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建立制粉系统中磨煤机电流、排粉机电流与各运行参数之间的非线性神经网络模型,通过带约束条件的非线性优化,获得使制粉单耗较低的运行参数,以此作为控制系统的设定值。在此基础上,采用基于操作经验的智能控制及多变量解耦控制等技术对制粉系统实施全局优化控制,确保制粉系统运行在最佳工况的附近,有效降低制粉单耗,并减轻运行人员的操作强度。
A nonlinear neural network model between pulverizer current, powder discharge machine current and each operating parameter is set up. Through the nonlinear optimization with constraints, the operating parameters with low consumption of milling are obtained, As the control system settings. Based on this, global optimal control of the milling system is implemented by using intelligent control based on operational experience and multivariable decoupling control to ensure that the milling system is operating near the best working conditions, and the unit consumption of milling is effectively reduced. Reduce operating personnel operating strength.