This paper presents a comprehensive study on the implementation and analysis of PID controllers in an automated voltage regulator (AVR) system. A novel tuning technique, Virtual Time response-based iterative gain evaluation and re-design (V-Tiger), is introduced to iteratively adjust PID gains for optimal control performance. The study begins with the development of a mathematical model for the AVR system and initialization of PID gains using the Pessen Integral Rule. Virtual time-response analysis is then conducted to evaluate system performance, followed by iterative gain adjustments using Particle Swarm Optimization (PSO) within the V-Tiger framework. MATLAB simulations are employed to implement various controllers, including the V-Tiger PID controller, and their performance is compared in terms of transient response, stability, and control signal generation. Robustness analysis is conducted to assess the system's stability under uncertainties, and worst-case gain analysis is performed to quantify robustness. The transient response of the AVR with the proposed PID controller is compared with other heuristic controllers such as the Flower Pollination Algorithm, Teaching-Learning-based Optimization, Pessen Integral Rule, and Zeigler-Nichols methods. By measuring the peak closed-loop gain of the AVR with the controller and adding uncertainty to the AVR's field exciter and amplifier, the robustness of proposed controller is determined. Plotting the performance degradation curves yields robust stability margins and the accompanying maximum uncertainty that the AVR can withstand without compromising its stability or performance. Based on the degradation curves, robust stability margin of the V-Tiger PID controller is estimated at 3.5. The worst-case peak gains are also estimated using the performance degradation curves. Future research directions include exploring novel optimization techniques for further enhancing control performance in various industrial applications.
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http://dx.doi.org/10.1038/s41598-024-58481-1 | DOI Listing |
Sci Rep
January 2025
State Key Laboratory of Metallurgical Intelligent Manufacturing System, Beijing, 100071, China.
At present, the parameters of the controllers in hot rolling roughing microtension control systems are not adaptively adjustable to variations in working conditions, which compromises both width accuracy and production stability. To address this issue, this paper introduces an ATKB-PID adaptive micro tension control method. This method incorporates a linear attention layer and utilizes a K-Nearest Neighbors (KNN) algorithm to predict the optimal learning rate and inertia coefficient under actual operating conditions.
View Article and Find Full Text PDFSci Rep
January 2025
ENET Centre, VSB-Technical University of Ostrava, Ostrava, 708 00, Czech Republic.
Steam condensers are vital components of thermal power plants, responsible for converting turbine exhaust steam back into water for reuse in the power generation cycle. Effective pressure regulation is crucial to ensure operational efficiency and equipment safety. However, conventional control strategies, such as PI, PI-PDn and FOPID controllers, often struggle to manage the nonlinearities and disturbances inherent in steam condenser systems.
View Article and Find Full Text PDFPLoS One
January 2025
Faculty of Mechanical Engineering, Thuyloi University, Hanoi, Vietnam.
Road surface roughness is the cause of vehicle vibration, which is considered a system disturbance. Previous studies on suspension system control often ignore the influence of disturbances while designing the controller, leading to system performance degradation under severe vibration conditions. In this work, we propose a control method to improve active suspension performance that reduces vehicle vibration by eliminating the influence of road disturbances.
View Article and Find Full Text PDFVirol J
January 2025
Laboratory of Clinical Virology, WHO Regional Reference Laboratory for Poliomyelitis and Measles for in the Eastern Mediterranean Region, Institut Pasteur de Tunis, University of Tunis El Manar, 13 place Pasteur, BP74 1002 le Belvédère, Tunis, Tunisia.
Background: Primary Immunodeficiency disorders (PID) can increase the risk of severe COVID-19 and prolonged infection. This study investigates the duration of SARS-CoV-2 excretion and the genetic evolution of the virus in pediatric PID patients as compared to immunocompetent (IC) patients.
Materials And Methods: A total of 40 nasopharyngeal and 24 stool samples were obtained from five PID and ten IC children.
ACS Nano
January 2025
Department of Physics and Astronomy, University of Manitoba, Winnipeg R3T 2N2, Canada.
Theory and simulations are used to demonstrate implementation of a variational Bayes algorithm called "active inference" in interacting arrays of nanomagnetic elements. The algorithm requires stochastic elements, and a simplified model based on a magnetic artificial spin ice geometry is used to illustrate how nanomagnets can generate the required random dynamics. Examples of tracking and PID control are demonstrated and shown to be consistent with the original stochastic differential equation formulation of active inference.
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