Supported by the National Natural Science Foundation of China(61374044);Shanghai Science Technology Commission(15510722100,16111106300);Shanghai Municipal Education Commission(14ZZ088)
Considering the two-dimension(2 D) characteristic and the unknown optimal trajectory problem of the batch processes, an integrated model predictive control-iterative learning control(MPC-ILC) for batch processes is pr...
National Natural Science Foundation of China(No.61374044);Shanghai Science Technology Commission,China(Nos.15510722100,16111106300)
Special input signals identification method based on the auxiliary model based multi-innovation stochastic gradient algorithm for Hammerstein output-error system was proposed.The special input signals were used to rea...
National Natural Science Foundation of China(No.61374044);Shanghai Municipal Science and Technology Commission,China(No.15510722100);Shanghai Municipal Education Commission,China(No.14ZZ088);Shanghai Talent Development Plan,China;Shanghai Baoshan Science and Technology Commission,China(No.bkw2013120)
A new identification method of neuro-uzzy Hammerstein model based on probability density function(PDF) is presented,which is different from the idea that mean squared error(MSE) is employed as the index function in tr...
Supported by the National Natural Science Foundation of China(61374044);Shanghai Science Technology Commission(12510709400);Shanghai Municipal Education Commission(14ZZ088);Shanghai Talent Development Plan
This paper focuses on resolving the identification problem of a neuro-fuzzy model(NFM) applied in batch processes. A hybrid learning algorithm is introduced to identify the proposed NFM with the idea of auxiliary erro...