Peter C. Young - researchr alias

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Viewing Publication 1 - 36 from 36

2023

Disturbance Observer-Based Repetitive Control System With Nonminimal State-Space Realization and Experimental EvaluationLiuping Wang, Chris T. Freeman, Eric Rogers, Peter C. Young. tcst, 31(2):961-968, March 2023. [doi]

2022

A simple robust method of fractional time-delay estimation for linear dynamic systemsFengwei Chen, Peter C. Young. automatica, 137:110117, 2022. [doi]

2021

Monitoring and forecasting the COVID-19 epidemic in the UKPeter C. Young, Fengwei Chen. arc, 51:488-499, 2021. [doi]

2020

Efficient parameterisation of nonlinear system models: a comment on Nöel and Schoukens (2018)Peter C. Young, Alexandre Janot. ijcon, 93(7):1591-1595, 2020. [doi]

2018

An instrumental variable method for robot identification based on time variable parameter estimationMathieu Brunot, Alexandre Janot, Peter C. Young, Francisco Carrillo. kybernetika, 54(1):202-220, 2018. [doi]

2017

Identification and control of electro-mechanical systems using state-dependent parameter estimationAlexandre Janot, Peter C. Young, Maxime Gautier. ijcon, 90(4):643-660, 2017. [doi]

Identification and control of nonlinear electro-mechanical systemsAlexandre Janot, Peter C. Young, Hugues Garnier, Françoise Lamnabhi-Lagarrigue. ijcon, 90(4):641-642, 2017. [doi]

2016

Real-time identification of linear continuous-time systems with slowly time-varying parametersA. Padilla, Hugues Garnier, Peter C. Young, J. Yuz. cdc 2016: 3769-3774 [doi]

2015

Refined instrumental variable estimation: Maximum likelihood optimization of a unified Box-Jenkins modelPeter C. Young. automatica, 52:35-46, 2015. [doi]

2014

Special issue on 'Applications of Continuous-Time Model Identification and Estimation'Hugues Garnier, Peter C. Young. ijcon, 87(7):1317-1318, 2014. [doi]

The advantages of directly identifying continuous-time transfer function models in practical applicationsHugues Garnier, Peter C. Young. ijcon, 87(7):1319-1338, 2014. [doi]

Comment on 'Projection-based identification algorithm for grey-box continuous-time models' by Ichiro Maruta and Toshiharu SugiePeter C. Young. scl, 69:62-64, 2014. [doi]

2013

Instrumental variable methods for identifying partial differential equation modelsJulien Schorsch, Hugues Garnier, Marion Gilson, Peter C. Young. ijcon, 86(12):2325-2335, 2013. [doi]

2012

A general framework for Dynamic Emulation Modelling in environmental problemsAndrea Castelletti, Stefano Galelli, Marco Ratto, Rodolfo Soncini-Sessa, Peter C. Young. envsoft, 34:5-18, 2012. [doi]

A Matlab software framework for dynamic model emulationWlodek Tych, Peter C. Young. envsoft, 34:19-29, 2012. [doi]

2011

Statistical Emulation of Large Linear Dynamic ModelsPeter C. Young, Marco Ratto. technometrics, 53(1):29-43, 2011. [doi]

2009

2008

Refined instrumental variable methods for identification of Hammerstein continuous-time Box-Jenkins modelsVincent Laurain, Marion Gilson, Hugues Garnier, Peter C. Young. cdc 2008: 1386-1391 [doi]

2007

Linear dynamic harmonic regressionMarcos Bujosa, Antonio García-Ferrer, Peter C. Young. csda, 52(2):999-1024, 2007. [doi]

Continuous-time non-minimal state-space designPeter J. Gawthrop, Liuping Wang, Peter C. Young. ijcon, 80(10):1690-1697, 2007. [doi]

Environmental time series analysis and forecasting with the Captain toolboxC. James Taylor, Diego J. Pedregal, Peter C. Young, Wlodek Tych. envsoft, 22(6):797-814, 2007. [doi]

Non-linear system modelling based on non-parametric identification and linear wavelet estimation of SDP modelsNguyen-Vu Truong, Liuping Wang, Peter C. Young. ijcon, 80(5):774-788, 2007. [doi]

2006

Nonlinear System Modeling Based on Non-Parametric Identification and Linear Wavelet stimation of SDP ModelsNguyen-Vu Truong, Liuping Wang, Peter C. Young. cdc 2006: 2523-2528 [doi]

The data-based mechanistic approach to the modelling, forecasting and control of environmental systemsPeter C. Young. arc, 30(2):169-182, 2006. [doi]

Identification and estimation of continuous-time, data-based mechanistic (DBM) models for environmental systemsPeter C. Young, Hugues Garnier. envsoft, 21(8):1055-1072, 2006. [doi]

2004

Time-domain approaches to continuous-time model identification of dynamical systems from sampled dataHugues Garnier, Peter C. Young. amcc 2004: 667-672 [doi]

Macroscopic traffic flow modelling and ramp metering control using Matlab/SimulinkC. James Taylor, Paul G. McKenna, Peter C. Young, Arun Chotai, Mike Mackinnon. envsoft, 19(10):975-988, 2004. [doi]

2003

Data assimilation and uncertainty analysis of environmental assessment problems - an application of Stochastic Transfer Function and Generalised Likelihood Uncertainty Estimation techniquesRenata J. Romanowicz, Peter C. Young. ress, 79(2):161-174, 2003. [doi]

1980

Instrumental Variable Algorithms for Multiple Input Systems Described by Multiple Transfer FunctionsAnthony J. Jakeman, L. Paul Steele, Peter C. Young. tsmc, 10(10):593-602, 1980. [doi]

An instrumental variable method for model order identificationPeter C. Young, Anthony J. Jakeman, Ross McMurtrie. automatica, 16(3):281-294, 1980. [doi]

1973

A new approach to feature selection based on the Karhunen-Loeve expansionJosef Kittler, Peter C. Young. PR, 5(4):335-352, 1973. [doi]

1970

R70-8 Analog Methods for On-Line System Identification Using Noisy MeasurementsPeter C. Young. TC, 19(5):465-466, 1970. [doi]

1969

The differential equation-error method of real-time process identificationPeter C. Young. PhD thesis, University of Cambridge, UK, 1969. [doi]

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