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Centralized and Collective Neurodynamic Optimization Approaches for Sparse Signal Reconstruction via L₁-Minimization.

IEEE transactions on neural networks and learning systems
This article develops several centralized and collective neurodynamic approaches for sparse signal reconstruction by solving the L -minimization problem. First, two centralized neurodynamic approaches are designed based on the augmented Lagrange meth...

Prescribed Finite-Time Adaptive Neural Tracking Control for Nonlinear State-Constrained Systems: Barrier Function Approach.

IEEE transactions on neural networks and learning systems
The purpose of this article is to present a novel backstepping-based adaptive neural tracking control design procedure for nonlinear systems with time-varying state constraints. The designed adaptive neural tracking controller is expected to have the...

Adaptive Deformation Control of a Flexible Variable-Length Rotary Crane Arm With Asymmetric Input-Output Constraints.

IEEE transactions on cybernetics
This article constructs two adaptive control laws to achieve deformation reduction and attitude tracking for a rotary variable-length crane arm with system parameter uncertainties and asymmetric input-output constraints. Two auxiliary systems are giv...

Adaptive Prescribed Performance Control of A Flexible-Joint Robotic Manipulator With Dynamic Uncertainties.

IEEE transactions on cybernetics
An adaptive fuzzy control strategy is proposed for a single-link flexible-joint robotic manipulator (SFRM) with prescribed performance, in which the unknown nonlinearity is identified by adopting the fuzzy-logic system. By designing a performance fun...

Robust Composite H Synchronization of Markov Jump Reaction-Diffusion Neural Networks via a Disturbance Observer-Based Method.

IEEE transactions on cybernetics
This article focuses on the composite H synchronization problem for jumping reaction-diffusion neural networks (NNs) with multiple kinds of disturbances. Due to the existence of disturbance effects, the performance of the aforementioned system would ...

Robust Adaptive Neural Control for Wing-Sail-Assisted Vehicle via the Multiport Event-Triggered Approach.

IEEE transactions on cybernetics
This article presents a robust adaptive neural control algorithm for the wing-sail-assisted vehicle to track the desired waypoint-based route, where the event-triggered mechanism is with the multiport form. The main features of the proposed algorithm...

Reinforcement learning for robust stabilization of nonlinear systems with asymmetric saturating actuators.

Neural networks : the official journal of the International Neural Network Society
We study the robust stabilization problem of a class of nonlinear systems with asymmetric saturating actuators and mismatched disturbances. Initially, we convert such a robust stabilization problem into a nonlinear-constrained optimal control problem...

Control Strategy of an Underactuated Underwater Drone-Shape Robot for Grasping Tasks.

Sensors (Basel, Switzerland)
In underwater environments, ensuring people's safety is complicated, with potentially life-threatening outcomes, especially when divers have to work in deeper conditions. To improve the available solutions for working with robots in this kind of envi...

Microsatellite Uncertainty Control Using Deterministic Artificial Intelligence.

Sensors (Basel, Switzerland)
This manuscript explores the applications of deterministic artificial intelligence (DAI) in a space environment in response to unknown sensor noise and sudden changes in craft physical parameters. The current state of the art literature has proposed ...

Event-triggered adaptive dynamic programming for decentralized tracking control of input constrained unknown nonlinear interconnected systems.

Neural networks : the official journal of the International Neural Network Society
This paper addresses decentralized tracking control (DTC) problems for input constrained unknown nonlinear interconnected systems via event-triggered adaptive dynamic programming. To reconstruct the system dynamics, a neural-network-based local obser...