ILC has been a major control design methodology for twenty years; numerous algorithms
have been developed to solve real-time control problems, from MEMS to batch reactors …

This paper proposes the design of robust repetitive control with time-varying sampling
periods. First, it develops a new frequency domain method to design a low-order, stable …

Introduction: Digital technology platforms offer unparalleled opportunities to reach
vulnerable adolescents at scale and overcome many barriers that exist around conventional …

This paper addresses neural network (NN) control of a lower limb exoskeleton for
rehabilitation. Two control schemes are presented for exoskeleton to conduct trajectory …

In this brief, continuous-time nonlinear systems with extended matching uncertainties are
considered. The problem of designing a state-feedback adaptive learning control of reduced …

This article proposes a prescribed-time robust repetitive learning control scheme for
uncertain permanent magnet synchronous motor (PMSM) servo systems. An error-tracking …

In this paper, a novel excitation control is designed for improvement of transient stability of
power systems. The control algorithm is based on the adaptive backstepping method in a …

This article presents neural learning based adaptive impedance control for a lower limb
rehabilitation exoskeleton with flexible joints (LLREFJ). First, the full model consisting of both …

In order to asymptotically track the desired trajectory of nonlinear systems with unidirectional
control input under various uncertainties, a modified saturated learning-based control law …

A novel active disturbance rejection based repetitive learning control scheme, including
three channels, namely, feedforward, feedback, and disturbance rejection channels, is …