AIMC Topic: Nonlinear Dynamics

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The deep arbitrary polynomial chaos neural network or how Deep Artificial Neural Networks could benefit from data-driven homogeneous chaos theory.

Neural networks : the official journal of the International Neural Network Society
Artificial Intelligence and Machine learning have been widely used in various fields of mathematical computing, physical modeling, computational science, communication science, and stochastic analysis. Approaches based on Deep Artificial Neural Netwo...

Hybridization of the swarming and interior point algorithms to solve the Rabinovich-Fabrikant system.

Scientific reports
In this study, a trustworthy swarming computing procedure is demonstrated for solving the nonlinear dynamics of the Rabinovich-Fabrikant system. The nonlinear system's dynamic depends upon the three differential equations. The computational stochasti...

Neural-Network-Based Adaptive Control of Uncertain MIMO Singularly Perturbed Systems With Full-State Constraints.

IEEE transactions on neural networks and learning systems
This article investigates the tracking control problem for a class of nonlinear multi-input-multi-output (MIMO) uncertain singularly perturbed systems (SPSs) with full-state constraints. The underlying issues become more challenging because two-time-...

Data-Driven H Optimal Output Feedback Control for Linear Discrete-Time Systems Based on Off-Policy Q-Learning.

IEEE transactions on neural networks and learning systems
This article develops two novel output feedback (OPFB) Q -learning algorithms, on-policy Q -learning and off-policy Q -learning, to solve H static OPFB control problem of linear discrete-time (DT) systems. The primary contribution of the proposed alg...

Local Stability and Convergence Analysis of Neural Network Controllers With Error Integral Inputs.

IEEE transactions on neural networks and learning systems
This article investigates the local stability and local convergence of a class of neural network (NN) controllers with error integrals as inputs for reference tracking. It is formally proved that if the input of the NN controller consists exclusively...

Intelligent solution predictive networks for non-linear tumor-immune delayed model.

Computer methods in biomechanics and biomedical engineering
In this article, we analyze the dynamics of the non-linear tumor-immune delayed (TID) model illustrating the interaction among tumor cells and the immune system (cytotoxic T lymphocytes, T helper cells), where the delays portray the times required fo...

Cooperative Game-Based Approximate Optimal Control of Modular Robot Manipulators for Human-Robot Collaboration.

IEEE transactions on cybernetics
Major challenges of controlling human-robot collaboration (HRC)-oriented modular robot manipulators (MRMs) include the estimation of human motion intention while cooperating with a robot and performance optimization. This article proposes a cooperati...

Nonfragile Output Feedback Tracking Control for Markov Jump Fuzzy Systems Based on Integral Reinforcement Learning Scheme.

IEEE transactions on cybernetics
In this article, a novel integral reinforcement learning (RL)-based nonfragile output feedback tracking control algorithm is proposed for uncertain Markov jump nonlinear systems presented by the Takagi-Sugeno fuzzy model. The problem of nonfragile co...

Evolving and Incremental Value Iteration Schemes for Nonlinear Discrete-Time Zero-Sum Games.

IEEE transactions on cybernetics
In this article, evolving and incremental value iteration (VI) frameworks are constructed to address the discrete-time zero-sum game problem. First, the evolving scheme means that the closed-loop system is regulated by using the evolving policy pair....

Adaptive Optimal Control of Hybrid Electric Vehicle Power Battery via Policy Learning.

Computational intelligence and neuroscience
An online policy learning algorithm is used to solve the optimal control problem of the power battery state of charge (SOC) observer for the first time. The design of adaptive neural network (NN) optimal control is studied for the nonlinear power bat...