Abstract
By mimicking the biological evolution process, genetic algorithm (GA) methodology has the advantages of creating and updating new elite parameters for optimization processes, especially in controller design technique. In this paper, a GA improvement that can speed up convergence and save operation time by neglecting chromosome decoding step is proposed to find the optimized fuzzy-proportional-integral-derivative (fuzzy-PID) control parameters. Due to minimizing tracking error of the controller design criterion, the fitness function integral of square error (ISE) was employed to utilize the advantages of the modified GA. The proposed method was then applied to a novel autonomous hovercraft motion model to display the superiority to the standard GA.
Subject
Process Chemistry and Technology,Chemical Engineering (miscellaneous),Bioengineering
Reference31 articles.
1. Engineering Optimization: An Introduction with Metaheuristic Applications;Yang,2010
2. Practical Genetic Algorithms;Haupt,2004
3. Optimization of Control Parameters for Genetic Algorithms
4. Adaptive probabilities of crossover and mutation in genetic algorithms
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