AIMC Topic: Computer Simulation

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Granger Causality Inference in EEG Source Connectivity Analysis: A State-Space Approach.

IEEE transactions on neural networks and learning systems Jul 6, 2022
This article addresses the problem of estimating brain effective connectivity from electroencephalogram (EEG) signals using a Granger causality (GC) characterized on state-space models, extended from the conventional vector autoregressive (VAR) proce...
Humans Neural Networks, Computer Brain Computer Simulation Least-Squares Analysis Electroencephalography
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Observer-Based Fixed-Time Neural Control for a Class of Nonlinear Systems.

IEEE transactions on neural networks and learning systems Jul 6, 2022
This article is concerned with an issue of fixed time adaptive neural control for a class of uncertain nonlinear systems subject to hysteresis input and immeasurable states. The state observer and neural networks (NNs) are used to estimate the immeas...
Neural Networks, Computer Computer Simulation Feedback Nonlinear Dynamics Uncertainty
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Parameterized Luenberger-Type H State Estimator for Delayed Static Neural Networks.

IEEE transactions on neural networks and learning systems Jul 6, 2022
This article proposes a new Luenberger-type state estimator that has parameterized observer gains dependent on the activation function, to improve the H state estimation performance of the static neural networks with time-varying delay. The nonlinear...
Neural Networks, Computer Computer Simulation Time Factors
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A novel PID controller for BLDCM speed control using dual fuzzy logic systems with HSA optimization.

Scientific reports Jul 4, 2022
In order to enhance the speed control performance of the brushless DC motor (BLDCM), a novel proportion integration differentiation (PID) is proposed in this paper by using dual fuzzy logic systems (FLSs) with harmony search algorithm (HSA) optimizat...
Algorithms Computer Simulation Fuzzy Logic
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Spatial Iterative Learning Control for Robotic Path Learning.

IEEE transactions on cybernetics Jul 4, 2022
A spatial iterative learning control (sILC) method is proposed for a robot to learn a desired path in an unknown environment. When interacting with the environment, the robot initially starts with a predefined trajectory so an interaction force is ge...
Computer Simulation Learning Robotics Robotic Surgical Procedures Mechanical Phenomena
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Vibration Control of a Constrained Two-Link Flexible Robotic Manipulator With Fixed-Time Convergence.

IEEE transactions on cybernetics Jul 4, 2022
With the more extensive application of flexible robots, the expectation for flexible manipulators is also increasing rapidly. However, the fast convergence will cause the increase of vibration amplitude to some extent, and it is difficult to obtain v...
Computer Simulation Robotics Robotic Surgical Procedures Nonlinear Dynamics Vibration
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Anti-Saturation-Based Adaptive Sliding-Mode Control for Active Suspension Systems With Time-Varying Vertical Displacement and Speed Constraints.

IEEE transactions on cybernetics Jul 4, 2022
In this article, an adaptive sliding-mode control scheme is developed for a class of uncertain quarter vehicle active suspension systems with time-varying vertical displacement and speed constraints, in which the input saturation is considered. The i...
Neural Networks, Computer Computer Simulation Feedback Time Factors Nonlinear Dynamics
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Distributed Cooperative Compound Tracking Control for a Platoon of Vehicles With Adaptive NN.

IEEE transactions on cybernetics Jul 4, 2022
This article focuses on the distributed cooperative compound tracking issue of the vehicular platoon. First, a definition, called compound tracking control, is proposed, which means that the practical finite-time stability and asymptotical convergenc...
Neural Networks, Computer Algorithms Computer Simulation Feedback Nonlinear Dynamics
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Resilient Asynchronous State Estimation for Markovian Jump Neural Networks Subject to Stochastic Nonlinearities and Sensor Saturations.

IEEE transactions on cybernetics Jul 4, 2022
This article studies the problem of dissipativity-based asynchronous state estimation for a class of discrete-time Markov jump neural networks subject to randomly occurring nonlinearities, sensor saturations, and stochastic parameter uncertainties. F...
Neural Networks, Computer Computer Simulation Communication Time Factors Markov Chains
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Neural-Networks-Based Prescribed Tracking for Nonaffine Switched Nonlinear Time-Delay Systems.

IEEE transactions on cybernetics Jul 4, 2022
In this article, by using the neural-networks (NNs) separation and approximation technique, an adaptive scheme is presented to deliver the prescribed tracking performance for a class of unknown nonaffine switched nonlinear time-delay systems. The non...
Neural Networks, Computer Algorithms Computer Simulation Nonlinear Dynamics
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