Neural network-based flight control systems: Present and future

SA Emami, P Castaldi, A Banazadeh - Annual Reviews in Control, 2022 - Elsevier
As the first review in this field, this paper presents an in-depth mathematical view of
Intelligent Flight Control Systems (IFCSs), particularly those based on artificial neural …

Adaptive neural network control for a class of nonlinear systems with function constraints on states

YJ Liu, W Zhao, L Liu, D Li, S Tong… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
In this article, the problem of tracking control for a class of nonlinear time-varying full state
constrained systems is investigated. By constructing the time-varying asymmetric barrier …

Adaptive finite-time tracking control of full state constrained nonlinear systems with dead-zone

H Li, S Zhao, W He, R Lu - Automatica, 2019 - Elsevier
This paper investigates the problem of adaptive finite-time tracking control for strict-feedback
nonlinear continuous-time systems subject to full state constraints and dead-zone. By …

Singularity-free fixed-time fuzzy control for robotic systems with user-defined performance

Y Pan, P Du, H Xue, HK Lam - IEEE Transactions on Fuzzy …, 2020 - ieeexplore.ieee.org
In this article, the singularity-free adaptive fuzzy fixed-time control problem is studied for an
uncertain n-link robotic system with the position tracking error constraint. The controlled …

Adaptive-constrained impedance control for human–robot co-transportation

X Yu, B Li, W He, Y Feng, L Cheng… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
Human–robot co-transportation allows for a human and a robot to perform an object
transportation task cooperatively on a shared environment. This range of applications raises …

Adaptive control-based barrier Lyapunov functions for a class of stochastic nonlinear systems with full state constraints

YJ Liu, S Lu, S Tong, X Chen, CLP Chen, DJ Li - Automatica, 2018 - Elsevier
An adaptive control scheme is developed in the paper for nonlinear stochastic systems with
unknown parameters. All the states in the systems are required to be constrained in a …

Adaptive fuzzy neural network control for a constrained robot using impedance learning

W He, Y Dong - IEEE transactions on neural networks and …, 2017 - ieeexplore.ieee.org
This paper investigates adaptive fuzzy neural network (NN) control using impedance
learning for a constrained robot, subject to unknown system dynamics, the effect of state …

Adaptive output-feedback control design with prescribed performance for switched nonlinear systems

Y Li, S Tong, L Liu, G Feng - Automatica, 2017 - Elsevier
In this paper, an output feedback control method with prescribed performance is proposed
for single-input and single-output (SISO) switched non-strict-feedback nonlinear systems. It …

Reinforcement learning-based decentralized fault tolerant control for constrained interconnected nonlinear systems

Y Zhao, H Wang, N Xu, G Zong, X Zhao - Chaos, Solitons & Fractals, 2023 - Elsevier
This paper addresses the decentralized fault tolerant control problem for interconnected
nonlinear systems under a reinforcement learning strategy. The system under consideration …

Barrier Lyapunov functions-based adaptive control for a class of nonlinear pure-feedback systems with full state constraints

YJ Liu, S Tong - Automatica, 2016 - Elsevier
In this study, an adaptive control technique is developed for a class of uncertain nonlinear
parametric systems. The considered systems can be viewed as a class of nonlinear pure …