Search Results - (( control optimization methods algorithm ) OR ( user evaluation method algorithm ))
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PID TUNING OF DC MOTOR USING SWARM ITELLIGENCE ALGORITHM
Published 2012“…In this project, Particle Swarm Optimization (PSO) as one of Swarm Intelligence Algorithm based has proposed to be integrated with PID (Proportional, Integral, Derivative) Controller in order to achieve optimal tuning method. …”
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Final Year Project -
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An improved marine predators algorithm tuned data-driven multiple-node hormone regulation neuroendocrine-PID controller for multi-input–multi-output gantry crane system
Published 2023“…Comparative findings alongside other existing metaheuristic-based algorithms confirmed excellence of the proposed method through its superior performance against the conventional MPA, particle swarm optimization (PSO), grey wolf optimizer (GWO), moth-flame optimization (MFO), multi-verse optimizer (MVO), sine-cosine algorithm (SCA), salp-swarm algorithm (SSA), slime mould algorithm (SMA), flow direction algorithm (FDA), and the formally published adaptive safe experimentation dynamics (ASED)-based methods.…”
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Performance Comparison of Nature-inspired Optimization Algorithms Applied to MVDR Technique for Canceling Multiple Access Interference Signals
Published 2018“…Methods/Analysis: In this work, two nature-inspired optimization methods, namely Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA) are applied to enhancing the conventional MVDR performance. …”
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Modular motor driver with torque control for gripping mechanism
Published 2023“…These graphical outputs of the controller was evaluated based on the response time, degree of overshooting, and steady-state error to determine the most optimal method of control to be implemented in torque control scheme. …”
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3D virtual modelling and stabilization control of triple links inverted pendulum on two-wheeled system using enhanced interval type-2 fuzzy logic control
Published 2020“…Without a specific method introduced to determine the optimal values of input and output control gains, as well as the IT2FLC control parameters, optimization algorithm has been applied to enhance the system's performance in term of stability and disturbance rejection. …”
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Thesis -
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Electroencephalogram signal interpretation system for mobile robot
Published 2013“…The aim of this project is to develop an algorithm that can choose optimal four electrodes for signal recording, and convert one thought into multiple commands with the chosen electrodes. …”
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Thesis -
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Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks
Published 2025thesis::doctoral thesis -
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Energy-efficient power allocation and joint user association in multiuser-downlink massive MIMO system
Published 2019“…The study aims to maximize the non-convex EE in a downlink (DL) massive MIMO system using a proposed energy-efficient low-complexity algorithm (EELCA) that guarantees optimal power allocation solution based on Newton’s methods and joint user’s association based on the Lagrange’s decomposition method. …”
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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…The performance of DE algorithm depends heavily on the selected mutation strategy and its associated control parameters. …”
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Thesis -
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Dynamic approaches for spectrum control in cognitive radio networks
Published 2015“…This is done by allowing secondary users (unlicensed users) to access licensed spectrum if the primary user (licensed user) is not using it. …”
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Thesis -
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Imposed weighting factor optimization method for torque ripple reduction of IM fed by indirect matrix converter with predictive control algorithm
Published 2015“…This paper proposes a weighting factor optimization method in predictive control algorithm for torque ripple reduction in an induction motor fed by an indirect matrix converter (IMC). …”
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Harmony search-based robust optimal controller with prior defined structure
Published 2013“…In this approach, a combination of interacting two levels HS optimization algorithm is presented. In the first level, a new method for analytical formulation of integral square error cost function based on controller variables is elaborated for performance evaluation purposes by the proposed optimization algorithm. …”
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Thesis -
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Optimized PID controller of DC-DC buck converter based on archimedes optimization algorithm
Published 2023“…This study concludes that the AOA optimization algorithm surpasses other methods in tuning the PID controller for closed-loop DC-DC buck converters.…”
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BBO algorithm-based tuning of PID controller for speed control of synchronous machine
Published 2023Article -
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Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques
Published 2018“…To deal with these problems, this thesis introduces three approved intelligent controllers for hydropower generation. Firstly, a hybrid algorithm namely firefly particle swarm optimization (FPSO) and series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed. …”
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Thesis -
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Genetic algorithm based method for optimal location placement of flexible ac transmission system devices for voltage profile improvement
Published 2011“…This thesis present a genetic algorithm based method for placement of FACTS devices for voltage profile improvement. …”
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Thesis -
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Position tracking of DC motor with PID controller utilizing particle swarm optimization algorithm with lévy flight and doppler effect
Published 2025“…Traditional optimization algorithms like particle swarm optimization, whale optimization algorithm, grey wolf optimizer, and moth flame optimization often face challenges in balancing exploration and exploitation, leading to suboptimal performance. …”
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Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study
Published 2023“…—Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
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