Следене
Zhixing Cao
Zhixing Cao
Queen's University
Потвърден имейл адрес: g.harvard.edu - Начална страница
Заглавие
Позовавания
Позовавания
Година
Linear mapping approximation of gene regulatory networks with stochastic dynamics
Z Cao, R Grima
Nature Communications 9, 2018
1392018
Analytical distributions for detailed models of stochastic gene expression in eukaryotic cells
Z Cao, R Grima
Proceedings of the National Academy of Sciences 117 (9), 4682-4692, 2020
1322020
Neural network aided approximation and parameter inference of non-Markovian models of gene expression
Q Jiang, X Fu, S Yan, R Li, W Du, Z Cao, F Qian, R Grima
Nature communications 12 (1), 2618, 2021
1132021
Nonlinear Monotonically Convergent Iterative Learning Control for Batch Processes
J Lu, Z Cao, R Zhang, F Gao
IEEE Transactions on Industrial Electronics 65 (7), 5826 - 5836, 2017
832017
Multipoint iterative learning model predictive control
J Lu, Z Cao, F Gao
IEEE Transactions on Industrial Electronics 66 (8), 6230-6240, 2018
582018
A Systematic Min-Max Optimization Design of Constrained Model Predictive Tracking Control for Industrial Processes against Uncertainty
R Zhang, S Wu, Z Cao, J Lu, F Gao
IEEE Transactions on Control Systems Technology, 2017
542017
Design of fractional order modeling based extended non-minimal state space MPC for temperature in an industrial electric heating furnace
R Zhang, Q Zou, Z Cao, F Gao
Journal of Process Control 56, 13-22, 2017
472017
A stochastic model of gene expression with polymerase recruitment and pause release
Z Cao, T Filatova, DA Oyarzún, R Grima
Biophysical Journal 119 (5), 1002-1014, 2020
40*2020
Constrained two dimensional recursive least squares model identification for batch processes
Z Cao, Y Yang, J Lu, F Gao
Journal of Process Control 24 (6), 871-879, 2014
382014
110th Anniversary: An Overview on Learning-Based Model Predictive Control for Batch Processes
J Lu, Z Cao, C Zhao, F Gao
Industrial & Engineering Chemistry Research 58 (37), 17164-17173, 2019
372019
Accuracy of parameter estimation for auto-regulatory transcriptional feedback loops from noisy data
Z Cao, R Grima
Journal of The Royal Society Interface 16 (153), 20180967, 2019
372019
Iterative learning Kalman filter for repetitive processes
Z Cao, J Lu, R Zhang, F Gao
Journal of Process Control 46, 92-104, 2016
342016
Discrete-time robust iterative learning Kalman filtering for repetitive processes
Z Cao, R Zhang, Y Yang, J Lu, F Gao
IEEE Transactions on Automatic Control 61 (1), 270-275, 2015
332015
New PID controller design using extended nonminimal state space model based predictive functional control structure
R Zhang, Z Cao, C Bo, P Li, F Gao
Industrial & Engineering Chemistry Research 53 (8), 3283-3292, 2014
332014
Stochastic modeling of autoregulatory genetic feedback loops: A review and comparative study
J Holehouse, Z Cao, R Grima
Biophysical Journal 118 (7), 1517-1525, 2020
302020
Extremum seeking control for personalized zone adaptation in model predictive control for type 1 diabetes
Z Cao, R Gondhalekar, E Dassau, FJ Doyle
IEEE Transactions on Biomedical Engineering 65 (8), 1859-1870, 2017
302017
A two-stage design of two-dimensional model predictive iterative learning control for nonrepetitive disturbance attenuation
J Lu, Z Cao, Z Wang, F Gao
Industrial & Engineering Chemistry Research 54 (21), 5683-5689, 2015
302015
Quantifying how post-transcriptional noise and gene copy number variation bias transcriptional parameter inference from mRNA distributions
X Fu, HP Patel, S Coppola, L Xu, Z Cao, TL Lenstra, R Grima
Elife 11, e82493, 2022
282022
Iterative learning and extremum seeking for repetitive time-varying mappings
Z Cao, HB Dürr, C Ebenbauer, F Allgöwer, F Gao
IEEE Transactions on Automatic Control 62 (7), 3339-3353, 2016
272016
Batch process control-overview and outlook
J Lu, Z Cao, F Gao
Acta Automatica Sinica 43 (6), 933-943, 2017
242017
Системата не може да изпълни операцията сега. Опитайте отново по-късно.
Статии 1–20