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.

常见的非线性过程控制问题之一是连续搅拌釜反应器问题，该反应器在化学过程工业中应用广泛。为所考虑的非线性连续搅拌釜反应器 (CSTR) 模型的浓度和温度控制开发合适的控制器方案非常重要。在本文中，开发了一种新颖的小波神经网络（WNN）控制器模型来执行控制动作并满足系统模型的性能要求。已开发的小波神经网络模型采用所提出的确定性灰狼优化器算法对其权重进行了调整，其输入来自 Mamdani 模糊模型。使用确定性灰狼优化器 (DGWO) 计算为模糊规则库模型制定的最佳规则数，它是经典灰狼优化器 (GWO) 的变体。WNN 控制器设计基于模糊模型的输入和 DGWO 的权重，旨在对非线性 CSTR 模型执行控制操作。浓度和温度控制由所提出的控制器执行，并获得响应。此外，还针对开发的 WNN 控制器评估了相应的时间响应规范。与文献中的现有控制器相比，仿真实验证明了所提出的控制器对于所考虑的非线性 CSTR 模型的有效性。基于模糊模型的输入和 DGWO 的权重，设计用于对非线性 CSTR 模型执行控制操作。浓度和温度控制由所提出的控制器执行，并获得响应。此外，还针对开发的 WNN 控制器评估了相应的时间响应规范。与文献中的现有控制器相比，仿真实验证明了所提出的控制器对于所考虑的非线性 CSTR 模型的有效性。基于模糊模型的输入和 DGWO 的权重，设计用于对非线性 CSTR 模型执行控制操作。浓度和温度控制由所提出的控制器执行，并获得响应。此外，还针对开发的 WNN 控制器评估了相应的时间响应规范。与文献中的现有控制器相比，仿真实验证明了所提出的控制器对于所考虑的非线性 CSTR 模型的有效性。