AIMC Topic: Computer Simulation

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Robust Fixed-Time H∞ Trajectory Tracking Control for Marine Surface Vessels Based on a Self-Structuring Neural Network.

Computational intelligence and neuroscience
In this study, a robust fixed-time H∞ trajectory tracking controller for marine surface vessels (MSVs) is proposed based on self-structuring neural network (SSNN). First, a fixed-time H Lyapunov stability theorem is proposed to guarantee that the MSV...

Employing Artificial Neural Networks to Identify Reaction Coordinates and Pathways for Self-Assembly.

The journal of physical chemistry. B
Capturing the autonomous self-assembly of molecular building blocks in computer simulations is a persistent challenge, requiring to model complex interactions and to access long time scales. Advanced sampling methods allow to bridge these time scales...

Design and Research of an Articulated Tracked Firefighting Robot.

Sensors (Basel, Switzerland)
Aiming to improve the situation where a firefighting robot is affected by conditions of space and complex terrain, a small four-track, four-drive articulated tracked fire-extinguishing robot is designed, which can flexibly perform fire detection and ...

A Two-Stage Feature Point Detection and Marking Approach Based on the Labeled Multi-Bernoulli Filter.

Sensors (Basel, Switzerland)
In recent years, various algorithms using random finite sets (RFS) to solve the issue of simultaneous localization and mapping (SLAM) have been proposed. Compared with the traditional method, the advantage of the RFS method is that it can avoid data ...

Recurrent neural network based high-precision position compensation control of magnetic levitation system.

Scientific reports
For improving the dynamic quality and steady-state performance, the hybrid controller based on recurrent neural network (RNN) is designed to implement the position control of the magnetic levitation ball system in this study. This hybrid controller c...

Deep learning from phylogenies to uncover the epidemiological dynamics of outbreaks.

Nature communications
Widely applicable, accurate and fast inference methods in phylodynamics are needed to fully profit from the richness of genetic data in uncovering the dynamics of epidemics. Standard methods, including maximum-likelihood and Bayesian approaches, gene...

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

IEEE transactions on neural networks and learning systems
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...

Observer-Based Fixed-Time Neural Control for a Class of Nonlinear Systems.

IEEE transactions on neural networks and learning systems
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...

Parameterized Luenberger-Type H State Estimator for Delayed Static Neural Networks.

IEEE transactions on neural networks and learning systems
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...

A novel PID controller for BLDCM speed control using dual fuzzy logic systems with HSA optimization.

Scientific reports
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...