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Adaptive neural network control for uncertain dual switching nonlinear systems.

Scientific reports
Dual switching system is a special hybrid system that contains both deterministic and stochastic switching subsystems. Due to its complex switching mechanism, few studies have been conducted for dual switching systems, especially for systems with unc...

Reinforcement Learning Control of Robotic Knee With Human-in-the-Loop by Flexible Policy Iteration.

IEEE transactions on neural networks and learning systems
We are motivated by the real challenges presented in a human-robot system to develop new designs that are efficient at data level and with performance guarantees, such as stability and optimality at system level. Existing approximate/adaptive dynamic...

Graph-Based Bayesian Optimization for Large-Scale Objective-Based Experimental Design.

IEEE transactions on neural networks and learning systems
Design is an inseparable part of most scientific and engineering tasks, including real and simulation-based experimental design processes and parameter/hyperparameter tuning/optimization. Several model-based experimental design techniques have been d...

Spherical Formation Tracking Control of Nonlinear Second-Order Agents With Adaptive Neural Flow Estimate.

IEEE transactions on neural networks and learning systems
This article addresses the spherical formation tracking control problem of nonlinear second-order vehicles moving in flowfields under both undirected networks and directed, strongly connected networks. Different from the previous adaptive estimate of...

Adaptive Observation-Based Efficient Reinforcement Learning for Uncertain Systems.

IEEE transactions on neural networks and learning systems
This article develops an adaptive observation-based efficient reinforcement learning (RL) approach for systems with uncertain drift dynamics. A novel concurrent learning adaptive extended observer (CL-AEO) is first designed to jointly estimate the sy...

Data-Driven Designs of Fault Detection Systems via Neural Network-Aided Learning.

IEEE transactions on neural networks and learning systems
With the aid of neural networks, this article develops two data-driven designs of fault detection (FD) for dynamic systems. The first neural network is constructed for generating residual signals in the so-called finite impulse response (FIR) filter-...

Co-creation environment with cloud virtual reality and real-time artificial intelligence toward the design of molecular robots.

Journal of integrative bioinformatics
This paper describes the design philosophy for our cloud-based virtual reality (VR) co-creation environment (CCE) for molecular modeling. Using interactive VR simulation can provide enhanced perspectives in molecular modeling for intuitive live demon...

Neural network-based event-triggered data-driven control of disturbed nonlinear systems with quantized input.

Neural networks : the official journal of the International Neural Network Society
This paper is devoted to design an event-triggered data-driven control for a class of disturbed nonlinear systems with quantized input. A uniform quantizer reconstructed with decreasing quantization intervals is employed to reduce the quantization er...

What are clinically relevant performance metrics in robotic surgery? A systematic review of the literature.

Journal of robotic surgery
A crucial element of any surgical training program is the ability to provide procedure-specific, objective, and reliable measures of performance. During robotic surgery, objective clinically relevant performance metrics (CRPMs) can provide tailored c...