AIMC Topic: Nonlinear Dynamics

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Event-triggered fault-tolerant control for input-constrained nonlinear systems with mismatched disturbances via adaptive dynamic programming.

Neural networks : the official journal of the International Neural Network Society
In this paper, the issue of event-triggered optimal fault-tolerant control is investigated for input-constrained nonlinear systems with mismatched disturbances. To eliminate the effect of abrupt faults and ensure the optimal performance of general no...

Tree-structured neural networks: Spatiotemporal dynamics and optimal control.

Neural networks : the official journal of the International Neural Network Society
How the network topology drives the response dynamic is a basic question that has not yet been fully answered in neural networks. Elucidating the internal relation between topological structures and dynamics is instrumental in our understanding of br...

Optimal H tracking control of nonlinear systems with zero-equilibrium-free via novel adaptive critic designs.

Neural networks : the official journal of the International Neural Network Society
In this paper, a novel adaptive critic control method is designed to solve an optimal H tracking control problem for continuous nonlinear systems with nonzero equilibrium based on adaptive dynamic programming (ADP). To guarantee the finiteness of a c...

Dynamic event-triggered controller design for nonlinear systems: Reinforcement learning strategy.

Neural networks : the official journal of the International Neural Network Society
The current investigation aims at the optimal control problem for discrete-time nonstrict-feedback nonlinear systems by invoking the reinforcement learning-based backstepping technique and neural networks. The dynamic-event-triggered control strategy...

A Prediction Model Based on Gated Nonlinear Spiking Neural Systems.

International journal of neural systems
Nonlinear spiking neural P (NSNP) systems are one of neural-like membrane computing models, abstracted by nonlinear spiking mechanisms of biological neurons. NSNP systems have a nonlinear structure and can show rich nonlinear dynamics. In this paper,...

Stable isotope and trace element analyses with non-linear machine-learning data analysis improved coffee origin classification and marker selection.

Journal of the science of food and agriculture
BACKGROUND: This study investigated the geographical origin classification of green coffee beans from continental to country and regional levels. An innovative approach combined stable isotope and trace element analyses with non-linear machine learni...

Improved disturbance observer-based fixed-time adaptive neural network consensus tracking for nonlinear multi-agent systems.

Neural networks : the official journal of the International Neural Network Society
This paper is concerned with the problem of fixed-time consensus tracking for a class of nonlinear multi-agent systems subject to unknown disturbances. Firstly, a modified fixed-time disturbance observer is devised to estimate the unknown mismatched ...

Nonlinear function-on-scalar regression via functional universal approximation.

Biometrics
We consider general nonlinear function-on-scalar (FOS) regression models, where the functional response depends on multiple scalar predictors in a general unknown nonlinear form. Existing methods either assume specific model forms (e.g., additive mod...

Neural-Network-Based Immune Optimization Regulation Using Adaptive Dynamic Programming.

IEEE transactions on cybernetics
This article investigates optimal regulation scheme between tumor and immune cells based on the adaptive dynamic programming (ADP) approach. The therapeutic goal is to inhibit the growth of tumor cells to allowable injury degree and maximize the numb...

A computational framework for physics-informed symbolic regression with straightforward integration of domain knowledge.

Scientific reports
Discovering a meaningful symbolic expression that explains experimental data is a fundamental challenge in many scientific fields. We present a novel, open-source computational framework called Scientist-Machine Equation Detector (SciMED), which inte...