In-situ controller autotuning by Bayesian optimization for closed-loop feedback control of laser powder bed fusion process

Additive manufacturing, Journal Year: 2025, Volume and Issue: unknown, P. 104641 - 104641

Published: Jan. 1, 2025

Language: Английский

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Chaotic Puma Optimizer Algorithm for controlling wheeled mobile robots

Engineering Science and Technology an International Journal, Journal Year: 2025, Volume and Issue: 63, P. 101982 - 101982

Published: Feb. 2, 2025

Language: Английский

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Adaptive control system of header for cabbage combine harvester based on IPSO-fuzzy PID controller

Computers and Electronics in Agriculture, Journal Year: 2025, Volume and Issue: 232, P. 110044 - 110044

Published: Feb. 12, 2025

Language: Английский

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A Self-Tuning Variable Universe Fuzzy PID Control Framework with Hybrid BAS-PSO-SA Optimization for Unmanned Surface Vehicles

Journal of Marine Science and Engineering, Journal Year: 2025, Volume and Issue: 13(3), P. 558 - 558

Published: March 13, 2025

In this study, a hybrid heading control framework for unmanned surface vehicles (USVs) is proposed, combining variable domain fuzzy Proportional–Integral–Derivative (VUF-PID) with an improved algorithmic Beetle Antennae Search–Particle Swarm Optimization–Simulated Annealing (BAS-PSO-SA) optimization to address the multi-objective challenge. Key innovations include self-tuning VUF mechanism that improves disturbance rejection by 42%, weighted adaptive strategy reduces parameter tuning iterations 37%, and asymmetric learning factor balances global exploration local refinement. Benchmarks using Rastrigin, Griewank, Sphere functions show superior convergence 68% stability improvement. Ocean simulations of 7.02 m vehicle (USV) Nomoto model 91.7% reduction in stabilization time, 0.9% overshoot, 30% iterations. The experimental validation under wind wave disturbances shows deviation less than 0.0392°, meeting IMO MSC.1/Circ.1580 standard, 89.5% improvement energy efficiency. Although processing time 12.7% longer compared GRO approach, lays solid foundation ship autonomy systems, future enhancements will focus on MPC-based delay compensation Field-Programmable Gate Array (FPGA) acceleration.

Language: Английский

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Level Control of Blast Furnace Gas Cleaning Tank System with Fuzzy Based Gain Regulation for Model Reference Adaptive Controller

Processes, Journal Year: 2022, Volume and Issue: 10(12), P. 2503 - 2503

Published: Nov. 25, 2022

Iron making processes and automation systems are mostly controlled by logical rules PID controllers. The dynamic behavior of these varies due to factors such as raw materials, outdoor conditions, equipment aging. Changes in system dynamics necessitate re-determination controller parameters. Model reference adaptive controllers (MRACs) used many industrial application areas with their adaptability variable conditions. In this study, an MRAC is applied the gas cleaning tank level control problem blast furnace facility, which at center iron processes. addition, fuzzy based gain regulation proposed improve performance. results observed compared. fast response adaptation performance approach along external disturbance effects analyzed. Fuzzy performances show better especially change well effect.

Language: Английский

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Efficient Speed Control for DC Motors Using Novel Gazelle Simplex Optimizer

IEEE Access, Journal Year: 2023, Volume and Issue: 11, P. 105830 - 105842

Published: Jan. 1, 2023

This paper addresses the design of an optimally executed proportional-integral-derivative (PID) controller, tailored for speed regulation a direct current (DC) motor. To achieve this objective, we present novel hybrid algorithm, combining gazelle optimization algorithm (GOA) with effective simplex search method known as Nelder-Mead (NM) technique. The fusion these algorithms yields innovative hybridized version, striking balance between exploration and exploitation. proposed approach, named optimizer (GSO), showcases great promise when applied to task controlling DC motor using PID controller. identify optimal values gains, harness power objective function well, which guides GSO in determining most favorable controller settings. Rigorous comparative simulations are then undertaken, where pit against several other algorithms, namely reptile prairie dog weighted mean vectors optimization, original GOA algorithm. These allow us assess system's behavior through various lenses, such statistical tests, time frequency domain responses, robustness analysis, changes function. evaluations from comprehensive tests demonstrate superiority GSO-based controlled system. exhibits better performance than alternative providing solid evidence its effectiveness. Furthermore, approach outperforms reported tuning methods, affirming prowess achieving superior motors.

Language: Английский

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Metaheuristic-Based Algorithms for Optimizing Fractional-Order Controllers—A Recent, Systematic, and Comprehensive Review

Fractal and Fractional, Journal Year: 2023, Volume and Issue: 7(7), P. 553 - 553

Published: July 17, 2023

Metaheuristic optimization algorithms (MHA) play a significant role in obtaining the best (optimal) values of system’s parameters to improve its performance. This is significantly apparent when dealing with systems where classical analytical methods fail. Fractional-order (FO) have not yet shown an easy procedure deal determination their optimal through traditional methods. In this paper, recent, systematic. And comprehensive review presented highlight MHA set gains and orders for FO controllers. The systematic starts by exploring most relevant publications related study focused on popular controllers such as FO-PI, FO-PID, Type-1 fuzzy-PID, Type-2 fuzzy-PID. time domain restricted articles published last decade (2014:2023) reputed databases Scopus, Web Science, Science Direct, Google Scholar. identified number papers, from entire databases, has reached 850 articles. A Preferred Reporting Items Systematic Reviews Meta-Analyses (PRISMA) methodology was applied initial be screened filtered end up final list that contains 82 Then, thorough list. results showed Particle Swarm Optimization (PSO) attractive optimizer researchers used identification it attains about 25% papers. addition, papers PSO gained high citation despite fact Chaotic Atom Search (ChASO) highest one, but only once. Furthermore, Integral Time-Weighted Absolute Error (ITAE) nominated cost function. Based our literature review, appears first paper systematically comprehensively addresses fractional-order PI, PID, Type-1, fuzzy use MHAs. Therefore, work can guide who are interested working field.

Language: Английский

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Research and Design of Hybrid Optimized Backpropagation (BP) Neural Network PID Algorithm for Integrated Water and Fertilizer Precision Fertilization Control System for Field Crops

Agronomy, Journal Year: 2023, Volume and Issue: 13(5), P. 1423 - 1423

Published: May 21, 2023

China’s field crops such as cotton, wheat, and tomato have been produced on a large scale, but their cultivation process still adopts more traditional manual fertilization methods, which makes the use of chemical fertilizers in China high causes waste fertilizer resources ecological environmental damage. To address above problems, hybrid optimization genetic algorithms particle swarm (GA–PSO) is used to optimize initial weights backpropagation (BP) neural network, optimization-based BP network PID controller designed realize accurate control flow integrated water precision system for crops. At same time, STM32 microcontroller-based application was developed performance verified experimentally. The results show that has an average maximum overshoot 5.1% adjustment time 68.99 s, better than based (BP–PID) controllers; among them, algorithm by algorithm(GA–PSO–BP–PID) best-integrated when rate 0.6m3/h.

Language: Английский

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Artificial rabbits optimization algorithm based tuning of PID controller parameters for improving voltage profile in AVR system using IoT

e-Prime - Advances in Electrical Engineering Electronics and Energy, Journal Year: 2024, Volume and Issue: 8, P. 100523 - 100523

Published: March 27, 2024

The power system is mainly affected by transient situations caused switching heavy loads. may become unstable when occur. should be able to perform continuous operation maintain its voltage within acceptable limits. To achieve more stability and increase speed of response, an Automatic Voltage Regulator (AVR) requires the inclusion a controller. AVR in generating station uses PID controller adjust abnormal conditions. nominal level under all load conditions system, bio-inspired meta-heuristic algorithm called Artificial Rabbit Optimization (ARO) proposed tune gain parameters obtain optimal gain, thereby adjusts generator terminal levels. ARO inspires natural survival techniques improve performance reducing errors. stable profile this research mathematically models using Internet Things (IoT) solution. As result, devices connected network receive that ensures their reliability. effectiveness for verified with MATLAB R2022a model, statistics functions are implemented module Pandas, Scipy mathematical investigations done Numpy. achieves better less than 12.63% maximum peak overshoot during system's response. provides fastest response highest comparable other optimisation algorithms.

Language: Английский

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Model Predictive Paradigm with Low Computational Burden Based on Dandelion Optimizer for Autonomous Vehicle Considering Vision System Uncertainty

Mathematics, Journal Year: 2022, Volume and Issue: 10(23), P. 4539 - 4539

Published: Dec. 1, 2022

The uncertainty due to road fluctuations and vision system dynamics represents a big challenge adjusting the steering angle of autonomous vehicles (AVs). Furthermore, AVs require fast action follow target lane overcome lateral deviation with minor errors. In this regard, paper introduces model predictive controller formulated based on discrete-time Laguerre function (DTLF) high computational burden traditional MPC. To improve hybrid DTLF-MPC performance, modern effective dandelion optimizer (DO) strategy is used in work, which resulted obtaining optimal parameters achieving satisfactory results. proposed designed different algorithms literature evaluate performance DO. Several scenarios are discussed confirm effectiveness efficiency control against fluctuations. results emphasize that DO can achieve best damping for deviations less overshoot; around 0.4533, settling time 0.01979 s compared other algorithms.

Language: Английский

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