Control of neutralization process using neuro and fuzzy controller

N. Bharathi, J. Shanmugam, T. Rangaswamy
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引用次数: 3

Abstract

Due to the extreme nonlinearity in the pH characteristics, control of pH in any chemical or biochemical process is a difficult task. Different approaches for pH control are proposed in various literatures. In the present study, control of pH neutralization process using neural and fuzzy controller is proposed. Initially a conventional linear controller is tried to control the pH at different linear regions. Based on the pH process characteristics, the nonlinear operating region is divided into three linear regions like pH low, pH middle, and pH high. Within each region, a local linear model is used to represent the process and a controller is designed. Control of pH by conventional PI controller based on the local linear model fails to provide satisfactory performance over the entire region, because of the extreme nonlinearity in the pH dynamics. It is required to tune the controller gain for different operating regions. Hence to overcome this drawback a neuro controller and a fuzzy controller are used. In this paper a novel fuzzy controller is used. Most fuzzy controllers use control error (e) and change in the control error (Deltae) as controller inputs and hence not able to differentiate the region in which the process operates, which is important information, necessary to control the nonlinear process. This controller uses set point as third input to select the region in which the process is operating.
中和过程的控制采用神经和模糊控制器
由于pH特性的极端非线性,在任何化学或生化过程中控制pH都是一项艰巨的任务。在各种文献中提出了不同的pH控制方法。在本研究中,提出了用神经和模糊控制器控制pH中和过程。首先,采用传统的线性控制器来控制不同线性区域的pH值。根据pH过程特点,将非线性工作区域划分为pH低、pH中、pH高三个线性区域。在每个区域内,用局部线性模型表示过程,并设计控制器。传统的基于局部线性模型的PI控制器对pH的控制,由于pH动力学具有极大的非线性,在整个区域内无法提供满意的控制效果。需要根据不同的工作区域调整控制器增益。因此,为了克服这一缺点,采用了神经控制器和模糊控制器。本文采用了一种新颖的模糊控制器。大多数模糊控制器使用控制误差(e)和控制误差变化(Deltae)作为控制器输入,因此无法区分过程运行的区域,这是控制非线性过程所必需的重要信息。该控制器使用设定点作为第三个输入来选择过程运行的区域。
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