Kaixiang Peng

TL;DR: This paper investigates adaptive neural control methods for robotic manipulators, subject to uncertain plant dynamics and constraints on the joint position, in which the barrier Lyapunov function is employed to guarantee that the joint constraints are not violated.

TL;DR: The proposed KPI prediction and diagnosis scheme is finally applied to an industrial hot strip mill, and the results demonstrate the effectiveness of the proposed scheme.

TL;DR: The key performance indicator-based multivariate statistical process monitoring and fault diagnosis methods for linear static processes are surveyed and evaluated using the multivariate statistics framework and are broadly classified into three categories: direct, linear regression-based, and PLS-based.

TL;DR: It is shown using the real industrial data that for faults affecting the thickness and flatness of the strip steel in this process, the detection and diagnosis abilities are better compared with the existing methods.

TL;DR: The main focus of this paper is on the analysis and design scheme of performance-based fault detection and fault-tolerant control for automatic control systems with incipient (slowly developing) multiplicative faults.