Search Results - (( variable system control algorithm ) OR ( java application optimization algorithm ))

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    Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

    Published 2016
    “…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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    Conference or Workshop Item
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    Route Optimization System by Zulkifli, Abdul Hayy

    Published 2005
    “…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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    Final Year Project
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    Study of nature inspired computing (NIC) technique for optimal reactive power dispatch problems by Sulaiman, Mohd Herwan

    Published 2017
    “…ORPD problem is a nonlinear optimization problem that involving both equality constraints and inequality constraints. The proposed algorithms are tested on five different case studies which are IEEE 30-bus system with 13 control variables, IEEE 30-bus system with 19 control variables, IEEE 30-bus system with 25 control variables, IEEE 57-bus system with 25 control variables and IEEE 118-bus system with 77 control variables. …”
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    Research Report
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    Variable Speed Control Of Two-Mass Wind Turbine System Via State Feedback With Adaptation Law by Mohamad Murad, Nor Syaza Farhana

    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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    Thesis
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    Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization by Nur Iffah, Mohamed Azmi

    Published 2014
    “…Controller that uses PID parameters requires a good tuning method in order to improve the control system performance. …”
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    Thesis
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    Optimization Of Sliding Mode Control Using Particle Swarm Algorithm For An Electro-Hydraulic Actuator System by Rozaimi, Ghazali

    Published 2016
    “…The dynamic parts of electro-hydraulic actuator(EHA) system are widely applied in the industrial field for the process that exposed to the motion control.In order to achieve accurate motion produced by these dynamic parts,an appropriate controller will be needed.However,the EHA system is well known to be nonlinear in nature.A great challenge is carried out in the EHA system modelling and the controller development due to its nonlinear characteristic and system complexity.An appropriate controller with proper controller parameters will be needed in order to maintain or enhance the performance of the utilized controller.This paper presents the optimization on the variables of sliding mode control (SMC) by using Particle Swarm Optimization (PSO) algorithm.The control scheme is established from the derived dynamic equation which stability is proven through Lyapunov theorem.From the obtained simulation results,it can be clearly inferred that the SMC controller variables tuning through PSO algorithm performed better compared with the conventional proportionalintegral-derivative (PID) controller.…”
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    Article
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    Automatic control of flotation process using computer vision by Saravani, Ali Jahed

    Published 2015
    “…A froth model correlating the image variables to process variables and a prediction system estimating the metallurgical parameters based on image variables were then developed by using a neural network structure. …”
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    Thesis
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    Artificial Robust Control of Robot Arm: Design a Novel SISO Backstepping Adaptive Lyapunov Based Variable Structure Control. by Sulaiman, Nasri, Piltan, Farzin, Jalali, Amin, Siamak, Sobhan, Nazari, Iman

    Published 2011
    “…This paper examines single input single output (SISO) chattering free variable structure control (VSC) which controller coefficient is on-line tuned by fuzzy backstepping algorithm. …”
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    Article
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    Neural network based model predictive control for a steel pickling process by Kittisupakorn, P., Thitiyasook, P., Hussain, Mohd Azlan, Daosud, W.

    Published 2009
    “…The Levenberg-Marquardt algorithm is used to train the process models. In the control (MPC) algorithm, the feedforward neural network models are used to predict the state variables over a prediction horizon within the model predictive control algorithm for searching the optimal control actions via sequential quadratic programming. …”
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    Article
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    Modification of a commercial PWM sprayer control system for precision farming application by Shahemabadi, Ali Rafiei, Moayed, Majid Javid

    Published 2008
    “…The variable-rate control system consisted of pulse width modulation (PWM) solenoids, a by pass control valve, and nozzle control system interfaced to a computer. …”
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    Conference or Workshop Item
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    Optimization of PID Parameters Utilizing Variable Weight Grey-Taguchi Method and Particle Swarm Optimization by Nur Iffah, Mohamed Azmi, Kamal Arifin, Mat Piah, Wan Azhar, Wan Yusoff, F. R. M., Romlay

    Published 2017
    “…Controller that uses PID parameters requires a good tuning method in order to improve the control system performance. …”
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    Application of genetic algorithm for optimal voltage control of the power system / Mohd Supian Yahya by Yahya, Mohd Supian

    Published 1998
    “…This project uses genetic algorithm (GA) for optimal voltage control of the power system and automatically will minimum a system loss. …”
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    Thesis
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    Data driven neuroendocrine pid controller for mimo plants based adaptive safe experimentation dynamics algorithm by Mohd Riduwan, Ghazali

    Published 2020
    “…Besides, in the existing NEPID controller structure of the SISO system, only a single node of hormone regulation is used due to a single control variable. …”
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    Thesis
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    Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT by Abdullah, Amran

    Published 2006
    “…Genetic Algorithm is one of the most popular optimization solutions used in various applications such as scheduling. …”
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    Thesis