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Study on an improved algorithm for optimization of PID parameters

机译:PID参数优化的改进算法研究

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The improved ant colony algorithm is the hybrid algorithm consisting of the genetic algorithm and ant colony algorithm convergence. Through the introduction of the gauss mutation, we achieve the goal of improving ant colony algorithm. Using coal-fired power plant unit as main steam temperature controlled object, we design the PID controller based on improved ant colony algorithm. And setting of PID parameters by Z - N method has carried on the comparative analysis of the main steam temperature control system. Simulation results show that PID optimization based on improved ant colony algorithm can greatly improve the dynamic performance of the control system. So we verify the sophistication and effectiveness of the algorithm.
机译:改进的蚁群算法是由遗传算法和蚁群算法收敛组成的混合算法。通过引入高斯变异,我们达到了改进蚁群算法的目的。以燃煤电厂机组为主要蒸汽温度控制对象,设计了基于改进蚁群算法的PID控制器。采用Z-N法设定PID参数进行了主汽温控制系统的比较分析。仿真结果表明,基于改进蚁群算法的PID优化可以大大提高控制系统的动态性能。因此,我们验证了该算法的复杂性和有效性。

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