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Peter C. Young
Person information
- affiliation: Lancaster University, UK
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2020 – today
- 2023
- [j36]Torben J. Andersen, Peter C. Young:
Enhancing public sector enterprise risk management through interactive information processing. Frontiers Res. Metrics Anal. 8 (2023) - [j35]Liuping Wang
, Chris T. Freeman
, Eric Rogers
, Peter C. Young
:
Disturbance Observer-Based Repetitive Control System With Nonminimal State-Space Realization and Experimental Evaluation. IEEE Trans. Control. Syst. Technol. 31(2): 961-968 (2023) - 2022
- [j34]Fengwei Chen, Peter C. Young:
A simple robust method of fractional time-delay estimation for linear dynamic systems. Autom. 137: 110117 (2022) - 2021
- [j33]Peter C. Young, Fengwei Chen:
Monitoring and forecasting the COVID-19 epidemic in the UK. Annu. Rev. Control. 51: 488-499 (2021) - 2020
- [j32]Peter C. Young, Alexandre Janot:
Efficient parameterisation of nonlinear system models: a comment on Nöel and Schoukens (2018). Int. J. Control 93(7): 1591-1595 (2020)
2010 – 2019
- 2018
- [j31]Mathieu Brunot, Alexandre Janot, Peter C. Young, Francisco Carrillo:
An instrumental variable method for robot identification based on time variable parameter estimation. Kybernetika 54(1): 202-220 (2018) - 2017
- [j30]Alexandre Janot, Peter C. Young, Hugues Garnier
, Françoise Lamnabhi-Lagarrigue:
Identification and control of nonlinear electro-mechanical systems. Int. J. Control 90(4): 641-642 (2017) - [j29]Alexandre Janot, Peter C. Young, Maxime Gautier:
Identification and control of electro-mechanical systems using state-dependent parameter estimation. Int. J. Control 90(4): 643-660 (2017) - 2016
- [c4]Arturo Andrés Padilla Bernedo, Hugues Garnier
, Peter C. Young, Juan I. Yuz:
Real-time identification of linear continuous-time systems with slowly time-varying parameters. CDC 2016: 3769-3774 - 2015
- [j28]Peter C. Young:
Refined instrumental variable estimation: Maximum likelihood optimization of a unified Box-Jenkins model. Autom. 52: 35-46 (2015) - 2014
- [j27]Hugues Garnier
, Peter C. Young:
Special issue on 'Applications of Continuous-Time Model Identification and Estimation'. Int. J. Control 87(7): 1317-1318 (2014) - [j26]Hugues Garnier
, Peter C. Young:
The advantages of directly identifying continuous-time transfer function models in practical applications. Int. J. Control 87(7): 1319-1338 (2014) - [j25]Peter C. Young:
Comment on 'Projection-based identification algorithm for grey-box continuous-time models' by Ichiro Maruta and Toshiharu Sugie. Syst. Control. Lett. 69: 62-64 (2014) - 2013
- [j24]Julien Schorsch, Hugues Garnier
, Marion Gilson
, Peter C. Young:
Instrumental variable methods for identifying partial differential equation models. Int. J. Control 86(12): 2325-2335 (2013) - 2012
- [j23]Andrea Castelletti
, Stefano Galelli
, Marco Ratto
, Rodolfo Soncini-Sessa, Peter C. Young:
A general framework for Dynamic Emulation Modelling in environmental problems. Environ. Model. Softw. 34: 5-18 (2012) - [j22]Wlodek Tych
, Peter C. Young:
A Matlab software framework for dynamic model emulation. Environ. Model. Softw. 34: 19-29 (2012) - 2011
- [j21]Peter C. Young, Marco Ratto
:
Statistical Emulation of Large Linear Dynamic Models. Technometrics 53(1): 29-43 (2011)
2000 – 2009
- 2009
- [j20]Andrew Jarvis
, David Leedal, C. James Taylor
, Peter C. Young:
Stabilizing global mean surface temperature: A feedback control perspective. Environ. Model. Softw. 24(5): 665-674 (2009) - [j19]C. James Taylor
, Arun Chotai, Peter C. Young:
Non-linear control by input-output state variable feedback pole assignment. Int. J. Control 82(6): 1029-1044 (2009) - [j18]Liuping Wang
, Peter C. Young, Peter J. Gawthrop, C. James Taylor
:
Non-minimal state-space model-based continuous-time model predictive control with constraints. Int. J. Control 82(6): 1122-1137 (2009) - [j17]Marco Ratto
, Andrea Pagano, Peter C. Young:
Non-parametric estimation of conditional moments for sensitivity analysis. Reliab. Eng. Syst. Saf. 94(2): 237-243 (2009) - 2008
- [j16]Diego J. Pedregal
, Peter C. Young:
Development of improved adaptive approaches to electricity demand forecasting. J. Oper. Res. Soc. 59(8): 1066-1076 (2008) - [c3]Vincent Laurain, Marion Gilson
, Hugues Garnier
, Peter C. Young:
Refined instrumental variable methods for identification of Hammerstein continuous-time Box-Jenkins models. CDC 2008: 1386-1391 - 2007
- [j15]Marco Ratto
, Andrea Pagano, Peter C. Young:
State Dependent Parameter metamodelling and sensitivity analysis. Comput. Phys. Commun. 177(11): 863-876 (2007) - [j14]Marcos Bujosa
, Antonio García-Ferrer
, Peter C. Young:
Linear dynamic harmonic regression. Comput. Stat. Data Anal. 52(2): 999-1024 (2007) - [j13]C. James Taylor
, Diego J. Pedregal
, Peter C. Young, Wlodek Tych
:
Environmental time series analysis and forecasting with the Captain toolbox. Environ. Model. Softw. 22(6): 797-814 (2007) - [j12]Nguyen-Vu Truong, Liuping Wang
, Peter C. Young:
Non-linear system modelling based on non-parametric identification and linear wavelet estimation of SDP models. Int. J. Control 80(5): 774-788 (2007) - [j11]Peter J. Gawthrop
, Liuping Wang
, Peter C. Young:
Continuous-time non-minimal state-space design. Int. J. Control 80(10): 1690-1697 (2007) - 2006
- [j10]Peter C. Young:
The data-based mechanistic approach to the modelling, forecasting and control of environmental systems. Annu. Rev. Control. 30(2): 169-182 (2006) - [j9]Renata J. Romanowicz, Peter C. Young, Patrick E. Brown
, Peter Diggle:
A recursive estimation approach to the spatio-temporal analysis and modelling of air quality data. Environ. Model. Softw. 21(6): 759-769 (2006) - [j8]Peter C. Young, Hugues Garnier
:
Identification and estimation of continuous-time, data-based mechanistic (DBM) models for environmental systems. Environ. Model. Softw. 21(8): 1055-1072 (2006) - [c2]Nguyen-Vu Truong, Liuping Wang, Peter C. Young:
Nonlinear System Modeling Based on Non-Parametric Identification and Linear Wavelet stimation of SDP Models. CDC 2006: 2523-2528 - 2004
- [j7]C. James Taylor
, Paul G. McKenna, Peter C. Young, Arun Chotai, Mike Mackinnon:
Macroscopic traffic flow modelling and ramp metering control using Matlab/Simulink. Environ. Model. Softw. 19(10): 975-988 (2004) - [c1]Hugues Garnier, Peter C. Young:
Time-domain approaches to continuous-time model identification of dynamical systems from sampled data. ACC 2004: 667-672 - 2003
- [j6]Renata J. Romanowicz, Peter C. Young:
Data assimilation and uncertainty analysis of environmental assessment problems - an application of Stochastic Transfer Function and Generalised Likelihood Uncertainty Estimation techniques. Reliab. Eng. Syst. Saf. 79(2): 161-174 (2003)
1990 – 1999
- 1996
- [j5]Peter C. Young, Wlodek Tych
:
Operational control of water systems: Structures, algorithms and applications : By M. A. Brdys and B. Ulanicki. Autom. 32(11): 1619-1620 (1996)
1980 – 1989
- 1980
- [j4]Peter C. Young, Anthony J. Jakeman
, Ross McMurtrie:
An instrumental variable method for model order identification. Autom. 16(3): 281-294 (1980) - [j3]Anthony J. Jakeman
, L. Paul Steele, Peter C. Young:
Instrumental Variable Algorithms for Multiple Input Systems Described by Multiple Transfer Functions. IEEE Trans. Syst. Man Cybern. 10(10): 593-602 (1980)
1970 – 1979
- 1973
- [j2]Josef Kittler, Peter C. Young:
A new approach to feature selection based on the Karhunen-Loeve expansion. Pattern Recognit. 5(4): 335-352 (1973) - 1970
- [j1]Peter C. Young:
R70-8 Analog Methods for On-Line System Identification Using Noisy Measurements. IEEE Trans. Computers 19(5): 465-466 (1970)
1960 – 1969
- 1969
- [b1]Peter C. Young:
The differential equation-error method of real-time process identification. University of Cambridge, UK, 1969
Coauthor Index
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