This article presents a novel reinforcement learning strategy that addresses an optimal
stabilizing problem for unknown nonlinear systems subject to uncertain input constraints …

This paper is focused on the observer-based adaptive fuzzy control problem for nonlinear
stochastic systems with the nonstrict-feedback form, in which some complicated and …

In this paper, we propose an adaptive fuzzy dynamic surface control (DSC) scheme for
single-link flexible-joint robotic systems with input saturation. A smooth function is utilized …

In this paper, through event-triggered approach, the constrained near-optimal control
problem for a class of nonlinear discrete-time systems is investigated and solved by heuristic …

In this article, an adaptive neural network (NN) tracking control scheme is proposed for
uncertain multi-input–multi-output (MIMO) nonlinear system in strict-feedback form subject to …

This paper investigates the problem of optimal fault-tolerant control (FTC) for a class of
unknown nonlinear discrete-time systems with actuator fault in the framework of adaptive …

In this paper, we present an optimal neuro-control scheme for continuous-time (CT)
nonlinear systems with asymmetric input constraints. Initially, we introduce a discounted cost …

Artificial neural networks (ANNs) have been used over the last few decades to perform tasks
by learning with comparisons. Fitting input-output models, system identification, control, and …

This paper proposes an event-based near-optimal control algorithm for nonaffine discrete-
time systems with constrained inputs. The method is derived from the dual heuristic dynamic …

In this article, using singular perturbation theory and adaptive dynamic programming (ADP)
approach, an adaptive composite suboptimal control method is proposed for linear …