Search Results - (( variable integration control algorithm ) OR ( java simulation optimization algorithm ))
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1
Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…The simulation is implemented with iFogSim and java programming language. …”
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2
Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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3
Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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4
Shunt active power filter using hybrid fuzzy-proportional and crisp-integral control algorithms for total harmonic distortion improvement
Published 2016“…Hence, the use of conventional synchronization algorithms can be neglected.Second, an adaptive Hybrid Fuzzy-Proportional and Crisp-Integral (HFP+CI) current control algorithm is proposed, by using the indirect control strategy together with an integration of Fuzzy-Proportional (Fuzzy-P) and Crisp-Integral (Crisp-I) current controllers. …”
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5
OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT
Published 2023“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”
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Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization
Published 2014“…This research aims to improve the PSO-PID tuning algorithms by integrating the tuning process with the Variable Weight Grey-Taguchi Design of Experiment (DOE) method. …”
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7
Variable Speed Control Of Two-Mass Wind Turbine System Via State Feedback With Adaptation Law
Published 2018“…Wind turbine convert kinetic energy from the wind to rotational energy and then to electrical energy.In a wind energy conversion system (WECS),its electrical power control (EPC) side demanded a maximum mechanical power from the mechanical power control (MPC) side despite any intermittent wind and seasonal interference.Therefore,it is necessary to develop a variable speed algorithm for a modern WECS.For a two-mass horizontal axis wind turbine, the rotor and generator stiffness is commonly being neglected in the system dynamic.The inclusion of stiffness in system dynamic introduces integral term in the system expression and hence,incur mathematical complexity in the controller design phase.Contrary,this study consider stiffness as unknown parameter in the wind turbine dynamic.In order to obtain the maximum output power,the design of an algorithm with adaptation law for the speed control of a two-mass wind turbine system with an unknown stiffness is proposed in this research.The algorithm is formulated using a full-state feedback.In pursuance of solving the tracking control as a regulation case,the speed of the turbine is bijective mapped into the error dynamic.The stability of the proposed algorithm is guaranteed by Lyapunov.The adaptation law used in the variable speed algorithm is to successfully acquire the adaptability of the algorithm towards an unknown stiffness.Therein,the estimated stiffness is augmented in the Lyapunov function.The Lie derivative of the function is made into a negative semi-definite via the non-negative control parameters.In order to control the rotor speed to sustain the optimum tip-speed ratio (TSR),as well as obtaining the maximum power output from the turbine,the proposed algorithm is constructed.A MATLAB with Simulink® toolbox is used to validate the effectiveness of the proposed control speed.The simulation result showed that the rotor speed achieved an asymptotic tracking towards the demanded rotor speed irrespective of the stiffness value.The error is proved to be minimized as the integral of absolute error (IAE) obtained for wind turbine with stiffness ranging from 134550 Nmrad-1,269100 Nmrad-1,and 403650 Nmrad-1 are recorded as 0.003088,0.003063 and 0.003088 respectively. …”
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8
Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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9
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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Optimization of PID Parameters Utilizing Variable Weight Grey-Taguchi Method and Particle Swarm Optimization
Published 2017“…This research aims to improve the PSO-PID tuning algorithms by integrating the tuning process with the Variable Weight Grey-Taguchi Design of Experiment (DOE) method. …”
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Conference or Workshop Item -
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Resource management in grid computing using ant colony optimization
Published 2011“…Resources with high pheromone value are selected to process the submitted jobs.Global pheromone update is performed after completion processing the jobs in order to reduce the pheromone value of resources.A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against other ant based algorithm, in terms of resource utilization.Experimental results show that EACO produced better grid resource management solution.…”
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Monograph -
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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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Adaptive hybrid fuzzy-proportional plus crisp-integral current control algorithm for shunt active power filter operation
Published 2016“…The gain value is modified and controlled using the Fuzzy-P current controller’s output variable. …”
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15
Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter
Published 2019“…Cloudsim is used as Discrete Event Simulation tool and Java as coding language to evaluate LACE algorithm. …”
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16
A DC motor controller using PID algorithm implementation on PIC
Published 2008“…This project is about controlling the speed of DC servo motor by using Proportional-Integral-Derivative (PID) algorithm then implemented on Peripheral Interface Circuit (PIC) microcontroller. …”
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Undergraduates Project Papers -
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Optimal operation and control of hybrid power systems with stochastic renewables and FACTS devices: An intelligent multi-objective optimization approach
Published 2025“…including thyristor-controlled series compensators, static VAR compensators, and thyristor-controlled phase shifters. …”
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STUDIES ON COMPARISON OF PROPORTIONAL ON ERROR WITH PROPORTIONAL ON MEASURED VALUE IN PID CONTROLLERS
Published 2019“… PID Controllers have different algorithms or methods in which the controller action is based on Error or Process Variable (PV). …”
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Final Year Project -
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An improved neuroendocrine-proportional-integral-derivative controller with sigmoid-based secretion rate for nonlinear multi-input-multi-output crane systems
Published 2019“…The performance of the proposed sigmoid-based secretion rate neuroendocrine–proportional–integral–derivative controller-based safe experimentation dynamics algorithm is evaluated by tracking the error and the control input. …”
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Optimized fuzzy logic sliding mode control with proportional-integral-derivative for an electrohydraulic actuator system
Published 2023“…Due to the difficulty of concurrent hybrid design, the PSO algorithm was employed to determine the optimal control variables value. …”
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