Search Results - (( control function _ algorithm ) OR ( parameter optimization method algorithm ))
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1
Design of low order quantitative feedback theory and H-infinity-based controllers using particle swarm optimisation for a pneumatic actuator system
Published 2010“…The particle swarm optimization (PSO) method is used to tune the parameters of the controller and weighting functions subject to QFT and/or constraints. …”
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2
Optimization Of Pid Controller Using Grey Wolf Optimzer And Dragonfly Algorithm
Published 2018“…However, to fully utilize the algorithm, the parameter of the algorithm need to be set properly. …”
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Monograph -
3
Performance evaluation of smoothed functional algorithm based methods for sigmoid-PID control optimization in MIMO twin-rotor systems
Published 2024“…The SPID controller, incorporating a sigmoid function, extends the applicability of traditional PID controllers to complex, non-linear systems. …”
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4
Fast and optimal tuning of fractional order PID controller for AVR system based on memorizable-smoothed functional algorithm
Published 2022“…Therefore, this study proposes a modified smoothed function algorithm (MSFA) based method to tune the FOPID controller of AVR system since it requires fewer number of function evaluation per iteration. …”
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Article -
5
Genetic Algorithms In Optimizing Membership Function For Fuzzy Logic Controller
Published 2010“…Thus it is important to select the accurate membership functions but these methods possess one common weakness where conventional FLC use membership function and control rules generated by human operator. …”
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6
Design of PSO-based Fuzzy Logic Controller for single Axis Magnetic Levitation System.
Published 2011“…PSO algorithm is applied to search globally optimal parameters of FLCs. …”
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Article -
7
BBO algorithm-based tuning of PID controller for speed control of synchronous machine
Published 2023Article -
8
Performance of particle swarm optimization under different range of direct current motor's moment of inertia / Mohd Azri Abdul Aziz
Published 2018“…The implementation of Particle Swarm Optimization (PSO) algorithm in optimizing Proportional-Integral-Derivative (PID) controller's parameters is a popular technique to improve the performance of a control system. …”
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9
Data-Driven control based on marine predators algorithm for optimal tuning of the wind plant
Published 2022“…Comparative results alongside other existing metaheuristic-based algorithms further confirmed excellence of the proposed method through its superior performance against the slime mould algorithm (SMA), multi-verse optimizer (MVO), sine-cosine algorithm (SCA), grey wolf optimizer (GWO), and safe experimentation dynamics (SED) algorithm.…”
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10
An Optimized PID Parameters for LFC in Interconnected Power Systems Using MLSL Optimization Algorithm
Published 2016“…In order to enhance the dynamic performance, the optimal parameters of the PID scheme which optimized by the proposed MLSL algorithm are compared with that one’s obtained by GA algorithm. …”
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Article -
11
PID-Controller Tuning of Brushless DC Motor by Using ACO (Ant Colony Optimization) Technique
Published 2012“…ACO algorithm is used as the technique for the PID controller parameters optimization. …”
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Final Year Project -
12
Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar
Published 2019“…In addition, ACO algorithm has been used for optimization of PID controller parameters to obtain within rated smooth output power of WT from fluctuating wind speed. …”
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13
Performance of particle swarm optimization under different range of direct current motor's moment of inertia / Mohd Azri Abdul Aziz
Published 2018“…The implementation of Particle Swarm Optimization (PSO) algorithm in optimizing Proportional-Integral-Derivative (PID) controller's parameters is a popular technique to improve the performance of a control system. …”
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Book Section -
14
Elitism-crossover barnacle mating optimization and its application to PID controller design for a buck converter
Published 2024“…Result of benchmark functions test shows the proposed algorithm has attained higher accuracy for all functions compared to BMO algorithm. …”
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Article -
15
PID CONTROLLER TUNING OF 3-PHASE SEPARATOR IN OIL & GAS INDUSTRY USING BACTERIA FORAGING OPTIMIZATION ALGORITHM
Published 2012“…So, this paper will introduce Bacterial Foraging Optimization Algorithm (BFOA) in optimizing the parameters for PI control. …”
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Final Year Project -
16
Estimation of photovoltaic models using an enhanced Henry gas solubility optimization algorithm with first-order adaptive damping Berndt-Hall-Hall-Hausman method
Published 2024“…A reliable methodology is essential for accurately estimating the parameters of PV models, enabling reliable performance evaluations, effective control studies, accurate analysis of partial shading effects, and optimal optimization of Photovoltaic (PV) systems. …”
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Article -
17
Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms
Published 2020“…A new mutation vector inspired by the two-opposite path (2-Opt) algorithm with adaptive mutation scalar (F ) and crossover rate (CR) control parameters were employed to enhance the exploration and exploitation phases of the proposed algorithm. …”
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Thesis -
18
Single Machine Connected Infinite Bus system tuning coordination control using biogeography-based optimization algorithm
Published 2023“…The objective function J is framed using Integral square error (ISE) and the optimal parameters can be obtained by minimizing the objective function using the proposed Biogeography Based Optimization (BBO) algorithm. …”
Article -
19
Power production optimization of model-free wind farm using smoothed functional algorithm
Published 2022“…Whereby, the SFA based method is used to optimize the control parameter of each wind turbine such that the total power production of wind farm is maximized. …”
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20
Data-driven PID controller of wind turbine systems using safe experimentation dynamics algorithm
Published 2024“…These results underscore the efficacy of the SEDA method in providing optimal PID control parameters while reducing computational burdens by 52% compared to other multi-agent optimization-based methods.…”
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