Abstract
The design of a robust control system for a specified second order plant is considered using three different approaches. Initially, a con- trol system evolved by a genetic programming algorithm is reproduced and analysed in order to identify its advantages and drawbacks. The au- tomatic design technique is compared to a traditional one through the analysis of the constraints and performance indices obtained by simula- tion. A set of unspecified control constraints explored by the GP search process is found to be the cause of a better performance. Hence, giving a better constraints specification, a genetic algorithm is used to evolve an alternative controller. A PID structure is used by the GA to produce and tune the controller. Simulations show a significant gain in performance thanks to a more aggressive and complete exploration of the search space within the constraints. The effectiveness of the two methods compared to the traditional approach is discussed with regard to performance, com- plexity of design and computational viability.
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