Supported by National Natural Science Foundation of China(F010114-6097414061273135)
In this paper,a reinforced gradient-type iterative learning control pro file is proposed by making use of system matrices and a proper learning step to improve the tracking performance of batch processes disturbed by ...
Supported in part by the State Key Development Program for Basic Research of China(2012CB720505);the National Natural Science Foundation of China(61174105,60874049)
Based on the two-dimensional (2D) system theory, an integrated predictive iterative learning control (2D-IPILC) strategy for batch processes is presented. First, the output response and the error transition model ...
Supported in part by NSFC/RGC joint Research Scheme (N-HKUST639/09), the National Natural Science Foundation of China (61104058, 61273101), Guangzhou Scientific and Technological Project (2012J5100032), Nansha district independent innovation project (201103003), China Postdoctoral Science Foundation (2012M511367, 2012M511368), and Doctor Scientific Research Foundation of Liaoning Province (20121046).
Based on an equivalent two-dimensional Fornasini-Marchsini model for a batch process in industry, a closed-loop robust iterative learning fault-tolerant guaranteed cost control scheme is proposed for batch processes w...
Supported by the National Natural Science Foundation of China (60974040, 61120106009), the Research Award Foundation for the Excellent Youth Scientists of Shandong Province of China (BS2011DX010), and the High School Science & Technol- ogy Fund Planning Project of Shandong Province of China (J 10LG32).
This work presents an anticipatory terminal iterative learning control scheme for a class of batch proc- esses, where only the final system output is measurable and the control input is constant in each operations. Th...
Supported by the National Natural Science Foundation of China (60404012, 60674064), UK EPSRC (GR/N13319 and GR/R10875), the National High Technology Research and Development Program of China (2007AA04Z193), New Star of Science and Technology of Beijing City (2006A62), and IBM China Research Lab 2007 UR-Program.
A batch-to-batch optimal iterative learning control (ILC) strategy for the tracking control of product quality in batch processes is presented. The linear time-varying perturbation (LTVP) model is built for produc...