UNBIASED IDENTIFICATION OF CONTINUOUS-TIME PARAMETRIC MODELS USING A TIME-WEIGHTED INTEGRAL TRANSFORM

A time-weighted integral transform is presented to identify a continuous SISO or MIMO parametric model based on a single dynamic test under open-loop or closed-loop operation. Moving-horizon algorithms are proposed to obtain unbiased estimates of the model parameters. The off-line algorithm in a least-squares form and the on-line algorithm in a recursive form are provided. An effective technique based on pattern recognition is also developed to determine the system order and time delay from observed data in a simple manner. Furthermore, the proposed method can be easily applied as a model reduction technique that results in an ideal model with delay for any specified order.     

Closed-loop identification of wafer temperature dynamics in a rapid thermal process

Single wafer rapid thermal processing (RTP) can be used for various wafer fabrication steps such as annealing, oxidation and chemical vapor deposition. A key issue in RTP is accurate temperature control, i.e., the wafer temperatures should be rapidly increased while maintaining uniformity of the temperature profile. A closed-loop identification method that suppresses RTP drift effects and maintains a linear operating region during identification tests is proposed. A simple graphical identification method that can be implemented on a field controller for autotuning and a nonlinear least squares method have been investigated. Both methods are tested with RTP equipment based on a design developed by Texas Instruments.     

Fluidization of fine particles in a sound field and identification of group C/A particles using acoustic waves

Effects of sound field on the fluidization of fine particles have been comprehensively examined by using fine powders (4.8-65 μm average in size) including Al₂O₃, TiO₂, glass beads and FCC catalyst. It is found that the fluidization quality of fine particles can be enhanced with the assistance of a sound field, resulting in higher pressure drops and a lower u_mf. The effect of sound on the fluidization of fine particles is strongly dependent on the particle properties (Geldart type and particle size) as well as the parameters of the sound field such as sound pressure level (or intensity) and frequency. Given a fixed sound frequency, the effect becomes more significant at a higher sound pressure level. For the present sound-aided fluidized bed system, there is a resonant frequency at about 100-110 Hz, at which the effectiveness of the sound wave in improving fluidization of fine particles is most remarkable. In addition, based on the different attenuation features of sonic waves in the gas-solid suspension of group C and A particles, a novel acoustic method is explored to distinguish group C from group A particles.