Search Results - (( parameter estimation sensor algorithm ) OR ( using simulation method algorithm ))
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Sensorless Adaptive Fuzzy Logic Control Of Permanent Magnet Synchronous Motor
Published 2008“…Both experimental and simulation results obtained from the HMRASC and the position angle estimation algorithms showed superior results compared to other methods presented in the literature.…”
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Thesis -
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Speed sensorless control for PMSM drives using Extended Kalman Filter
Published 2021“…Therefore, this project proposes sensorless control using an EKF. This method provides an optional estimation algorithm for the non-linear system that can produce a fast and accurate estimation of state variables. …”
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Using Wireless Sensor Network (Wsn) Localization To Determine The Target Location
Published 2015“…Therefore, in this project, the simulation is used instead of running a real experiment in Wireless Sensor Networh (WSN). …”
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Final Year Project Report / IMRAD -
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EZ-SEP: extended Z-SEP routing protocol with hierarchical clustering approach for wireless heterogeneous sensor network
Published 2021“…EZ-SEP was executed and compared to routing protocols such as Z-SEP, SEP, and LEACH. The proposed algorithm performed using the MATLAB R2016b simulator. …”
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Direct Adaptive Predictive Control For Wastewater Treatment Plant
Published 2012“…The performances of both estimation and control algorithms are illustrated by simulation results. …”
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Conference or Workshop Item -
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Data filtering of 5-axis inertial measurement unit using kalman filter
Published 2013“…This thesis has the purpose to design and develop data filtering of 5-axis Inertial Measurement Unit (IMU) using Kalman Filter. This project endeavour to verify that the data from 5DOF IMU can be filtered using Kalman Filter method so that it can be used as an algorithm in motion alignment. …”
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Undergraduates Project Papers -
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Sensorless induction motor speed control for electric vehicles using enhanced hybrid flux estimator with ann-ifoc controller
Published 2022“…Basically, a speed sensor is used to sense an electric vehicle’s motor speed at the rated value in order to achieve a high tracking accuracy of the speed, but the use of a sensor is costly and it is sensitive to vibrations. …”
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Thesis -
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Indirect Rotor Field Oriented Control of Induction Motor With Rotor Time Constant Estimation
Published 2004“…Hence, this work focuses on the Indirect Rotor Field Oriented Control of induction motors with estimation of the rotor time constant. A simple yet effective rotor time constant identification method is presented and used for updating the slip calculator used by the IRFOC algorithms. …”
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Analysis of robot localisation performance based on extended kalman filter
Published 2015“…First is the performance of the algorithm using different parameters in which different velocities and number of landmarks have been used to determine the accuracy of the localisation method. …”
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Observer-based fault detection approach using fuzzy adaptive poles placement system with real-time implementation
Published 2021“…This paper validated the system simulation by implementing fault detection algorithms by using a real-time embedded observer-based system. …”
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Covariance matrix analysis in simultaneous localization and mapping
Published 2016“…Estimation at a specific time or also known as the filtering technique in estimation and control theory is a method to estimate the desired parameters from indirect and uncertain observations, taking into account the system and measurement errors. …”
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Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller
Published 2010“…In this regards, a new method of Pico-satellite attitude control using Mamdani Fuzzy Logic Principles is introduced. …”
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Thesis -
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IRFOC induction motor with rotor time constant estimation modelling and simulation
Published 2005“…Increased oscillations in the estimated inverse rotor time constant appeared at lower speeds (below 10 per cent of rated speed) due to drift in a PI regulator (used at the estimator side), which was tuned under rated operating conditions and using parameters nominal values.Research limitations/implications– This estimation scheme is limited when near zero speed operation is demanded; otherwise it gives a simple and practical solution. …”
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Hybrid fault detection using kalman filter and neural network for quadrotor micro aerial vehicle
Published 2018“…ANN is an algorithm that is used to determine the fault condition and determine its severity in the quadrotor system. …”
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Thesis -
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Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor / Muhammad Nasrul Hakim Adenan
Published 2013“…The algorithm will be developed in MATLAB. The objective of this project is to develop ANN model for ISFET sensor that able to estimate the main ion in mixed solution by learning the pattern of the input and output of the sensor. …”
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Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor: article / Muhammad Nasrul Hakim Adenan and Maizatul Zolkapli
Published 2013“…The algorithm will be developed in MATLAB. The objective of this project is to develop ANN model for ISFET sensor that able to estimate the main ion in mixed solution by learning the pattern of the input and output of the sensor. …”
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Performance study of direction of arrival (DOA) estimation algorithms for linear array antenna
Published 2009“…The analysis is based on linear array antenna and the calculation of the pseudospectra function of the estimation algorithms. Matlab is used for simulating the algorithms.…”
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Proceeding Paper -
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Novel chewing cycle approach for peak detection algorithm of chew count estimation
Published 2025“…The peak detection algorithm identifies key signal features, while PSO optimizes the peak prominence and width parameters to minimize the mean absolute error (MAE) in chew count estimation. …”
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Novel chewing cycle approach for peak detection algorithm of chew count estimation
Published 2025“…The peak detection algorithm identifies key signal features, while PSO optimizes the peak prominence and width parameters to minimize the mean absolute error (MAE) in chew count estimation. …”
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