To meet the progressively stringent demands for trajectory tracking performance in
precision/ultra-precision industry, multiple advanced feedforward compensation strategies …

This article presents a robust model predictive control (MPC) scheme for error-bounded
tracking of the magnetically levitated (maglev) planar motor. The motivation lies in bringing …

The traditional methodology utilized in dynamic tracking control synthesis is usually model-
based, and therefore, the performance is highly dependent on a precise mathematical …

Learning-based control methods utilize run-time data from the underlying process to
improve the controller performance under model mismatch and unmodeled disturbances …

This paper aims to overcome complex dynamic problems such as low damping resonant
frequency, resonant point drift, and uncertainty of dynamic model of the large stroke …

The proposed hierarchical learning framework induces a generalized optimal tracking
behavior for a control system. The L1 learning level ensures indirect closed-loop system …

To improve the trajectory tracking performance of planar motors against disturbances, model
predictive position control (MPPC) methods using the non‐linear disturbance observer …

Understanding complex systems by the help of modeling, simulation, and control is a well-
known challenge across several application domains. As such, these type of systems are not …

In this article, a dual-stage positioning system for precisely tracking continuous scan and
step scan profiles to meet the high-precision dynamic positioning requirements of space …

In many specific scenarios, accurate and effective system identification is a commonly
encountered challenge in the model predictive control (MPC) formulation. As a …