Abstract
Based on subpopulation parallel computing, a novel quantum genetic algorithm (NQGA) is presented. In the algorithm, each axis of solution is divided into k parts, so m dimensional space is partitioned km subspaces, the individual (or chromosome) from different subspace code differently. Finally, NQGA and the classical quantum genetic algorithm (QGA) are applied to parameter optimization of PID controller, simulation results show that NQGA performs better than QGA on running speed and optimizing capability.
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Wang, J., Zhou, R. (2010). A Novel Quantum Genetic Algorithm for PID Controller. In: Huang, DS., Zhao, Z., Bevilacqua, V., Figueroa, J.C. (eds) Advanced Intelligent Computing Theories and Applications. ICIC 2010. Lecture Notes in Computer Science, vol 6215. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14922-1_10
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DOI: https://doi.org/10.1007/978-3-642-14922-1_10
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