Publication

Peer-reviewed Journal Publication

(Corresponding authorship is denoted by ^* )

Jiang, Q., Fu, X., Yan, S., Li, R., Du, W., Cao, Z.^*, Qian, F., Grima, R. (2021) Neural network aided approximation and parameter inference of non-Markovian models of gene expression (Accepted by Nature Communications). (Codes)

Lu, J., Cao, Z.^*, Hu, Q., Xu, Z., Gao, F. (2020). Optimal iterative learning control for batch processes in the presence of time-varying dynamics (Accepted).
Cao, Z., Filatova, T., Oyarzun, D., Grima, R. (2020). A stochastic model of gene expression with polymerase recruitment and pause release. Biophysical Journal, 119(5), 1002-1014.
Cao, Z.^*, Yu, J., Wang W., Lu H., Xia X., Xu H., Yang X., Bao L., Zhang Q., Wang H., Zhang S., Zhang L. (2020). Multi-scale data-driven engineering for biosynthetic titer improvement. Current Opinion in Biotechnology, 65, 205-212.
Holehouse J., Cao, Z., Grima, R. (2020). Stochastic feedback loops in gene regulatory networks. Biophysical Journal, 118, 1517-1525.
Cao, Z., Grima, R. (2020). Analytical distributions for detailed models of stochastic gene expression in eukaryotic cells. Proceedings of the National Academy of Science of the United States of America, 117(9), 4682-4692.

Lu, J., Cao, Z.^*, Zhao, C., Gao, F. (2019). 110th Anniversary: an overview on learning-based model predictive control for batch processes. Industrial & Engineering Chemistry Research, 58(37), 17164-17173.
Lu, J., Cao, Z.^*, Gao, F. (2019). Multi-point iterative learning model predictive control. IEEE Transactions on Industrial Electronics, 66(8), 6230-6240.
Cao, Z., Grima, R. (2019). Accuracy of parameter estimation for auto-regulatory transcriptional feedback loops from noisy data. Journal of the Royal Society Interface, 16(153), 20180967.

Cao, Z., Grima, R. (2018). Linear mapping approximation of gene regulatory networks with stochastic dynamics. Nature communications, 9(1), 3305. (IF 12.353) (Codes)
Lu, J., Cao, Z.^*, Zhang, R., Gao, F. (2017). Nonlinear monotonically convergent iterative learning control for batch processes. IEEE Transactions on Industrial Electronics, 65(7), 5826-5836.
Cao, Z., Gondhalekar, R., Dassau, E., Doyle, F. J. (2017). Extremum seeking control for personalized zone adaptation in model predictive control for type 1 diabetes. IEEE Transactions on Biomedical Engineering, 65(8), 1859-1870.
Cao, Z., Lu, J., Zhang, R., Gao, F. (2018). Online average-based system modelling method for batch process. Computers & Chemical Engineering, 108, 128-138.
Zhang, R., Wu, S., Cao, Z., Lu, J., Gao, F. (2018). A systematic min–max optimization design of constrained model predictive tracking control for industrial processes against uncertainty. IEEE Transactions on Control Systems Technology, 26(6), 2157-2164.

Cao, Z., Dürr, H. B., Ebenbauer, C., Allgöwer, F., Gao, F. (2017). Iterative learning and extremum seeking for repetitive time-varying mappings. IEEE Transactions on Automatic Control, 62(7), 3339-3353.
Lu, J., Cao, Z., Gao, F. (2017). Batch process control-overview and outlook. Acta Automatica Sinica, 43(6), 933-943.
Zhang, R., Zou, Q., Cao, Z., Gao, F. (2017). Design of fractional order modeling based extended non-minimal state space MPC for temperature in an industrial electric heating furnace. Journal of Process Control, 56, 13-22.

Cao, Z., Lu, J., Zhang, R., Gao, F. (2016). Iterative learning Kalman filter for repetitive processes. Journal of Process Control, 46, 92-104.
Cao, Z., Yang, Y., Yi, H., Gao, F. (2016). Priori knowledge-based online batch-to-batch identification in a closed loop and an application to injection molding. Industrial & Engineering Chemistry Research, 55(32), 8818-8829.
Cao, Z., Zhang, R., Lu, J., Gao, F. (2016). Online identification for batch processes in closed loop incorporating priori controller knowledge. Computers & Chemical Engineering, 90, 222-233.
Cao, Z., Zhang, R., Lu, J., Gao, F. (2016). Two-time dimensional recursive system identification incorporating priori pole and zero knowledge. Journal of Process Control, 39, 100-110.
Cao, Z., Zhang, R., Yang, Y., Lu, J., Gao, F. (2016). Discrete-time robust iterative learning Kalman filtering for repetitive processes. IEEE Transactions on Automatic Control, 61(1), 270-275.
Lu, J., Cao, Z., Gao, F. (2016). Ellipsoid invariant set-based robust model predictive control for repetitive processes with constraints. IET Control Theory & Applications, 10(9), 1018-1026.

Cao, Z., Yang, Y., Lu, J., Gao, F. (2015). Two-time-dimensional model predictive control of weld line positioning in bi-injection molding. Industrial & Engineering Chemistry Research, 54(17), 4795-4804.
Zhang, R., Cao, Z., Lu, R., Li, P., Gao, F. (2015). State-space predictive-p control for liquid level in an industrial coke fractionation tower. IEEE Transactions on Automation Science and Engineering, 12(4), 1516-1524.
Lu, J., Cao, Z., Wang, Z., & Gao, F. (2015). A two-stage design of two-dimensional model predictive iterative learning control for nonrepetitive disturbance attenuation. Industrial & Engineering Chemistry Research, 54(21), 5683-5689.

Cao, Z., Yang, Y., Lu, J., Gao, F. (2014). Constrained two dimensional recursive least squares model identification for batch processes. Journal of Process Control, 24(6), 871-879.
Zhang, R., Cao, Z., Bo, C., Li, P., Gao, F. (2014). New PID controller design using extended nonminimal state space model based predictive functional control structure. Industrial & Engineering Chemistry Research, 53(8), 3283-3292.
Zhang, R., Cao, Z., Li, P., Gao, F. (2014). Design and implementation of an improved linear quadratic regulation control for oxygen content in a coke furnace. IET Control Theory & Applications, 8(14), 1303-1311.