Design of robust fuzzy-logic control systems by multi-objective evolutionary methods with hardware in the loop.
|dc.identifier.citation||Stewart, P., Stone, D.A., and Fleming, P.J. (2004) 'Design of robust fuzzy-logic control systems by multi-objective evolutionary methods with hardware in the loop', Engineering Applications of Artificial Intelligence, 17(3), pp.275-284. doi: 10.1016/j.engappai.2004.03.003.||en_US|
|dc.description.abstract||Evolutionary development of a fuzzy-logic controller is described and is evaluated in the context of hardware in the loop. It had been found previously that a robust speed controller could be designed for a DC motor motion control platform via off-line fuzzy logic controller design. However to achieve the desired performance, the controller required manual tuning on-line. This paper investigates the automatic design of a fuzzy logic controller directly onto hardware. An optimiser which modifies the fuzzy membership functions, rule base and defuzzification algorithms is considered. A multi-objective evolutionary algorithm is applied to the task of controller development, while an objective function ranks the system response to find the Pareto-optimal set of controllers. Disturbances are introduced during each evaluation at run-time in order to produce robust performance. The performance of the controller is compared experimentally with the fuzzy logic controller which has been designed off-line, and a standard PID controller which has been tuned online. The on-line optimised fuzzy controller is shown to be robust, possessing excellent steady-state and dynamic characteristics, demonstrating the performance possibilities of this type of approach to controller design.||en_US|
|dc.rights||Attribution 3.0 United States||*|
|dc.subject||Models and algorithms||en_US|
|dc.title||Design of robust fuzzy-logic control systems by multi-objective evolutionary methods with hardware in the loop.||en_US|
|dc.contributor.department||University of Sheffield||en_US|
|dc.identifier.journal||Engineering Applications of Artificial Intelligence||en_US|