From a functional standpoint, classic robots are not at all similar to biological systems. If
compared with rigid robots, animals' bodies look overly redundant, imprecise, and weak …

This paper proposes a unified framework of iterative learning control for typical flexible
structures under spatiotemporally varying disturbances. Input constraints and the external …

This paper investigates adaptive neural control methods for robotic manipulators, subject to
uncertain plant dynamics and constraints on the joint position. The barrier Lyapunov function …

This paper examines the boundary disturbance observer-based control for a vibrating single-
link flexible manipulator system possessing external disturbances. Two new boundary anti …

This paper focuses on a new finite-time convergence disturbance rejection control scheme
design for a flexible Timoshenko manipulator subject to extraneous disturbances. To …

In this article, an echo state network (ESN)-based backstep** adaptive iterative learning
control scheme is proposed for nonlinear strict-feedback systems performing the same …

This article proposes a new framework using physics-informed neural networks (PINNs) to
simulate complex structural systems that consist of single and double beams based on Euler …

This article presents a control scheme for stabilizing a vibrating flexible hose used for aerial
refueling subject to bounded actuators for the rate and magnitude. A dynamical model of …

This paper proposes adaptive iterative learning control (ILC) schemes for continuous-time
parametric nonlinear systems with iteration lengths that randomly vary. As opposed to the …

In this paper, a novel data-driven predictive iterative learning control (DDPILC) scheme
based on a radial basis function neural network (RBFNN) is proposed for a class of …