| This paper describes the basic theory of ant colony algorithm and explores the mathematical model of the algorithm and its implementation, and analysis of the strengths and weaknesses, then proposed an improved method. The specific approach is to retain its positive feedback mechanism, the advantages of easy-to-parallel processing cases, for its convergence speed is slow, prone to stagnation, the global search capability is poor, presents an improved ant colony algorithm fusion of genetic algorithm. In this paper, selected the main steam temperature control system from the thermal control systems , improved ant colony algorithm used to the PID control parameters of optimization main steam temperature control system. Simulation results show that the system of PID controller parameters optimization used improved ant colony algorithm has a good following performance, anti-jamming performance and robustness. |
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