Optimized Fuzzy-Based Wavelet Neural Network Controller for a Non-Linear Process Control System. Issue 3 (3rd April 2023)

• Record Type: Journal Article
• Authors: Deepa, S.N.; Jayalakshmi, N. Yogambal
• Is Part Of: IETE journal of research. Volume 69:Issue 3(2023)
• Page Start: 1363
• Page End: 1372
• Publication Date: 2023-04-03
• Subjects: Continuous stirred tank reactor -- Deterministic grey wolf optimizer -- Mamdani fuzzy model -- Non-linear system -- Wavelet neural network; Electronics -- Periodicals; Telecommunication -- Periodicals; Electronics; Telecommunication; Periodicals; 621.38
• DOI: 10.1080/03772063.2020.1865212
• Languages: English
• ISSNs: 0377-2063

Abstract

Abstract : One of the common non-linear process control problems is the continuous stirred tank reactor problem and the reactor is applied widely in chemical process industries. It is of high importance to develop a suitable controller scheme for the concentration and temperature control of the considered non-linear continuous stirred tank reactor (CSTR) model. In this paper, a novel wavelet neural network (WNN) controller model is developed to carry out the control action and to meet the performance requirements of the system model. The developed wavelet neural network model is tuned for its weights employing the proposed deterministic grey wolf optimizer algorithm and its input is fed from the Mamdani fuzzy model. The optimal number of rules to be formulated for the fuzzy rule base model is computed using the deterministic grey wolf optimizer (DGWO) which is the variant of the classic grey wolf optimizer (GWO). WNN controller devise, based on the inputs from the fuzzy model and weights from DGWO, is designed to perform control action on the non-linear CSTR model. The concentration and temperature control is carried out by the proposed controller and the responses are obtained. Also, the respective time response specifications are evaluated for the developed WNN controller. Simulation experiments prove the effectiveness of the proposed controller for the considered non-linear CSTR model in comparison with that of the existing controllers from the literature.