Soft Computing Approach for Optimal Power Control in Large-Scale Nuclear Power Reactors Under Adverse Operating Conditions

Nuclear reactors, as a class, exhibit nonlinear and higher-order system characteristics, posing a consistent challenge for researchers in the design of effective controllers.The specific focus of this study is on the Pressurized Heavy Water Reactor (PHWR), a representative example of such intricate systems.Given the inherent complexity of higher-order system dynamics, this work tackles the challenge by employing a reduced-order modeling approach, capturing the essence of the original system's behavior.In the context of this research, a novel approach is taken in the design of a controller for the PHWR system.The method involves the use of an optimization-based Fractional Order Proportional Integral Derivative (FOPID) controller tailored for the lower-order model of the PHWR.The reduced-order model is derived through the application of the Balanced Truncation method, which enables the creation of a simplified yet representative model that faithfully emulates the behavior of the original higher-order system.The optimization of the FOPID controller parameters is achieved through the adoption of the Grey Wolf Optimization (GWO) algorithm.To substantiate the efficacy of the proposed controller, a comprehensive performance analysis is conducted.Various performance indices are employed to evaluate the controller's robustness and overall effectiveness in regulating the PHWR system.