Observer-based adaptive optimal control for unknown singularly perturbed nonlinear systems with input constraints
This paper introduces an observer-based adaptive optimal control method for unknown
singularly perturbed nonlinear systems with input constraints. First, a multi-time scales …
singularly perturbed nonlinear systems with input constraints. First, a multi-time scales …
Adaptive optimal control of unknown nonlinear systems with different time scales
The adaptive optimal control of unknown nonlinear system with different time scales is
considered in this paper. The commonly used singular perturbation theory (SPT) to solve …
considered in this paper. The commonly used singular perturbation theory (SPT) to solve …
Neural network-based adaptive tracking control for a class of nonlinear singularly perturbed systems
In this paper, the neural network-based adaptive tracking control method is addressed for a
class of multi-input affine unknown nonlinear singularly perturbed systems. Based on the …
class of multi-input affine unknown nonlinear singularly perturbed systems. Based on the …
Neural-network-based adaptive control of uncertain MIMO singularly perturbed systems with full-state constraints
H Wang, C Yang, X Liu, L Zhou - IEEE Transactions on Neural …, 2021 - ieeexplore.ieee.org
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 …
output (MIMO) uncertain singularly perturbed systems (SPSs) with full-state constraints. The …
Identification and trajectory tracking control of nonlinear singularly perturbed systems
In this paper, a new identification and control scheme using multitime scale recurrent high-
order neural networks is proposed to control the singularly perturbed nonlinear systems with …
order neural networks is proposed to control the singularly perturbed nonlinear systems with …
Reinforcement learning for robust adaptive control of partially unknown nonlinear systems subject to unmatched uncertainties
This paper proposes a novel robust adaptive control strategy for partially unknown
continuous-time nonlinear systems subject to unmatched uncertainties. Initially, the robust …
continuous-time nonlinear systems subject to unmatched uncertainties. Initially, the robust …
Optimal output feedback control of nonlinear partially-unknown constrained-input systems using integral reinforcement learning
L Ren, G Zhang, C Mu - Neural Processing Letters, 2019 - Springer
The problem of output feedback optimal control of the partially-unknown nonlinear systems
with constrained-input is investigated in this paper. Firstly, a neural network observer is …
with constrained-input is investigated in this paper. Firstly, a neural network observer is …
Observer-based adaptive control of uncertain nonlinear systems via neural networks
C Mu, Y Zhang, K Wang - IEEE Access, 2018 - ieeexplore.ieee.org
In this paper, a novel observer-based control strategy is proposed for a class of uncertain
continuous-time nonlinear systems based on the Hamilton-Jacobi-Bellman (HJB) equation …
continuous-time nonlinear systems based on the Hamilton-Jacobi-Bellman (HJB) equation …
Neuroadaptive control of saturated nonlinear systems with disturbance compensation
Extended state observer acting as a popular tool can estimate the system states and total
disturbances simultaneously. However, for extended-state-observer-based control of high …
disturbances simultaneously. However, for extended-state-observer-based control of high …
Approximation-based disturbance observer approach for adaptive tracking of uncertain pure-feedback nonlinear systems with unmatched disturbances
HO Kim, SJ Yoo - International Journal of Systems Science, 2017 - Taylor & Francis
This paper presents an approximation-based nonlinear disturbance observer (NDO)
methodology for adaptive tracking of uncertain pure-feedback nonlinear systems with …
methodology for adaptive tracking of uncertain pure-feedback nonlinear systems with …