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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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Intelligent adaptive active force control of a robotic arm with embedded iterative learning algorithms
Published 2001“…Two main iterative learning algorithms are utilized in the study – the first is used to automatically tune the controller gains while the second to estimate the inertia matrix of the manipulator. …”
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Adaptive active force control of a robotic arm employing twin iterative learning algorithms / Musa Mailah and Ong Miaw Yong
Published 2004“…Two iterative learning algorithms are employed in the study - the first is used to tune automatically the controller gains while the second to estimate the inertia matrix of the robotic arm. …”
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Intelligent active force control of a rigid robot arm using embedded iterative learning algorithm
Published 2000“…The paper presents a novel approach to estimating the inertia matrix of a robot arm adaptively and on-line using an iterative learning algorithm. It is employed in conjunction with an active force control strategy which has been shown to be very effective in accommodating the disturbances. …”
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Active Suspension System for Passenger Vehicle using Active Force Control with Iterative Learning Algorithm
Published 2014“…The paper describes the practical implementation of a new hybrid control method to a vehicle suspension system using Active Force Control (AFC) with Iterative Learning (IL) and proportional-integralderivative (PID) control strategy. …”
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Optimising neural network training efficiency through spectral parameter-based multiple adaptive learning rates
Published 2024“…The process of training neural networks heavily involves solving optimization problems. Most optimization algorithms use a !xed learning rate or a simpli!ed adaptive updating scheme in every iteration. …”
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Max-D clustering K-means algorithm for Autogeneration of Centroids and Distance of Data Points Cluster
“…K-Means is one of the unsupervised learning and partitioning clustering algorithms. It is very popular and widely used for its simplicity and fastness. …”
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Enhancement of network security by use machine learning
Published 2019“…This research is about the design and simulation on enhancement network security using machine learning. The design use MATLAB coding to show the simulation. …”
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MaxD K-Means: A clustering algorithm for auto-generation of centroids and distance of data points in clusters
Published 2012“…K-Means is one of the unsupervised learning and partitioning clustering algorithms. It is very popular and widely used for its simplicity and fastness. …”
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Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS
Published 2017“…Since extreme learning machine is a non-iterative estimation procedure, it is faster than gradient-based algorithms which are iterative. …”
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Kelantan daily water level prediction model using hybrid deep-learning algorithm for flood forecasting
Published 2021“…Therefore, this present study had imputed the missing hydrological data using five imputation methods, namely Neural Network (NN), Moving Median (MM), Iterative Algorithm (IA), Nonlinear Iterative Partial Least Square (NIPALS), and Combined Correlation with Inversed Distance (CCID) imputation methods. …”
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Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering
Published 2024“…To address this issue, this study incorporated joint graph learning from the gmc algorithm into swmcan, creating a new algorithm called swmcan-jg. …”
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Development of an Adaptive Algorithm for Solving the Inverse Kinematics Problem for Serial Robot Manipulators
Published 2005“…Artificial Neural Networks (ANN) technique has been utilized where learning is done iteratively based only on observation of input-output relationship. …”
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Advanced flood prediction at forest with rainfall data using various machine learning algorithms
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Vision based automatic steering control using a PID controller
Published 2006“…This is then extended to incorporate iterative learning control with genetic algorithm (GA) to optimize the learning parameters and a feedforward controller based on input shaping techniques for control of vibration (flexible motion) of the system. …”
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Hardware-in-the-Loop Simulation for Active Force Control with Iterative Learning Applied to an Active Vehicle Suspension System
Published 2014“…The paper focuses on the practical implementation of a novel control method to an automotive suspension system using active force control (AFC) with iterative learning algorithm (ILA) and proportional-integral-derivative (PID) control strategy. …”
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