基于蚁群算法的磨机负荷寻优控制策略研究

Research on optimization control strategy of mill load based on ant colony algorithm

利用模糊控制可以对非线性、纯滞后及复杂的对象进行控制的优点,并结合自寻优方法,设计出一种新的磨机负荷控制器。该控制器运用蚁群算法对模糊控制器进行优化,并结合变步长自寻优算法来控制磨机运行状况。试验结果表明,本文提出的模糊控制策略能更好地应对磨机运行时的干扰,提高磨机产量,从而提高矿厂的经济效益。

Since the fuzzy control can be applied to the control of non-linear, pure lag and complex object, in combination with self-optimization method, a new mill load controller was designed. The ant colony algorithm was applied to optimize fuzzy controller, and variable-step self-optimizing algorithm was combined to control the mill operation. Test results showed the proposed fuzzy control strategy was superior in dealing with interference during mill operation, thus both the throughput of the mill and the economical benefit of the enterprise enhanced.