Title :
Fault-tolerant control for batch processes - Overview and outlook
Author :
Wang, Youqing ; Zhou, Donghua ; Gao, Furong
Author_Institution :
Dept. of Chem. Eng., Univ. of California, Santa Barbara, CA, USA
Abstract :
Most processes can be divided into two classes: batch processes and continuous processes. In general, batch processes, which run intermittently, are best suited to low-volume and high-value products. Due to the high value of products, much more requirements are proposed for the control performance of batch processes. Hence, the plants become more and more complicated to achieve the high requirements. Consequently, the process complication exposes the possibility of system faults. Therefore, there is a trade-off between high performance and reliability. Fault-tolerant control (FTC) should be a good choice to handle this trade-off. Unfortunately, the reported work on FTC for batch processes is scarce. Trying our best, only four papers in the subject area were found by the authors. Therefore, both great challenges and opportunities exist in this field. Compared to continuous processes, batch processes have mainly three features: repetitive nature, finite duration, and nonlinear property. Generally, faults can be divided into three classes based on their location; FTC methods include two classes according to whether fault detection and diagnosis (FDD) is used; in addition, the proposed scheme could be linear or nonlinear. By means of these criteria, the existing papers are categorized. Thanks to these categorizations, some promising directions will be presented in this paper.
Keywords :
batch processing (industrial); fault tolerance; process control; batch processes; continuous processes; fault detection; fault diagnosis; fault-tolerant control; Automatic control; Automation; Chemical engineering; Chemical processes; Chemical technology; Fault detection; Fault diagnosis; Fault tolerance; Manufacturing processes; Process control; Batch Process; Fault Detection and Diagnosis; Fault-Tolerant Control; Iterative Learning Control; Model Predictive Control;
Conference_Titel :
Control and Decision Conference, 2009. CCDC '09. Chinese
Conference_Location :
Guilin
Print_ISBN :
978-1-4244-2722-2
Electronic_ISBN :
978-1-4244-2723-9
DOI :
10.1109/CCDC.2009.5191906