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Based on Neural Network PID Controller Design and Simulation

机译:基于神经网络PID控制器设计和仿真

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The technologic of PID control is very conventional. There is an extensive application in many fields at present. The PID controller is simple in structure, strong in robustness, and can be understood easily. Then neural networks have great capability in solving complex mathematical problems since they have been proven to approximate any continuous function as accurately as possible. Hence, it has received considerable attention in the field of process control. Due to the complication of modern industrial process and the increase of nonlinearity, time-varying and uncertainty of the practical production processes, the conventional PID controller can no longer meet our requirement. This paper introduces the theoretical foundation of the BP neural network and studying algorithm of the neural network briefly, and designs the PID temperature control system and simulation model based on BP neural network.
机译:PID控制的技术非常常规。目前许多领域都有一个广泛的应用。 PID控制器结构简单,具有强大的强大,并且可以轻松理解。然后神经网络在解决复杂的数学问题方面具有很大的能力,因为它们已被证明可以尽可能准确地近似任何连续功能。因此,它在过程控制领域获得了相当大的关注。由于现代工业流程的并发症和实际生产过程的非线性,时变不确定性,传统的PID控制器不再满足我们的要求。本文介绍了BP神经网络的理论基础,简要介绍了神经网络的研究算法,并设计了基于BP神经网络的PID温度控制系统和仿真模型。

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