AIMC Topic: Nonlinear Dynamics

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Global practical finite-time synchronization of disturbed inertial neural networks by delayed impulsive control.

Neural networks : the official journal of the International Neural Network Society
This paper delves into the practical finite-time synchronization (FTS) problem for inertial neural networks (INNs) with external disturbances. Firstly, based on Lyapunov theory, the local practical FTS of INNs with bounded external disturbances can b...

Differential Game-Based Control for Nonlinear Human-Robot Interaction System With Unknown Desired Trajectory.

IEEE transactions on cybernetics
Differential game is an effective technique to describe the negotiation between the humans and robots, which is widely used to realize the trajectory tracking tasks in the human-robot interaction (HRI). However, most existing works consider the contr...

Synchronization of time-delay dynamical networks via hybrid delayed impulses.

Neural networks : the official journal of the International Neural Network Society
This paper investigates the synchronization problem of time-delay dynamical networks by means of hybrid delayed impulses, where synchronizing impulses and desynchronizing impulses can occur simultaneously. Some sufficient synchronization conditions a...

Tracking control problem of nonlinear strict-feedback systems with input nonlinearity: An adaptive neural network dynamic surface control method.

PloS one
In this work, the tracking control problem for a class of nonlinear strict-feedback systems with input nonlinearity is addressed. In response to the influence of input nonlinearity, an auxiliary control system is constructed to compensate for it. To ...

Distributed leader-following bipartite consensus for one-sided Lipschitz multi-agent systems via dual-terminal event-triggered mechanism.

Neural networks : the official journal of the International Neural Network Society
This article analyses leader-following bipartite consensus for one-sided Lipschitz multi-agent systems by dual-terminal event-triggered output feedback control approach. A distributed observer is designed to estimate unknown system states by employin...

Modelling multivariate spatio-temporal data with identifiable variational autoencoders.

Neural networks : the official journal of the International Neural Network Society
Modelling multivariate spatio-temporal data with complex dependency structures is a challenging task but can be simplified by assuming that the original variables are generated from independent latent components. If these components are found, they c...

Dynamic dissipative control for fuzzy distributed parameter cyber physical system under input quantization and DoS attack.

PloS one
This article explores the dissipative control for a class of nonlinear DP-CPS (distributed parameter cyber physical system) within a finite-time interval. By utilizing a Takagi-Sugeno (T-S) fuzzy model to represent the system's nonlinear aspects, the...

Physical reservoir computing on a soft bio-inspired swimmer.

Neural networks : the official journal of the International Neural Network Society
Bio-inspired Autonomous Underwater Vehicles with soft bodies provide significant performance benefits over conventional propeller-driven vehicles; however, it is difficult to control these vehicles due to their soft underactuated bodies. This study i...

Referring Image Segmentation with Multi-Modal Feature Interaction and Alignment Based on Convolutional Nonlinear Spiking Neural Membrane Systems.

International journal of neural systems
Referring image segmentation aims to accurately align image pixels and text features for object segmentation based on natural language descriptions. This paper proposes NSNPRIS (convolutional nonlinear spiking neural P systems for referring image seg...

Spectral integrated neural networks (SINNs) for solving forward and inverse dynamic problems.

Neural networks : the official journal of the International Neural Network Society
This study introduces an innovative neural network framework named spectral integrated neural networks (SINNs) to address both forward and inverse dynamic problems in three-dimensional space. In the SINNs, the spectral integration technique is utiliz...