Stewart, Paul and 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. ISSN 0952-1976
Full text not available from this repository.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 on to hardware. An optimiser which modifies the fuzzy membership functions, rulebase 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 fuzzycontroller is shown to be robust, possessing excellent steady-state and dynamic characteristics, demonstrating the performance possibilities of this type of approach to controller design.
| Item Type: | Article |
|---|---|
| Additional Information: | 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 on to hardware. An optimiser which modifies the fuzzy membership functions, rulebase 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 fuzzycontroller is shown to be robust, possessing excellent steady-state and dynamic characteristics, demonstrating the performance possibilities of this type of approach to controller design. |
| Keywords: | Fuzzy Systems, Genetic Algorithms, Multiobjective Optimisation, Control Systems, Hardware in the Loop |
| Subjects: | H Engineering > H620 Electrical Engineering H Engineering > H660 Control Systems G Mathematical and Computer Sciences > G520 Systems Design Methodologies H Engineering > H100 General Engineering G Mathematical and Computer Sciences > G700 Artificial Intelligence H Engineering > H360 Electromechanical Engineering |
| Divisions: | College of Sciences > Faculty of Science > Lincoln School of Engineering |
| Depositing User: | Paul Stewart |
| Date Deposited: | 01 Mar 2010 23:01 |
| Last Modified: | 11 Dec 2012 15:08 |
| URI: | http://eprints.lincoln.ac.uk/id/eprint/2190 |
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