An improved BBO algorithm and its application in pid optimization of CFB bed temperature system

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Abstract

In order to improve the performance of biogeography optimization (BBO) algorithm in PID controller parameter optimization of thermal systems and have superior convergence characteristics, the article gives an improved BBO algorithm. The improved BBO algorithm introduces the introducing convergence mechanism of particle swarm optimization on the basis of original migration strategy, so that the whole migration process has a certain direction. Also, the article uses phase-out strategy to remove poor parameters which are obtained after the migration and mutation processes. Thus, on the one hand, directional migration and elimination mechanism can ensure its fast convergence properties. On the other hand, mutational mechanisms can ensure the global characteristics of wide-area searching and avoid falling into local extrema. Using it in the PID optimization of CFB bed temperature system, the simulation results show that the improved BBO algorithm has a better performance than the standard BBO algorithm on convergence speed and precision. It is feasible and effective for PID controller parameter optimization in thermal system.

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APA

Xue, H., & Pu, H. (2016). An improved BBO algorithm and its application in pid optimization of CFB bed temperature system. In Lecture Notes in Electrical Engineering (Vol. 367, pp. 675–682). Springer Verlag. https://doi.org/10.1007/978-3-662-48768-6_76

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