A Novel Salp Swarm Optimization Oriented 3-DOF-PIDA Controller Design for Automatic Voltage Regulator System DOI Creative Commons
Nelson Dhanpal Chetty, Gulshan Sharma, Ravi V. Gandhi

et al.

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 20181 - 20196

Published: Jan. 1, 2024

Voltage stability is critical in electrical power systems, and automatic voltage regulators play a crucial role maintaining levels within permissible limits. Due to their simplicity effectiveness, traditional Proportional-Integral-Derivative (PID) controllers have been widely used regulation. However, they may not always perform optimally complex under varying operating conditions external disturbances. This research introduces an integrated approach of employing 3-degrees freedom-PID-Acceleration (3-DOF-PIDA) controller coupled with disturbance observer-based control strategy. combination embedded simple but effective salp swarm optimisation algorithm. novel the combined 3-DOF-PIDA, observer will enhance regulation system. The proposed strategy incorporates acceleration component continuously adjust its parameters based on system dynamics. Simultaneously, responsible for estimating compensating disturbances, further improving system's performance. applied optimise both PIDA observer's find optimal solutions that improve rejection capabilities. results are established by performing statistical graphical analysis time-varying step load fluctuations, various parameter variations. validated comparisons five popular optimization algorithms found reviewed literature. investigations demonstrate this new provides outstanding performance, presence substantial fluctuations uncertainties.

Language: Английский

Predicting roof displacement of roadways in underground coal mines using adaptive neuro-fuzzy inference system optimized by various physics-based optimization algorithms DOI Creative Commons
Chengyu Xie, Hoang Nguyen, Xuan-Nam Bui

et al.

Journal of Rock Mechanics and Geotechnical Engineering, Journal Year: 2021, Volume and Issue: 13(6), P. 1452 - 1465

Published: Sept. 16, 2021

Due to the rapid industrialization and development of economy in each country, demand for energy is increasing rapidly. The coal mines have pace up mining operations with large production meet demand. This requirement has led underground go deeper more difficult conditions, especially hazards, such as deformations, rockburst, burst, roof collapse, name a few. Therefore, this study aims at investigating predicting stability roadways exploited by longwall method, using various novel intelligent techniques based on physics-based optimization algorithms (i.e. multi-verse optimizer (MVO), equilibrium (EO), simulated annealing (SA), Henry gas solubility (HGSO)) adaptive neuro-fuzzy inference system (ANFIS), named MVO-ANFIS, EO-ANFIS, SA-ANFIS HGSO-ANFIS models. Accordingly, 162 displacement events were investigated characteristics surrounding rocks, cohesion, Young's modulus, density, shear strength, angle internal friction, uniaxial compressive quench durability index, rock mass rating, tensile strength. models then developed evaluated dataset displacements mines. results indicated that proposed could accurately predict an accuracy range 83%–92%. Remarkably, model yielded most dominant 92%). Based accurate predictions from techniques, reinforced solutions can be timely suggested ensure during exploiting coal, mining.

Language: Английский

Citations

71
Development of Lévy flight-based reptile search algorithm with local search ability for power systems engineering design problems DOI
Serdar Ekinci, Davut İzci,

Raed Abu Zitar

et al.

Neural Computing and Applications, Journal Year: 2022, Volume and Issue: 34(22), P. 20263 - 20283

Published: July 21, 2022

Language: Английский

Citations

66
An effective control design approach based on novel enhanced aquila optimizer for automatic voltage regulator DOI
Serdar Ekinci, Davut İzci, Erdal Eker

et al.

Artificial Intelligence Review, Journal Year: 2022, Volume and Issue: 56(2), P. 1731 - 1762

Published: June 10, 2022

Language: Английский

Citations

65
Hybrid Deep Learning Model for Fault Detection and Classification of Grid-Connected Photovoltaic System DOI Creative Commons
Moath Alrifaey, Wei Hong Lim, Chun Kit Ang

et al.

IEEE Access, Journal Year: 2022, Volume and Issue: 10, P. 13852 - 13869

Published: Jan. 1, 2022

Effective fault detection and classification play essential roles in reducing the hazards such as electric shocks fire photovoltaic (PV) systems. However, issues of interest for PV systems remain an open-ended challenge due to manual time-consuming processes that require relevant domain knowledge experience diagnoses. This paper proposes a hybrid deep-learning (DL) model-based combined architectures novel DL approaches achieve real-time automatic system. research employed wavelet packet transform (WPT) data preprocessing technique handle voltage signal collected feeding them inputs consist equilibrium optimizer algorithm (EOA) long short-term memory (LSTM-SAE) approaches. The are able extract features automatically from preprocessed without requiring any previous knowledge, therefore can override traditional shortages feature extraction selection optimal extracted features. These desirable anticipated speed up capability proposed model with higher accuracy. In order determine performance model, we carried out comprehensive evaluation study on 250-kW grid-connected this paper, symmetrical asymmetrical faults have been studied involving all phases ground single phase ground, phase, three-phase ground. simulation results validate efficacy terms computation time, accuracy detection, noise robustness. Comprehensive comparisons between studies demonstrate multidisciplinary applications present study.

Language: Английский

Citations

53
Design and robustness analysis of fuzzy PID controller for automatic voltage regulator system using genetic algorithm DOI
Tufan Doğruer, Mehmet Can

Transactions of the Institute of Measurement and Control, Journal Year: 2022, Volume and Issue: 44(9), P. 1862 - 1873

Published: Jan. 5, 2022

In this paper, a Fuzzy proportional–integral–derivative (Fuzzy PID) controller design is presented to improve the automatic voltage regulator (AVR) transient characteristics and increase robustness of AVR. PID parameters are determined by genetic algorithm (GA)-based optimization method using novel multi-objective function. The function, which important for tuning parameters, obtains optimal solution Integrated Time multiplied Absolute Error (ITAE) criterion peak value output response. proposed tested on two AVR models with different compared studies in literature. It observed that improves response properties also robust parameter changes.

Language: Английский

Citations

50
Nature-inspired optimization algorithms and their significance in multi-thresholding image segmentation: an inclusive review DOI Open Access
Rebika Rai, Arunita Das, Krishna Gopal Dhal

et al.

Evolving Systems, Journal Year: 2022, Volume and Issue: 13(6), P. 889 - 945

Published: Feb. 21, 2022

Language: Английский

Citations

47
Improved Lévy flight distribution algorithm with FDB-based guiding mechanism for AVR system optimal design DOI
Hüseyin Bakır, Uğur Güvenç, Hamdi Tolga Kahraman

et al.

Computers & Industrial Engineering, Journal Year: 2022, Volume and Issue: 168, P. 108032 - 108032

Published: Feb. 28, 2022

Language: Английский

Citations

47
Optimal PID plus second-order derivative controller design for AVR system using a modified Runge Kutta optimizer and Bode’s ideal reference model DOI
Davut İzci, Serdar Ekinci, Seyedali Mirjalili

et al.

International Journal of Dynamics and Control, Journal Year: 2022, Volume and Issue: 11(3), P. 1247 - 1264

Published: Oct. 2, 2022

Language: Английский

Citations

44
An Improved Marine Predators Algorithm-Tuned Fractional-Order PID Controller for Automatic Voltage Regulator System DOI Creative Commons
Mohd Zaidi Mohd Tumari, Mohd Ashraf Ahmad, Mohd Helmi Suid

et al.

Fractal and Fractional, Journal Year: 2023, Volume and Issue: 7(7), P. 561 - 561

Published: July 20, 2023

One of the most popular controllers for automatic voltage regulator (AVR) in maintaining level a synchronous generator is fractional-order proportional–integral-derivative (FOPID) controller. Unfortunately, tuning FOPID controller challenging since there are five gains compared to three conventional proportional–integral–derivative (PID) Therefore, this research work presents variant marine predators algorithm (MPA) AVR system. Here, two modifications applied existing MPA: hybridization between MPA and safe experimentation dynamics (SEDA) updating mechanism solve local optima issue, introduction tunable step size adaptive coefficient (CF) improve searching capability. The effectiveness proposed method system was assessed terms convergence curve objective function, statistical analysis Wilcoxon’s rank test, response analysis, stability analyses, robustness analyses where subjected noise, disturbance, parameter uncertainties. We have shown that our has improved system’s transient also produced about times better results function with other recent metaheuristic optimization-tuned controllers.

Language: Английский

Citations

42
An intelligent tuning scheme with a master/slave approach for efficient control of the automatic voltage regulator DOI
Davut İzci, Serdar Ekinci, Seyedali Mirjalili

et al.

Neural Computing and Applications, Journal Year: 2023, Volume and Issue: 35(26), P. 19099 - 19115

Published: June 18, 2023

Language: Английский

Citations

32