AIMC Topic: Feedback

Clear Filters Showing 231 to 240 of 622 articles

Neural-Network Adaptive Output-Feedback Saturation Control for Uncertain Active Suspension Systems.

IEEE transactions on cybernetics
The adaptive neural-network (NN) output-feedback control problem is investigated for a quarter-car active suspension system. The sprung mass and the suspension stiffness in the considered suspension system are unknown, and the part states are not mea...

Finite-Time Dynamic Allocation and Control in Multiagent Coordination for Target Tracking.

IEEE transactions on cybernetics
A new finite-time dynamic allocation and control scheme is developed in this article for multiple agents tracking a moving target. Based on a competitive manner, the dynamic allocation is achieved by k-winners-take-all (k-WTA), which can be realized ...

System Transformation-Based Neural Control for Full-State-Constrained Pure-Feedback Systems via Disturbance Observer.

IEEE transactions on cybernetics
In this article, a novel disturbance observer-based adaptive neural control (ANC) scheme is proposed for full-state-constrained pure-feedback nonlinear systems using a new system transformation method. A nonlinear transformation function in a uniform...

A differential Hebbian framework for biologically-plausible motor control.

Neural networks : the official journal of the International Neural Network Society
In this paper we explore a neural control architecture that is both biologically plausible, and capable of fully autonomous learning. It consists of feedback controllers that learn to achieve a desired state by selecting the errors that should drive ...

Deep learning for 1-bit compressed sensing-based superimposed CSI feedback.

PloS one
In frequency-division duplexing (FDD) massive multiple-input multiple-output (MIMO) systems, 1-bit compressed sensing (CS)-based superimposed channel state information (CSI) feedback has shown many advantages, while still faces many challenges, such ...

Composite-Learning-Based Adaptive Neural Control for Dual-Arm Robots With Relative Motion.

IEEE transactions on neural networks and learning systems
This article presents an adaptive control method for dual-arm robot systems to perform bimanual tasks under modeling uncertainties. Different from the traditional symmetric bimanual robot control, we study the dual-arm robot control with relative mot...

Optimal Synchronization of Unidirectionally Coupled FO Chaotic Electromechanical Devices With the Hierarchical Neural Network.

IEEE transactions on neural networks and learning systems
This article solves the problem of optimal synchronization, which is important but challenging for coupled fractional-order (FO) chaotic electromechanical devices composed of mechanical and electrical oscillators and electromagnetic filed by using a ...

Output Feedback Control of Micromechanical Gyroscopes Using Neural Networks and Disturbance Observer.

IEEE transactions on neural networks and learning systems
This article addresses the output feedback control of micromechanical (MEMS) gyroscopes using neural networks (NNs) and disturbance observer (DOB). For the unmeasured system states, the state observer and the high gain observer are constructed. The a...

Event-Triggered Output Feedback Synchronization of Master-Slave Neural Networks Under Deception Attacks.

IEEE transactions on neural networks and learning systems
The problem of event-triggered synchronization of master-slave neural networks is investigated in this article. It is assumed that both communication channels from the sensor to controller and from controller to actuator are subject to stochastic dec...

Secure predictor-based neural dynamic surface control of nonlinear cyber-physical systems against sensor and actuator attacks.

ISA transactions
This paper addresses a secure predictor-based neural dynamic surface control (SPNDSC) issue for a cyber-physical system in a nontriangular form suffering from both sensor and actuator deception attacks. To avoid the algebraic loop problem, only parti...