Cited by 13Control Systems and IdentificationAdvanced Control Systems DesignFault Detection and Control Systems

The DOI matches its Crossref record; 62 of the 62 references it cites were found in a registry or an index.

Data-driven approach for time-delay estimation of industrial processes

Ma, Xin-Yue, Huang, Chun-Qing·2023·ISA Transactions

DOI 10.1016/j.isatra.2023.01.028

Open this paper in CoChat — free account

Abstract

An accurate estimate of time delay is of crucial importance for control tasks such as performance assessment and controller design. In this paper, a novel data-driven approach to time-delay estimation is developed for a process subject to industrial background disturbances, in which the closed-loop output data under the routine operating conditions is only required. The practical solutions are proposed to estimate the time delay based on the estimated impulse response of the closed loop that is estimated online by utilizing the output data. Without relying on system identification and any prior knowledge of the process as well, the time delay is estimated directly for a large time delayed process; while for a small time delayed process, the time delay is estimated by means of the stationarilized filter, the pre-filter and the loop filter. The effectiveness of the proposed approach is validated by various numerical and industrial examples including a distillation column, a petroleum refinery heating furnace and a ceramic dryer.

Integrity signals

Registry

Crossref · 10.1016/j.isatra.2023.01.028

Cites

62 of 62 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

System identification—Theory for the user
Sinha, N. K. (1989) · Automatica · doi:10.1016/0005-1098(89)90019-8 · Cited by 9,310
Stability of Time-Delay Systems
Gu, K., Kharitonov, V. L., & Chen, J. (2003) · Birkhäuser Boston eBooks · doi:10.1007/978-1-4612-0039-0 · Cited by 5,628
The generalized correlation method for estimation of time delay
Knapp, C., & Carter, G. (1976) · IEEE Transactions on Acoustics, Speech, and Signal Processing · doi:10.1109/tassp.1976.1162830 · Cited by 4,433
Time-delay systems: an overview of some recent advances and open problems
Richard, J.-P. (2003) · Automatica · doi:10.1016/s0005-1098(03)00167-5 · Cited by 3,353
Process dynamics and control
(1990) · Choice Reviews Online · doi:10.5860/choice.27-3903 · Cited by 831
Control of Dead-time Processes
Normey‐Rico, J. E., & Camacho, E. F. (2007) · Springer eBooks · doi:10.1007/978-1-84628-829-6 · Cited by 596
An overview of control performance assessment technology and industrial applications
Jelali, M. (2006) · Control Engineering Practice · doi:10.1016/j.conengprac.2005.11.005 · Cited by 503
Multivariable System Identification For Process Control
Zhu, Y. (2001) · Elsevier eBooks · doi:10.1016/b978-0-08-043985-3.x5000-5 · Cited by 463
Discrete time techniques for time delay estimation
Jacovitti, G., & Scarano, G. (1993) · IEEE Transactions on Signal Processing · doi:10.1109/78.193195 · Cited by 433
Autotuning of PID controllers: relay feedback approach
Becerra, V. M. (2000) · Automatica · doi:10.1016/s0005-1098(00)00096-0 · Cited by 250
A tutorial review on process identification from step or relay feedback test
Liu, T., Wang, Q., & Huang, H. (2013) · Journal of Process Control · doi:10.1016/j.jprocont.2013.08.003 · Cited by 222
Robust identification of continuous systems with dead-time from step responses
Wang, Q.-G., & Zhang, Y. (2001) · Automatica · doi:10.1016/s0005-1098(00)00177-1 · Cited by 164
The current state of control loop performance monitoring – A survey of application in industry
Bauer, M., Horch, A., Xie, L., Jelali, M., & Thornhill, N. F. (2015) · Journal of Process Control · doi:10.1016/j.jprocont.2015.11.002 · Cited by 154
A Survey and Comparison of Time-Delay Estimation Methods in Linear Systems
Björklund, S. (2003) · Cited by 142
Analysis of detrended time-lagged cross-correlation between two nonstationary time series
Shen, C. (2014) · Physics Letters A · doi:10.1016/j.physleta.2014.12.036 · Cited by 137
Improved correlation analysis and visualization of industrial alarm data
Yang, F., Shah, S. L., Xiao, D., & Chen, T. (2012) · ISA Transactions · doi:10.1016/j.isatra.2012.03.005 · Cited by 135
Nonlinear system identification for predictive control using continuous time recurrent neural networks and automatic differentiation
Al-Seyab, R., & Cao, Y. (2008) · Journal of Process Control · doi:10.1016/j.jprocont.2007.10.012 · Cited by 122
Online identification of continuous-time systems with unknown time delay
Ren, X. M., Rad, A. B., Chan, P. T., & Lo, W. L. (2005) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2005.854640 · Cited by 122
Relay Feedback: Analysis, Identification and Control
Wang, Q., Lee, T. H., & Lin, C. (2002) · Cited by 113
Robust tuning procedures of dead-time compensating controllers
Ingimundarson, A., & Hägglund, T. J. (2001) · Control Engineering Practice · doi:10.1016/s0967-0661(01)00065-x · Cited by 101
Parameter estimation for time-delay chaotic system by particle swarm optimization
Tang, Y., & Guan, X. (2007) · Chaos Solitons & Fractals · doi:10.1016/j.chaos.2007.09.055 · Cited by 97
Constrained multisine input signals for plant-friendly identification of chemical process systems
Rivera, D. E., Lee, H., Mittelmann, H. D., & Braun, M. (2008) · Journal of Process Control · doi:10.1016/j.jprocont.2008.08.006 · Cited by 97
Controlling industrial dead-time systems: When to use a PID or an advanced controller
da Silva, L. R., Flesch, R. C. C., & Normey‐Rico, J. E. (2019) · ISA Transactions · doi:10.1016/j.isatra.2019.09.008 · Cited by 96
Industrial Process Identification and Control Design: Step-test and Relay-experiment-based Methods
Liu, T., & Gao, F. (2011) · Cited by 77
Duality Between the Control of Processes Subject to Randomly Occurring Deterministic Disturbances and ARIMA Stochastic Disturbances
MacGregor, J. F., Harris, T. J., & Wright, J. D. (1984) · Technometrics · doi:10.1080/00401706.1984.10487992 · Cited by 73
Design of sliding mode control for quadruple-tank MIMO process with time delay compensation
Shah, D. H., & Patel, D. M. (2019) · Journal of Process Control · doi:10.1016/j.jprocont.2019.01.006 · Cited by 72
Robust identification of continuous-time models with arbitrary time-delay from irregularly sampled data
Chen, F., Garnier, H., & Gilson, M. (2015) · Journal of Process Control · doi:10.1016/j.jprocont.2014.10.003 · Cited by 68
Enhanced tuning of Smith predictor based series cascaded control structure for integrating processes
Raja, G. L., & Ali, A. (2020) · ISA Transactions · doi:10.1016/j.isatra.2020.12.045 · Cited by 68
Parameter estimation for nonlinear time-delay systems with noisy output measurements
Lin, Q., Loxton, R., Xu, C., & Teo, K. L. (2015) · Automatica · doi:10.1016/j.automatica.2015.06.028 · Cited by 67
09 2010 1985 1986 5565453 10.1109/TAC.2010.2069451 http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5565453 <![CDATA[An Optimization Approach to State-Delay Identification $ $
Loxton, R., Teo, K. L., & Rehbock, V. (2010) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2010.2050710 · Cited by 64
Achievable PID performance using sums of squares programming
Sendjaja, A. Y., & Kariwala, V. (2009) · Journal of Process Control · doi:10.1016/j.jprocont.2008.12.005 · Cited by 64
Case studies on closed-loop identification for MPC
Zhu, Y., & Butoyi, F. (2002) · Control Engineering Practice · doi:10.1016/s0967-0661(02)00007-2 · Cited by 59
Simple internal model control based modified Smith predictor for integrating time delayed processes with real-time verification
Karan, S., Dey, C., & Mukherjee, S. (2021) · ISA Transactions · doi:10.1016/j.isatra.2021.04.008 · Cited by 59
Identification of continuous-time systems with multiple unknown time delays by global nonlinear least-squares and instrumental variable methods
Yang, Z., Iemura, H., Kanae, S., & Wada, K. (2007) · Automatica · doi:10.1016/j.automatica.2006.12.026 · Cited by 56
Time delay estimation for MIMO dynamical systems – With time-frequency domain analysis
Ni, B., Xiao, D., & Shah, S. L. (2009) · Journal of Process Control · doi:10.1016/j.jprocont.2009.10.002 · Cited by 54
Identification of discrete-time output error model for industrial processes with time delay subject to load disturbance
Dong, S., Liu, T., Wang, W., Bao, J., & Cao, Y. (2016) · Journal of Process Control · doi:10.1016/j.jprocont.2016.11.007 · Cited by 51
Multivariate statistical methods for control loop performance assessment
Huang, B. (1997) · Library and Archives Canada (Government of Canada) · doi:10.7939/r39k45z71 · Cited by 50
Simultaneous online identification of rational dynamics and time delay: a correlation-based approach
Rad, A. B., Lo, W. L., & Tsang, K. M. (2003) · IEEE Transactions on Control Systems Technology · doi:10.1109/tcst.2003.819594 · Cited by 49
Cross-correlation analysis and time delay estimation of a homologous micro-seismic signal based on the Hilbert–Huang transform
Sun, H.-M., Jia, R., Du, Q.-Q., & Fu, Y. (2016) · Computers & Geosciences · doi:10.1016/j.cageo.2016.03.012 · Cited by 45
Time-delay identification in dynamic processes with disturbance via correlation analysis
Li, L., Dong, T., Zhang, S., Zhang, X., & Yang, S.-P. (2017) · Control Engineering Practice · doi:10.1016/j.conengprac.2017.03.007 · Cited by 45
Control of the temperature in a petroleum refinery heating furnace based on a robust modified Smith predictor
Feliú, V., & Rivas‐Perez, R. (2020) · ISA Transactions · doi:10.1016/j.isatra.2020.12.006 · Cited by 44
A generalized relay identification method for time delay and non-minimum phase processes
Liu, T., & Gao, F. (2009) · Automatica · doi:10.1016/j.automatica.2008.11.024 · Cited by 43
Identification and predictive control of a multistage evaporator
Atuonwu, J. C., Cao, Y., Rangaiah, G. P., & Tadé, M. O. (2010) · Control Engineering Practice · doi:10.1016/j.conengprac.2010.08.002 · Cited by 35
On the identifiability of the time delay with least-squares methods
Ferretti, G., Maffezzoni, C., & Scattolini, R. (1996) · Automatica · doi:10.1016/0005-1098(95)00172-7 · Cited by 33
Predictor–observer-based control of systems with multiple input/output delays
Albertos, P., & García, P. (2012) · Journal of Process Control · doi:10.1016/j.jprocont.2012.06.006 · Cited by 32
Linear and nonlinear hierarchical multivariate time delay analytics for dynamic modeling and process monitoring
Chen, X., & Zhao, C. (2021) · Journal of Process Control · doi:10.1016/j.jprocont.2021.10.008 · Cited by 31
Load balancing control of furnace with multiple parallel passes
Wang, X., & Zheng, D.-Z. (2006) · Control Engineering Practice · doi:10.1016/j.conengprac.2006.10.002 · Cited by 28
Robust filtered Smith predictor for processes with time-varying delay: A simplified stability approach
Franklin, T. S., & Santos, T. L. M. (2020) · European Journal of Control · doi:10.1016/j.ejcon.2020.01.005 · Cited by 28
A variable time delay compensator for multivariable linear processes
Saffer, D. R., Castro, J. J., & Doyle, F. J. (2005) · Journal of Process Control · doi:10.1016/j.jprocont.2004.05.005 · Cited by 26
Issues in separable identification of continuous-time models with time-delay
Chen, F., Zhuan, X., Garnier, H., & Gilson, M. (2018) · Automatica · doi:10.1016/j.automatica.2018.04.014 · Cited by 26
PID control performance assessment using iterative convex programming
Fu, R., Xie, L., Song, Z., & Cheng, Y. (2012) · Journal of Process Control · doi:10.1016/j.jprocont.2012.07.015 · Cited by 25
A dynamic time delay analysis approach for correlated process variables
Yang, B., Li, H., & Wen, B. (2017) · Process Safety and Environmental Protection · doi:10.1016/j.cherd.2017.04.010 · Cited by 24
Assessment minimum output variance with PID controllers
Shahni, F., & Malwatkar, G. M. (2011) · Journal of Process Control · doi:10.1016/j.jprocont.2011.01.003 · Cited by 19
Variable regression estimation of unknown system delay
Elnaggar, A. Y. (2011) · cIRcle (University of British Columbia) · doi:10.14288/1.0065633 · Cited by 14
A Comparison of Some Approaches to Time-Delay Estimation
Isaksson, M. (1997) · Lund University Publications Student Papers (Lund University) · Cited by 13
Optimum time delay estimation for complex-valued stationary signals
Cao, H., So, H. C., & Chan, Y. T. (2016) · Signal Processing · doi:10.1016/j.sigpro.2016.09.005 · Cited by 13
Recursive parameter estimation of exhaust gas oxygen sensors with input-dependent time delay and linear parameters
Moser, M. M., Onder, C. H., & Guzzella, L. (2015) · Control Engineering Practice · doi:10.1016/j.conengprac.2015.03.009 · Cited by 12
Algorithms for time delay estimation using a low complexity exhaustive search
Carlemalm, C., Halvarsson, S., Wigren, T., & Wahlberg, B. (1999) · IEEE Transactions on Automatic Control · doi:10.1109/9.763223 · Cited by 12
Automated synthesis of multivariate QFT controller and pre-filter for a distillation column with multiple time delays
Katal, N., & Narayan, S. (2021) · Journal of Process Control · doi:10.1016/j.jprocont.2020.12.004 · Cited by 12
Performance assessment of multivariate process using time delay matrix
Huang, C., Chen-Bing, Z., Yang, F., & Su, C. (2020) · Journal of Process Control · doi:10.1016/j.jprocont.2020.10.002 · Cited by 9
Self-citation
ARMAX Time Delay Systems Identification Based on Least Square Approach
Bedoui, S., & Abderrahim, K. (2015) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2015.12.278 · Cited by 8
Conversion of SISO processes with multiple time-delays to single time-delay processes
Luan, X., Chen, Q., Albertos, P., & Liu, F. (2017) · Journal of Process Control · doi:10.1016/j.jprocont.2017.10.001 · Cited by 8

Sorted by citations

A Novel Predefined-Performance Control for Uncertain Nonholonomic Mobile Manipulator
Yang, Y., Yan, Y., Hua, C., & Li, J. (2024) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2023.3345463 · Cited by 14
Multiple Correlation Analysis for Finite-Time Delay Estimation for Soft Sensor Design in the Presence of Noise
Graziani, S., & Xibilia, M. G. (2023) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2023.3307748 · Cited by 10
A novel class of non-Gaussian system performance assessment and controller parameter tuning methods
Yi, M., Zhou, J., Lei, F., Li, D., & Liu, R. (2024) · ISA Transactions · doi:10.1016/j.isatra.2024.08.031 · Cited by 5
Identification of finite-time delay and regressors for the design of soft sensors in the presence of input collinearity
Patané, L., Graziani, S., & Xibilia, M. G. (2025) · Control Engineering Practice · doi:10.1016/j.conengprac.2025.106267 · Cited by 5
Subspace identification of dynamic processes with consideration of time delays: A Bayesian optimization scheme
Liu, Q., Liu, T., Huang, D., & Shang, C. (2025) · Journal of Process Control · doi:10.1016/j.jprocont.2025.103387 · Cited by 5

See all 13

Authors: Ma, X.-Y., & Huang, C.-Q.
ORCID: Huang, Chun-Qing
Venue: ISA Transactions
Publisher: Elsevier BV
Published: 2023-06
Volume: 137
Pages: 35-58
ISSN: 0019-0578 (ISSN-L)
DOI: 10.1016/j.isatra.2023.01.028
OpenAlex: W4317929778
Cited by: 13
References: 62
Citations by year: 2026: 2 · 2025: 4 · 2024: 5 · 2023: 2
FWCI: 1.14
Type: journal article
Language: en
Open access: closed
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/legal/tdmrep-license (tdm)
Locations: ISA Transactions (publishedVersion)
PubMed (publishedVersion)
Funders: National Natural Science Foundation of China (62273285)
Topics: Physical Sciences › Engineering › Control and Systems Engineering › Control Systems and Identification
Physical Sciences › Engineering › Control and Systems Engineering › Advanced Control Systems Design
Physical Sciences › Engineering › Control and Systems Engineering › Fault Detection and Control Systems
Keywords: time delay estimation, data-driven estimation, industrial processes, impulse response estimation, online estimation, prefilter, loop filter, distillation column, heating furnace

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data-driven approach for time-delay estimation of industrial processes

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Citations

Cites

Cited by

Related

Metadata

Record

About these checks