognitive map process, available plant, and control objective data on represented knowledge to generate a complete FLC architecture and parameters description. Online assessment of measured data is processed for linguistic characterization of performance to determine the required FLC parameter's adjustments, the process is repeated until the control objective is reached. A mathematical model of the proposed approach is presented, and sample numerical data illustrate the following: (a) cognitive map construction, (b) start-up self fine-tuning, and (c) system's response to error of plant descriptive data. Simulation results demonstrate model interpretability, which suggests that the model is scalable and offers robust capability to generate near optimal controller, emulating human iterative design flow, and fine-tuning within the knowledge domain of cognitive map. © 2009 Wiley Periodicals, Inc.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
