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Hot strip laminar cooling control based on NNPID controller

机译:基于NNPID控制器的热轧带钢层流冷却控制

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摘要

Hot strip coiling temperature is one important parameter of performance index in hot rolled strip, and its control system is highly nonlinear. A new neural network PID (NNPID) controller, which is based on PID by means of neural network's ability of selflearning and adaptive, is presented. The NNPID controller is designed by combining neural network with PID control strategy. Additional momentum method, that is an improved BP algorithm, is used in the neural network is analyzed. It presents the control for the uncertain-information, multi-variable and hot strip laminar cooling control based on the NNPID controller. The results show that the dynamic quality of the system is improved, and NNPID has good adaptability.
机译:热轧卷取温度是热轧带材性能指标的重要参数之一,其控制系统是高度非线性的。提出了一种基于神经网络的自学习和自适应能力的基于PID的神经网络PID控制器。通过将神经网络与PID控制策略相结合来设计NNPID控制器。分析了神经网络中使用的附加动量法,即改进的BP算法。提出了基于NNPID控制器的不确定信息,多变量和热轧带钢层流冷却控制。结果表明,该系统的动态质量得到提高,并且NNPID具有良好的适应性。

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