Search Results - intelligence _ ((force algorithm) OR (new algorithm))
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Active force control with iterative learning control algorithm for a vehicle suspension
Published 2013“…The new control scheme named active force control with iterative learning control algorithm (AFCIL) is complemented by the classic proportionalintegral-derivative (PID) control incorporated and designed as the outermost control loop. …”
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An intelligent method to estimate the inertia matrix of a robot arm for active force control using on-line neural network training scheme
Published 1999“…This paper presents a new intelligent controller algorithm comprising an on-line multi-layer artificial neural network (ANN) training scheme to estimate the inertia matrix of the robot arm to enhance the performance of the active force control (AFC) scheme. …”
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Real time self-calibration algorithm of pressure sensor for robotic hand glove system
Published 2019“…This study investigates the use of a novel Proposed Self-Calibration Algorithm (PSCA) of multi pressure sensors in real time on robotic hand glove system. …”
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Optimizing the Social Force Model Using New Hybrid WOABAT-IFDO in Crowd Evacuation in Panic Situation
Published 2022“…As the current classical evacuation model, the Social Force Model lacks decision-making ability for finding the best directions towards an exit. …”
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Proceeding -
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Multi agent quality of service routing based on scheme ant colony optimization algorithm
Published 2014“…The proposed scheme has been simulated by OMNET++ and compared with standard AntNet and two well-known standard QoS routings; Widest Shortest Path (WSP) algorithm and Shortest Widest Path (SWP) algorithm. …”
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Intelligent Optimization of Force Tracking Parameters for MR Damper Modelling using Firefly Algorithm
Published 2020“…To overcome this problem, an intelligent optimization method known as firefly algorithm (FA) was used by this study to optimize the force tracking controller (FTC) parameters as to achieve the exact damping force of MR damper system. …”
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Proceeding -
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A review of classification techniques for electromyography signals
Published 2023“…Machine Learning (ML) is an area of Artificial Intelligent (AI) with a concept that a computer program can learn and familiarize to new data without human intervention. …”
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An Intelligent Active Force Control Algorithm to Control an Upper Extremity Exoskeleton for Motor Recovery
Published 2016“…A proportional-derivative (PD) architecture is employed in this study to investigate its efficacy performing joint-space control objectives. An intelligent AFC algorithm is also incorporated into the PD to investigate the effectiveness of this hybrid system in compensating disturbances. …”
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A hybrid intelligent active force controller for robot arms using evolutionary neural networks
Published 2000“…The EC part of the algorithm composes of a hybrid genetic algorithm (GA) and an evolutionary program (EP). …”
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A fuzzy-active force based control architecture for characterizing a nonlinear MIMO system / Tengku Luqman Tengku Mohamed
Published 2016“…This study examines the modelling and control of a twin rotor multi-input multi-output (MIMO) system (TRMS). An intelligent Active Force Control (AFC) scheme is utilised to compensate disturbances that a conventional PID control algorithm alone is unable to due to the system’s highly nonlinear behaviour. …”
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Surface defect detection and polishing parameter optimization using image processing for G3141 cold rolled steel
Published 2016“…To realize this, automatic cropping algorithm is developed to detect the region of interest and interpret the Ga value. …”
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Hybrid intelligent active force controller for robot arms using evolutionary neural networks
Published 2000“…The EC part of the algorithm composes of a hybrid genetic algorithm (GA) and an evolutionary program (EP). …”
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ICS cyber attack detection with ensemble machine learning and DPI using cyber-Kit datasets
Published 2021“…The processed metadata is normalized for the easiness of algorithm analysis and modelled with machine learning-based latest deep learning ensemble LSTM algorithms for anomaly detection. …”
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Proceeding Paper
