Substrate temperature estimation and control in advanced MOCVD process for superconductor manufacturing

The estimation and control of the substrate temperature in the Metal Organic Chemical Vapor Deposition (MOCVD) of superconductor tape manufacturing is investigated. In the advanced MOCVD (AMOCVD) for High-Temperature Superconductor (HTS) tape manufacturing developed at the University of Houston, Ohmic resistance heating is implemented to heat the rolling tape at a reference temperature. Control of the electric current through the tape is proposed to ensure substrate temperature uniformity that is essential for reducing nanoscale defect growth. The substrate temperature measurement is corrupted by the continuous deposition of precursor gas material on the crystal rods of the pyrometers in the reaction chamber challenging the real-time control process. The proposed approach for model-based substrate temperature control is based on the real-time estimation of the states of the substrate temperature model dynamics, and the sensor drift and drift rate, using an extended Kalman filter (EKF) combined with particle swarm optimization (PSO) to optimally tune the process and measurement noise covariance matrices. Experimental data from the AMOCVD facility are used to validate the model parameter and the sensor drift estimation process. The estimated temperature is used in a simulation study of a PSO-tuned LQR controller with adjustable gains designed to ensure uniform heating along the tape by controlling the electric current, and the results are compared with those of a PI controller. Precise temperature regulation in Ohmic heating is critical within a multitude of manufacturing and material processes, and the proposed methods constitute a systematic framework for model-based temperature estimation and control.