Efficient DC motor speed control using a novel multi-stage FOPD(1 + PI) controller optimized by the Pelican optimization algorithm

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Sept. 28, 2024

Language: Английский

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Frequency stability improvement in EV-integrated power systems using optimized fuzzy-sliding mode control and real-time validation

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Feb. 17, 2025

The rapid growth in power demand, integration of renewable energy sources (RES), and intermittent uncertainties have significantly challenged the stability reliability interconnected systems. electric vehicles (EVs), with their bidirectional flow, further exacerbates frequency fluctuation system. So, to mitigate & deviations as well stabilize system integrated distributed generators (DGs) EVs, robust intelligent control strategies are indispensable. This study dedicates a novel Fuzzy-Sliding Mode Controller (FSMC) utilized for load (LFC). First, dynamic response has been evaluated by using Sliding (SMC), showcasing its robustness against external disturbances parameter uncertainties. Second, enhance performance, fuzzy logic is SMC, leveraging adaptability create FSMC controller. achieved superiority handling non-linearities, communication delays variations A significant contribution like design tuning controllers Modified Gannet Optimization Algorithm (MGOA) established. potential MGOA over GOA corroborated convergence speed precision through benchmark functions. Furthermore, paper extensively analyzes impact EV tie-line dynamics under varying regulation capacities uncertain operating conditions. Comparative studies demonstrate that MGOA-tuned achieves faster settling times, reduced overshoot, improved metrics compared conventional state-of-the-art methods. Finally, MATLAB-based simulation results validated real-time implementation on OPAL-RT 4510 platform, confirming practicality proposed methodology addressing modern challenges involving high penetration integration.

Language: Английский

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A gazelle optimization expedition for key term separated fractional nonlinear systems with application to electrically stimulated muscle modeling

Chaos Solitons & Fractals, Journal Year: 2024, Volume and Issue: 185, P. 115111 - 115111

Published: June 15, 2024

Language: Английский

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Advanced control strategy for AC microgrids: a hybrid ANN-based adaptive PI controller with droop control and virtual impedance technique

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Dec. 28, 2024

In this paper, an improved voltage control strategy for microgrids (MG) is proposed, using artificial neural network (ANN)-based adaptive proportional-integral (PI) controller combined with droop and virtual impedance techniques (VIT). The developed to improve control, power sharing total harmonic distortion (THD) reduction in the MG systems renewable distributed generation (DG) sources. VIT used decouple active reactive power, reduce negative interactions between DG's robustness of system under varying load conditions. Simulation findings different tests have shown significant improvements performance computational simulation. rise time reduced by 60%, overshoot 80%, THD 75% (from 0.99 0.20%), current 69% 10.73 3.36%) compared conventional PI technique. Furthermore, values were maintained below IEEE-519 standard limits 5% 8%, respectively, quality enhancement. Fluctuations frequency also at 2% tolerance 1% tolerance, across all limits, which consistent international norms. Power-sharing errors 50% after conducting against DC supply disturbances. addition, proposed outperforms previous presented state art terms adaptability, stability and, especially, ability THD, validates its effectiveness optimization uncertain

Language: Английский

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Novel application of sinh cosh optimizer for robust controller design in hybrid photovoltaic-thermal power systems

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 22, 2025

Load frequency control (LFC) is critical for maintaining stability in interconnected power systems, addressing deviations and tie-line fluctuations due to system disturbances. Existing methods often face challenges, including limited robustness, poor adaptability dynamic conditions, early convergence optimization. This paper introduces a novel application of the sinh cosh optimizer (SCHO) design proportional–integral (PI) controllers hybrid photovoltaic (PV) thermal generator-based two-area system. The SCHO algorithm's balanced exploration exploitation mechanisms enable effective tuning PI controllers, overcoming challenges such as local minima entrapment speeds observed conventional metaheuristics. Comprehensive simulations validate proposed approach, demonstrating superior performance across various metrics. SCHO-based controller achieves faster settling times (e.g., 1.6231 s 2.4615 Area 1 2, respectively) enhanced robustness under parameter variations solar radiation fluctuations. Additionally, comparisons with based on salp swarm algorithm, whale optimization firefly algorithm confirm its significant advantages, 25–50% improvement integral error indices (IAE, ITAE, ISE, ITSE). These results highlight controller's effectiveness reliability modern systems renewable energy sources.

Language: Английский

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A Chaotic Boost: The Chaotic Crayfish Optimization Algorithm for Superior Solution Quality

Optimal Control Applications and Methods, Journal Year: 2025, Volume and Issue: unknown

Published: April 30, 2025

ABSTRACT This study introduces the Chaotic Crayfish Optimization Algorithm (CCOA), an advanced variant of (COA) that integrates chaotic maps to enhance its performance in solving complex global optimization and engineering problems. The COA, inspired by foraging behaviour crayfish, has demonstrated effectiveness but is challenged issues such as imbalance between exploration exploitation, a tendency get trapped local optima, slower convergence rates high‐dimensional landscapes. By incorporating dynamics, CCOA addresses these limitations, improving algorithm's ability navigate diverse regions solution space refine promising solutions. employs ten distinct dynamically adapt search strategies dynamically, optimizing exploration‐exploitation balance. algorithm rigorously evaluated against established benchmark test functions from recognized competitions, including CEC 2014, 2017, 2020, 2022, assess finding optimal A comprehensive comparative analysis conducted various well‐known algorithms, Particle Swarm Optimization, Differential Evolution, traditional among others. Statistical significance through average ranking Wilcoxon Rank Sum Test evaluations. Additionally, applied six real‐world design problems, Welded Beam Design Problem Cantilever Problem, demonstrating practical applicability effectiveness. results indicate significantly enhances speed quality while effectively escaping establishing it robust tool for addressing wide range challenges. work contributes expanding field metaheuristic optimization, showcasing potential improve algorithmic problem domains.

Language: Английский

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Efficient voltage regulation: An RW-ARO optimized cascaded controller approach

e-Prime - Advances in Electrical Engineering Electronics and Energy, Journal Year: 2024, Volume and Issue: 9, P. 100687 - 100687

Published: July 11, 2024

This work introduces novel advancements in automatic voltage regulator (AVR) control, addressing key challenges and delivering innovative contributions. The primary motivation lies enhancing AVR performance to ensure stable reliable output. A crucial innovation this is the introduction of random walk aided artificial rabbits optimizer (RW-ARO). optimization strategy incorporates a approach, efficiency control schemes. proposed cascaded RPIDD2-PI controller, fine-tuned using RW-ARO, stands out as pioneering approach domain. It demonstrates superior stability, faster response times, enhanced robustness, improved compared existing methods. Comparative analyses with established controller approaches reaffirm exceptional method. new results shorter rise quicker settling minimal overshoot, highlighting its effectiveness speed achieving desired system responses. Moreover, attains higher phase gain margins, showcasing frequency disturbance rejection harmonic analysis are performed order demonstrate efficacy for potential real-world applications. latter further cement capability regulation.

Language: Английский

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Enhanced artificial hummingbird algorithm with chaotic traversal flight

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Oct. 29, 2024

Tackling the shortcomings of slow convergence, imprecision, and entrapment in local optima inherent traditional meta-heuristic algorithms, this study presents enhanced artificial hummingbird algorithm with chaotic traversal flight (CEAHA), which employs ergodicity within foundational framework conventional algorithm. This approach implements motion regions solution space, ensuring a thorough exploration potential preventing algorithmic stagnation at maxima by guaranteeing non-repetitive all search states. also analyzes intrinsic mechanisms eight different mappings affect optimization performance, from perspectives invariant measures efficiency ergodic motion. In comparative tests 21 algorithms on CEC2014, CEC2019, CEC2022 benchmark suites across various dimensions, CEAHA demonstrates superior performance. Furthermore, practicability robustness have been confirmed mechanical design problems through 4 engineering instances: pressure vessel, gear trains, speed reducers, piston levers.

Language: Английский

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AI in gastrointestinal disease detection: overcoming segmentation challenges with Coati optimization strategy

Evolving Systems, Journal Year: 2024, Volume and Issue: 16(1)

Published: Nov. 16, 2024

Language: Английский

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