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Nonlinear Dynamics

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Observer-based finite-time adaptive fuzzy back-stepping control for MIMO coupled nonlinear systems.

Mathematical biosciences and engineering : MBE
An attempt is made in this paper to devise a finite-time adaptive fuzzy back-stepping control scheme for a class of multi-input and multi-output (MIMO) coupled nonlinear systems with immeasurable states. In view of the uncertainty of the system, adap...

Complex dynamics in a Hopfield neural network under electromagnetic induction and electromagnetic radiation.

Chaos (Woodbury, N.Y.)
Due to the potential difference between two neurons and that between the inner and outer membranes of an individual neuron, the neural network is always exposed to complex electromagnetic environments. In this paper, we utilize a hyperbolic-type memr...

Data-driven reduced-order modeling of spatiotemporal chaos with neural ordinary differential equations.

Chaos (Woodbury, N.Y.)
Dissipative partial differential equations that exhibit chaotic dynamics tend to evolve to attractors that exist on finite-dimensional manifolds. We present a data-driven reduced-order modeling method that capitalizes on this fact by finding a coordi...

Reducing echo state network size with controllability matrices.

Chaos (Woodbury, N.Y.)
Echo state networks are a fast training variant of recurrent neural networks excelling at approximating nonlinear dynamical systems and time series prediction. These machine learning models act as nonlinear fading memory filters. While these models b...

An approach to solving optimal control problems of nonlinear systems by introducing detail-reward mechanism in deep reinforcement learning.

Mathematical biosciences and engineering : MBE
In recent years, dynamic programming and reinforcement learning theory have been widely used to solve the nonlinear control system (NCS). Among them, many achievements have been made in the construction of network model and system stability analysis,...

Sliding-mode controller synthesis of robotic manipulator based on a new modified reaching law.

Mathematical biosciences and engineering : MBE
In this study, an adaptive modified reaching law-based switch controller design was developed for robotic manipulator systems using the disturbance observer (DO) approach. Firstly, a standard DO is employed to estimate the unknown disturbances of the...

Feed-forward neural network as nonlinear dynamics integrator for supercontinuum generation: erratum.

Optics letters
We present an erratum to our Letter [Opt. Lett.47, 802 (2022)10.1364/OL.448571]. This erratum corrects an error in the sign of one of the higher-order dispersion coefficient used in the simulations of Figs. 2 and 4, as well as in Figs. S1 and S3. The...

Learn bifurcations of nonlinear parametric systems via equation-driven neural networks.

Chaos (Woodbury, N.Y.)
Nonlinear parametric systems have been widely used in modeling nonlinear dynamics in science and engineering. Bifurcation analysis of these nonlinear systems on the parameter space is usually used to study the solution structure, such as the number o...

Dynamic Markers for Chaotic Motion in C. elegans.

Nonlinear dynamics, psychology, and life sciences
We describe the locomotion of Caenorhabditis elegans (C. elegans) using nonlinear dynamics. C. elegans is a commonly studied model organism based on ease of maintenance and simple neurological structure. In contrast to traditional microscopic techniq...

Evolution of the Wilson-Cowan equations.

Biological cybernetics
The Wilson-Cowan equations were developed to provide a simplified yet powerful description of neural network dynamics. As such, they embraced nonlinear dynamics, but in an interpretable form. Most importantly, it was the first mathematical formulatio...