Dissertation Title: Efficient and Ultra-Clean Coal Combustion Control over Full-range Operating Conditions Driven by Physical Mechanism and Operating Data

Date: 2026/05/26 – 2026/05/26

Abstract

Driven by China’s Dual Carbon strategy and large-scale renewable energy integration, coal-fired boilers face increasing demands for high efficiency, low emissions, and deep peak-shaving capability. This dissertation proposes a hybrid combustion optimization framework combining physical mechanisms and operational data. An FGRT method is developed to improve SCR inlet temperature and suppress NOx formation under deep peak-shaving conditions. A NARX-based MPC strategy with a KS-function is proposed to optimize secondary air distribution and improve combustion uniformity. Furthermore, a PINN–MPC framework is established to enhance model generalization and physical consistency across operating conditions. The proposed methods support efficient, low-emission, and flexible operation of coal-fired boilers.

Biography

Zongyang Hu is a Ph.D. candidate in Control Science and Engineering at the Global College, Shanghai Jiao Tong University, under the supervision of Prof. Mian Li. During this period, Hu focuses on model predictive control and process control, and has published three first-author papers.