Year: 2026
Type: article
Abstract: This paper introduces an Enhanced Generalized Modified Repetitive Control (EGMRC) scheme in which the compensator is derived directly in the continuous-time domain, avoiding conversion to a two-dimensional hybrid model. The proposed method is implemented for angular position tracking of a 1-DOF lower-limb robotic exoskeleton driven by a periodic reference. The closed-loop dynamics are expressed in an error-state form to explicitly capture the tracking objective. Controller gains are determined via linear matrix inequality (LMI) conditions to ensure asymptotic stability, while performance is shaped by tuning the relative contributions of the control and learning actions and by adjusting the internal-model filter cut-off frequency. Numerical studies verify the proposed approach and show that the most accurate tracking is obtained when the learning-action gain exceeds the control-action gain. The results further suggest that increasing the internal-model cut-off frequency generally improves tracking accuracy. Compared with generalized repetitive control (GRC), EGMRC achieves superior performance in the evaluated metrics, with the exception of settling time.
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W7164359226