P. Young

发表

An instrumental variable method for real-time identification of a noisy process

P. Young, 1970 .

Parameter estimation in stochastic differential equations: An overview

Jan Nygaard Nielsen, P. Young, H. Madsen, 2000 .

The data-based mechanistic approach to the modelling, forecasting and control of environmental systems

Peter C. Young, P. Young, 2006, Annu. Rev. Control..

Uncertainty, Complexity and Concepts of Good Science in Climate Change Modelling: Are GCMs the Best Tools?

P. Young, S. Shackley, S. Parkinson, 1998 .

Recent developments in the modelling of imperfectly mixed airspaces.

Peter C. Young, Karl Janssens, Daniel Berckmans, 2000 .

Multi-state dependent parameter model identification and estimation for nonlinear dynamic systems

P. Young, J. Sadeghi, W. Tych, 2010 .

Some observations on instrumental variable methods of time-series analysis

P. Young, 1976 .

AN INSTRUMENTAL VARIABLE APPROACH TO ARMA MODEL IDENTIFICATION AND ESTIMATION

P. Young, 2006 .

An improved structure for model predictive control using non-minimal state space realisation

P. Young, Liuping Wang, 2006 .

Refined instrumental variable methods of recursive time-series analysis Part I. Single input, single output systems

P. Young, A. Jakeman, 1979 .

The use of linear regression and related procedures for the identification of dynamic processes

P. Young, 1968 .

Recursive Estimation and Time Series Analysis

Peter C. Young, P. Young, 1984 .

A REFINED IV METHOD FOR CLOSED-LOOP SYSTEM IDENTIFICATION

P. Young, P. V. D. Hof, M. Gilson, 2006 .

An approach to the linear multivariable servomechanism problem.

P. Young, J. Willems, 1972 .

Optimal instrumental variable method for closed-loop identification

P. Young, P. V. D. Hof, M. Gilson, 2011 .

Refined Instrumental Variable Identification of Continuous-time Hybrid Box-Jenkins Models

P. Young, M. Gilson, H. Garnier, 2008 .

An optimal IV technique for identifying continuous-time transfer function model of multiple input systems

P. Young, M. Gilson, H. Garnier, 2007 .

Refined instrumental variable methods of recursive time-series analysis Part II. Multivariable systems

P. Young, A. Jakeman, 1979 .

Unified estimation of discrete and continuous-time transfer function models

P. Young, 2008 .

Dynamic harmonic regression.

P. Young, W. Tych, D. J. Pedregal, 1999 .

Data assimilation and adaptive forecasting of water levels in the river Severn catchment, United Kingdom

P. Young, K. Beven, R. Romanowicz, 2006 .

Identification of nonlinearity in rainfall‐flow response using data‐based mechanistic modeling

P. Young, N. McIntyre, B. Orellana, 2011 .

Refined instrumental variable methods of recursive time-series analysis Part III. Extensions

P. Young, A. Jakeman, 1980 .

Optimal IV identification and estimation of continuous-time TF models

P. Young, 2002 .

Parameter Estimation for Continuous Time Models - A Survey

Peter C. Young, P. Young, 1979 .

A dynamic model for DO—BOD relationships in a non-tidal stream

M. B. Beck, P. Young, 1975 .

Data-based mechanistic modelling of environmental, ecological, economic and engineering systems.

Peter C. Young, P. Young, 1998 .

Environmetric time-series analysis: modelling natural systems from experimental time-series data.

P. Young, P. Minchin, 1991, International journal of biological macromolecules.

Recent advances in the data-based modelling and analysis of hydrological systems

P. Young, A. Jakeman, D. Post, 1997 .

A systems approach to recursive economic forecasting and seasonal adjustment

P. Young, C. Ng, P. Armitage, 1989 .

Longitudinal Dispersion in Natural Streams

P. Young, T. Beer, 1983 .

Simplicity out of complexity in environmental modelling: Occam's razor revisited.

P. Young, S. Parkinson, M. Lees, 1996 .

Proportional-integral-plus (PIP) design for delta (delta) operator systems Part 2. MIMO systems

P. Young, W. Tych, A. Chotai, 1998 .

State space control system design based on non-minimal state-variable feedback: Further generalization and unification results

P. Young, A. Chotai, C. Taylor, 2000 .

Predicting daily flows in ungauged catchments: model regionalization from catchment descriptors at the Coweeta Hydrologic Laboratory, North Carolina

Anthony J. Jakeman, Peter C. Young, Teemu Kokkonen, 2003 .

Computation of the instantaneous unit hydrograph and identifiable component flows with application to two small upland catchments — Comment

P. Young, K. Beven, 1991 .

DATA-BASED MECHANISTIC MODELLING OF A SNOW AFFECTED BASIN

P. Young, F. Pianosi, A. Castelletti, 2005 .

Identification of non-linear stochastic systems by state dependent parameter estimation

P. Young, P. McKenna, J. Bruun, 2001 .

Recursive estimation: A unified approach to the identification estimation, and forecasting of hydrological systems

P. Young, S. Wallis, 1985 .

Modulated cycles, an approach to modelling periodic components from rapidly sampled data

P. Young, D. J. Pedregal, 2006 .

Direct digital control by input-output, state variable feedback: theoretical background

P. Young, Changren Wang, 1988 .

An analysis of international tourism demand in Spain.

P. Young, D. J. Pedregal, 1997 .

Unobserved Component Models

P. Young, 2011 .

AM Data-Based Mechanistic and Top-Down Modelling

P. Young, 2018 .

Uncertainty and sensitivity in global carbon cycle modelling

Peter C. Young, Stuart Parkinson, P. Young, 1998 .

Macro-economic relativity: government spending, private investment and unemployment in the USA 1948–1998

Diego J. Pedregal, Peter C. Young, P. Young, 1999 .

Identification and Representation of State Dependent Non-linearities in Flood Forecasting Using the DBM Methodology

Peter C. Young, Keith Beven, David Leedal, 2012 .

Direct digital and adaptive control by input-output state variable feedback pole assignment

Peter C. Young, Arun Chotai, M. A. Behzadi, 1987 .

Concise encyclopedia of environmental systems

Peter C. Young, P. Young, 1993 .

Time-variable parameter and trend estimation in non-stationary economic time series

Peter C. Young, P. Young, 1994 .

Recursive and en-bloc approaches to signal extraction

Peter C. Young, P. Young, 1999 .

An analysis of the dynamic response of stomatal conductance to a reduction in humidity over leaves of Cedrella odorata

Peter C. Young, William J. Davies, Andy Jarvis, 1999 .

Data-based mechanistic modelling and the simplification of environmental systems.

Peter C. Young, Arun Chotai, P. Young, 2004 .

PUB and data-based mechanistic modelling: the importance of parsimonious continuous-time models.

Peter C. Young, Renata J. Romanowicz, P. Young, 2004 .

The estimation of continuous-time rainfall-flow models for flood risk management

P. C. Young, P. Young, 2010 .

A Control Systems Approach to Input Estimation with Hydrological Applications

Peter C. Young, Malgorzata Sumislawska, P. Young, 2012 .

Identification-based Diagnosis of Rainfall Stream Flow Data: the Tinderry Catchment

P. Young, A. Jakeman, K. Keesman, 2011 .

Non-Parametric Model Structure Identification and Parametric Efficiency in Nonlinear State Dependent Parameter Models

P. Young, P.C. Young, 2006, 2006 International Symposium on Evolving Fuzzy Systems.

Water Quality Modelling in Rivers with Limited Observational Data: River Elbe Case Study.

Peter C. Young, Renata J. Romanowicz, Ulrich Callies, 2004 .

DATA-BASED MECHANISTIC MODELLING AND CONTROL FOR THE PLANNING AND MANAGEMENT OF ENVIRONMENTAL SYSTEMS

P. Young, 2004 .

STATE-DEPENDENT PARAMETER NONLINEAR SYSTEMS: IDENTIFICATION, ESTIMATION AND CONTROL

Peter C. Young, Arun Chotai, A. P. McCabe, 2002 .

Chapter 13 Simplicity out of complexity

P. C. Young, S. Parkinson, P. Young, 2002 .

An ARMA Representation of Unobserved Component Models under Generalized Random Walk Specifications: New Algorithms and Examples

Peter C. Young, Marcos Bujosa, P. Young, 2002 .

Modelling and proportional-integral-plus control design for free air carbon dioxide enrichment systems

Peter C. Young, A. R. Glasock, Arunkumar Chotai, 2000 .

A data-based mechanistic modelling (DBM) approach to understanding dynamic sediment transmission through Wyresdale Park Reservoir, Lancashire, UK.

Peter C. Young, Laura Price, P. Young, 2000 .

- 1-DYNAMIC HARMONIC REGRESSION

P. Young, W. Tych, D. J. Pedregal, 1999 .

Identification of improved rainfall-runoff models for an ephemeral low-yielding Australian catchment

Anthony J. Jakeman, Peter C. Young, Wei Ye, 1998 .

What can tracer profiles tell us about the mechanisms giving rise to them

Peter C. Young, M. J. Lees, M. R. Thorpe, 1996 .

Environmetric Methods of Nonstationary Time-Series Analysis: Univariate Methods

Peter C. Young, P. Young, T. Young, 1992 .

Recursive estimation and forecasting of non‐stationary time series

Peter C. Young, P. Young, C. Ng, 1990 .

Data-based mechanistic modelling and forecasting globally averaged surface temperature

P. Young, 2017 .

Comments on "On-line identification of linear dynamic systems with applications to Kalman filtering"

Peter C. Young, P. Young, 1972 .

Risk-based probabilistic fluvial flood forecasting for integrated catchment models - Phase 1 Report

P. Young, K. Beven, R. Moore, 2009 .

Modelling of Water Movement in Trees

P. Young, R. Milne, 1985 .

The identification of continuous-time linear and nonlinear models: a tutorial with environmental applications

Peter C. Young, Hugues Garnier, Andy Jarvis, 2003 .

Recursive estimation and modelling of nonstationary and nonlinear time series

P. Young, D. Runkle, 1990 .

Recursive Extrapolation, Interpolation and Smoothing of Nonstationary Time-series

Peter C. Young, P. Young, 1988 .

Recursive-Iterative IV Estimation of Multiple-Input Transfer Function Models

Peter C. Young, C. Cobelli, K. Thomaseth, 1985 .

Water supply in monsoonal Asia: modelling and predicting small tank storage

P. Young, A. Jakeman, S. Mahendrarajah, 1996 .

Downward Approach to Hydrological Model Development

Peter C. Young, Murugesu Sivapalan, P. Young, 2006 .

Technical Note TN/PCY/5 (2018) Efficiently Parameterised Models of the Silverbox Nonlinear Circuit

P. Young, 2018 .

New Results on the DBM Modelling, Forecasting and Control of Global Climate data

P. Young, 2017 .

***** Hypothetico-Inductive Data-Based Mechanistic Modelling, Forecasting and Control of Global Climate data

P. Young, 2014 .

Reconstructing historic reservoir sedimentation rates using data-based mechanistic modelling

P. Young, L. Price, J. Rowan, 2001 .

Modelling reservoir sedimentation and estimating historical deposition rates using a data-based mechanistic (DBM) approach

P. Young, L. Price, J. Rowan, 2000 .

The modelling and control of water quality in a river system

Peter C. Young, Bruce Beck, P. Young, 1974, Autom..

Comment on 'A quasi-ARMAX approach to the modelling of non-linear systems' by J. Hu et al.

Peter C. Young, P. Young, 2001 .

Control Structures and Interpretations

P. Young, A. Chotai, C. Taylor, 2013 .

On the Initialization of Refined Instrumental Variable Estimation Algorithms

P. Young, 2016 .

True Digital Control for Univariate Systems

P. Young, A. Chotai, C. Taylor, 2013 .

Robust PIP Tracking Control for NMSS Models with Additive Nonlinear Dynamics and Noises: Discrete Time Cases

P. Young, A. Chotai, H. Wang, 2006, 2006 6th World Congress on Intelligent Control and Automation.

Non‐Minimal State Variable Feedback

P. Young, A. Chotai, C. Taylor, 2013 .

A DBM model for snowmelt simulation

P. Young, F. Pianosi, A. Castelletti, 2009 .

Refined instrumental variable estimation: Maximum likelihood optimization of a unified Box-Jenkins model

Peter C. Young, P. Young, 2015, Autom..

Implementation of a new general modelling approach to Control Imperfectly Mixed PROcesses (CONIMPRO)

Jean-Marie Aerts, Daniel Berckmans, Peter C. Young, 1999 .

Non-minimal state space design: a unified approach to state variable feedback.

Peter C. Young, Arun Chotai, C. J. Taylor, 2000 .

Real-time flow forecasting.

Soroosh Sorooshian, Peter C. Young, Howard S. Wheater, 2007 .

Recursive Estimation, Forecasting, and Adaptive Control

Peter C. Young, P. Young, 1989 .

Managing Innovation: Optimizing Resource Allocation Using New York City's Innovative Technology Prioritization Tool

Peter C. Young, Dimitrios Katehis, Sarah Dailey, 2010 .

Efficient Estimation of the High Dimensional Model Representation for Non-Linear Models (PSAM-0402)

Peter C. Young, Andrea Pagano, Marco Ratto, 2006 .

Reviews: Environmental Systems: Philosophy, Analysis and Control, Regional and Urban Economics, Managing the Sense of a Region, Systems of Cities: Readings on Structure, Growth and Policy, Economics in Institutional Perspective

P. Young, B. Berry, T. O'riordan, 1979 .

Further evidence on forecasting international GNP growth rates using unobserved components transfer function models

Alfonso Novales Cinca, P. Young, Antonio García Ferrer, 1993 .

Recursive Identification, Estimation, and Forecasting of Nonstationary Economic Time Series with Applications to GNP International Data

Alfonso Novales Cinca, P. Young, Antonio García Ferrer, 1993 .

State dependent parameter – proportional integral plus (SDP-PIP) control of non-linear systems.

P. Young, A. Chotai, C. Taylor, 2003 .

Comments on “An analysis of the international tourism demand in Spain” by P. González and P. Moral

P. Young, D. J. Pedregal, 1997 .

A general framework for Dynamic Emulation Modelling in environmental problems

Andrea Castelletti, Peter C. Young, Rodolfo Soncini-Sessa, 2012, Environ. Model. Softw..

Linear dynamic harmonic regression

Peter C. Young, Antonio García-Ferrer, Marcos Bujosa, 2007, Comput. Stat. Data Anal..

An unobserved component model for multi-rate forecasting of telephone call demand: the design of a forecasting support system

Diego J. Pedregal, John Davies, Peter C. Young, 2002 .

The Identification and Estimation of Nonlinear Stochastic Systems

Peter C. Young, P. Young, 2001 .

Data-based mechanistic modelling, generalised sensitivity and dominant mode analysis

Peter C. Young, P. Young, 1999 .

The determination of the parameters of a dynamic process

Peter C. Young, P. Young, 1965 .

Monitoring and forecasting the COVID-19 epidemic in the UK

P. Young, Fengwei Chen, 2021, Annual Reviews in Control.

Efficient parameterisation of nonlinear system models: a comment on Nöel and Schoukens (2018)

Peter C. Young, Alexandre Janot, P. Young, 2018, Int. J. Control.

Data-based mechanistic modelling and the rainfall-flow non-linearity.

Peter C. Young, Keith Beven, P. Young, 1994 .

The Effects of Sulphur Dioxide on Phloem Transport in Two Cereals

P. C. Young, P. Young, P. Minchin, 1988 .

Process Parameter Estimation and Self Adaptive Control

Peter C. Young, P. Young, 1965 .

Advances in real–time flood forecasting

Peter C Young, P. Young, 2002, Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

Time Series Methods in Biological and Medical Data Analysis

Peter C. Young, A. J. Jakeman, P. Young, 1979 .

Forward path model predictive control using a non-minimal state-space form

Vasileios Exadaktylos, Peter C. Young, C. J. Taylor, 2009 .

State Dependent Parameter metamodelling and sensitivity analysis

Peter C. Young, Andrea Pagano, Marco Ratto, 2007, Comput. Phys. Commun..

Continuous-time non-minimal state-space design

Peter C. Young, Peter J. Gawthrop, Liuping Wang, 2007, Int. J. Control.

Multivariable DELTA (δ) Operator Control in a Plant Physiology Experiment

Paul McKenna, Andy Jarvis, Peter C. Young, 1997 .

Modelling and PIP control of a glasshouse micro-climate

Peter C. Young, Arun Chotai, M. J. Lees, 1994 .

THE CAPTAIN TOOLBOX FOR MATLAB

Peter C. Young, C. James Taylor, Wlodzimierz Tych, 2006 .

A simple robust method of fractional time-delay estimation for linear dynamic systems

P. Young, Fengwei Chen, 2022, Autom..

Data-Driven Modeling of Wireless Power Transfer Systems With Multiple Transmitters

Peter C. Young, Qijun Deng, Fengwei Chen, 2020, IEEE Transactions on Power Electronics.

Data-Driven Modeling of Wireless Power Transfer Systems With Slowly Time-Varying Parameters

Peter C. Young, Fengwei Chen, Hugues Garnier, 2020, IEEE Transactions on Power Electronics.

An improved instrumental variable method for industrial robot model identification

Peter C. Young, Alexandre Janot, Mathieu Brunot, 2018 .

New developments in the CAPTAIN Toolbox for Matlab with case study examples

Peter C. Young, C. James Taylor, Wlodzimierz Tych, 2018 .

Real-time identification of linear continuous-time systems with slowly time-varying parameters

Peter C. Young, Arturo Andrés Padilla Bernedo, Hugues Garnier, 2016, 2016 IEEE 55th Conference on Decision and Control (CDC).

The advantages of directly identifying continuous-time transfer function models in practical applications

Peter C. Young, Hugues Garnier, P. Young, 2014, Int. J. Control.

Comment on 'Projection-based identification algorithm for grey-box continuous-time models' by Ichiro Maruta and Toshiharu Sugie

Peter C. Young, P. Young, 2014, Syst. Control. Lett..

Identification, Estimation and Control of Continuous-Time Systems Described by Delta Operator Models

Peter C. Young, Arun Chotai, Wlodek Tych, 1991 .

Recursive Estimation and Time-Series Analysis: An Introduction

Peter C. Young, P. Young, 1984 .

Advanced methods of recursive time-series analysis

Anthony J. Jakeman, Peter C. Young, P. Young, 1983 .

On the decoupling of system and noise model parameter estimation in time-series analysis

Anthony J. Jakeman, Peter C. Young, P. Young, 1981 .

Instrumental Variable Algorithms for Multiple Input Systems Described by Multiple Transfer Functions

Anthony J. Jakeman, Peter C. Young, L. Paul Steele, 1980, IEEE Transactions on Systems, Man, and Cybernetics.

Disturbance Observer-Based Repetitive Control System With Nonminimal State-Space Realization and Experimental Evaluation

P. Young, Liuping Wang, C. Freeman, 2023, IEEE Transactions on Control Systems Technology.

Disturbance Observer Based Repetitive Control System with Non-minimal State Space Realization and Anti-windup Mechanism

E. Rogers, P. Young, Liuping Wang, 2020 .

Direct Identification of Continuous-time Models from Sampled Data: Issues, Basic Solutions and Relevance

Peter C. Young, Hugues Garnier, Liuping Wang, 2008 .

Identification and estimation of continuous-time, data-based mechanistic (DBM) models for environmental systems

Peter C. Young, Hugues Garnier, P. Young, 2006, Environ. Model. Softw..

Time-domain approaches to continuous-time model identification of dynamical systems from sampled data

H. Garnier, P. Young, P. Young, 2004, Proceedings of the 2004 American Control Conference.

True Digital Control: Statistical Modelling and Non-Minimal State Space Design

Peter C. Young, C. James Taylor, Arunkumar Chotai, 2013 .

Stabilizing global mean surface temperature: A feedback control perspective

Peter C. Young, C. James Taylor, Andrew Jarvis, 2009, Environ. Model. Softw..

Model-based PIP control of the spatial temperature distribution in cars

P. C. Young, A. Van Brecht, S. Quanten, 2003 .

Environmental time series analysis and forecasting with the Captain toolbox

Diego J. Pedregal, Peter C. Young, C. James Taylor, 2007, Environ. Model. Softw..

Parameter estimation for continuous-time models - A survey

Peter Young, P. Young, 1979, Autom..

Model Order Identification for Continuous-time Models

Peter C. Young, Liuping Wang, P. Young, 2008 .

Non-minimal state-space model-based continuous-time model predictive control with constraints

Peter C. Young, C. James Taylor, Peter J. Gawthrop, 2009, Int. J. Control.

Uncertainty , sensitivity analysis and the role of data based mechanistic modeling in hydrology

Peter C. Young, Florian Pappenberger, Marco Ratto, 2006 .

Parallel Processes in Hydrology and Water Quality: A Unified Time‐Series Approach

Peter C. Young, P. Young, 1992 .

Modelling and PIP control design for open-top chambers

Peter C. Young, Arun Chotai, C. J. Taylor, 1998 .

Idenitification, estimation and control of glasshouse systems

Peter C. Young, Arun Chotai, Wlodek Tych, 1991 .

THE UNCERTAINTY CASCADE IN FLOOD FORECASTING

Peter C. Young, Keith Beven, Florian Pappenberger, 2006 .

Non-linear control by input–output state variable feedback pole assignment

Peter C. Young, C. James Taylor, Arun Chotai, 2009, Int. J. Control.

Nonlinear pole assignment control of state dependent parameter models with time delays.

Peter C. Young, Arun Chotai, C. James Taylor, 2008 .

Hypothetico‐inductive data‐based mechanistic modeling of hydrological systems

Peter C. Young, P. Young, 2013 .

Comment on “Bayesian recursive parameter estimation for hydrologic models” by M. Thiemann, M. Trosset, H. Gupta, and S. Sorooshian

Peter C. Young, Keith Beven, P. Young, 2003 .

Time-Series Methods and Recursive Estimation in Hydrological Systems Analysis

Peter C. Young, P. Young, 1986 .

Identification of continuous-time models with slowly time-varying parameters

Peter C. Young, Juan I. Yuz, Fengwei Chen, 2019, Control Engineering Practice.

Water quality models: rivers and reservoirs

B. Henderson-Sellers, P. Young, J. R. Costa, 1990 .

Instrumental Variable Methods for Closed-loop Continuous-time Model Identification

Peter C. Young, Marion Gilson, Paul M.J. Van den Hof, 2008 .

The modelling and control of pollution in a river system

Peter C. Young, Bruce Beck, P. Young, 1976 .

A robust sequential CO2 emissions strategy based on optimal control of atmospheric CO2 concentrations

Peter C. Young, Andy Jarvis, Arun Chotai, 2008 .

A robust sequential CO 2 emissions strategy based on optimal control of atmospheric CO 2 concentrations

P. Young, A. Chotai, A. Jarvis, 2005 .

Top‐down and data‐based mechanistic modelling of rainfall–flow dynamics at the catchment scale

Peter C. Young, P. Young, 2003 .

Data-Based Mechanistic Modeling of Engineering Systems

Peter C. Young, P. Young, 1998 .

Design and application of PIP controllers: robust control of the IFAC93 benchmark

Peter C. Young, Arun Chotai, C. James Taylor, 2001 .

A guide to good practice in modeling semantics for authors and referees

Keith Beven, Peter C. Young, P. Young, 2013 .

Real‐Time Updating in Flood Forecasting and Warning

Peter C. Young, P. Young, 2010 .

Computationally efficient flood water level prediction (with uncertainty).

Peter C. Young, Keith Beven, Renata J. Romanowicz, 2009 .

Reduced Order Emulation of Distributed Hydraulic Simulation Models

Peter C. Young, Keith Beven, David Leedal, 2009 .

Uncertainty propagation in a sequential model for flood forecasting.

Peter C. Young, Keith Beven, Renata J. Romanowicz, 2006 .

Water quality in river systems: Monte‐Carlo Analysis

Peter C. Young, Paul Whitehead, P. Young, 1979 .

The Validity and Credibility of Models for Badly Defined Systems

Peter C. Young, P. Young, 1983 .

The Instrumental Variable Method: A Practical Approach to Identification and System Parameter Estimation

Peter C. Young, P. Young, 1985 .

Data‐Based Identification and Estimation of Transfer Function Models

Peter C. Young, Arun Chotai, C. James Taylor, 2013 .

What does continuous-time model identification have to offer?

Peter C. Young, Hugues Garnier, P. Young, 2012 .

Practical experience with unified discrete and continuous–time, multi–input identification for control system design

Peter C. Young, Philip Cross, C. James Taylor, 2012 .

The refined instrumental variable method

Peter C. Young, P. Young, 2008 .

Cost effective combined axial fan and throttling valve control of ventilation rate

Daniel Berckmans, Arun Chotai, Erik Vranken, 2004 .

Proportional-integral-plus (PIP) control of ventilation rate in agricultural buildings

Daniel Berckmans, Erik Vranken, Peter C. Young, 2004 .

True Digital Control of Carbon Dioxide in Agricultural Crop Growth Experiments

Peter C. Young, M. J. Lees, C. James Taylor, 1996 .

An instrumental variable method for model order identification

Anthony J. Jakeman, Peter C. Young, Ross McMurtrie, 1980, Autom..

Simple refined IV methods of closed-loop system identification

Peter C. Young, Hugues Garnier, Marion Gilson, 2009 .

Data-Based Mechanistic Modelling (DBM) and control of mass and energy transfer in agricultural buildings

Daniel Berckmans, Karl Janssens, Laura Price, 1999 .

TRUE DIGITAL CONTROL OF GLASSHOUSE SYSTEMS

Peter C. Young, Arun Chotai, P. Davis, 1991 .

Chapter 1 – IDENTIFICATION, ESTIMATION AND TRUE DIGITAL CONTROL OF GLASSHOUSE SYSTEMS

Peter C. Young, Arun Chotai, Wlodek Tych, 1993 .

Recursive forecasting, smoothing and seasonal adjustment of non‐stationary environmental data

Peter C. Young, D. Parker, C. N. Ng, 1991 .

Gauss, Kalman and advances in recursive parameter estimation

Peter C. Young, P. Young, 2011 .

High-resolution analysis of tomato leaf elongation: the application of novel time-series analysis techniques.

P. Young, W. Davies, L E Price, 2001, Journal of experimental botany.

A unified approach to environmental systems modeling

Peter C. Young, Marco Ratto, P. Young, 2009 .

Computer aided control system design of PIP controllers for systems described by delta operator and backward shift models.

Peter C. Young, Arun Chotai, M. J. Lees, 1994 .

TRUE DIGITAL CONTROL OF INTERURBAN TRAFFIC NETWORKS

Peter C. Young, Arun Chotai, Jim Taylor, 1996 .

A non-minimal state variable feedback approach to multivariable control of glasshouse climate

Peter C. Young, Arun Chotai, M. J. Lees, 1995 .

A Matlab software framework for dynamic model emulation

Peter C. Young, Wlodek Tych, P. Young, 2012, Environ. Model. Softw..

Identification of a multivariable state dependency for airflow rate in a forced ventilation test chamber.

Peter C. Young, C. James Taylor, M. A. Stables, 2004 .

Statistical Emulation of Large Linear Dynamic Models

Peter C. Young, Marco Ratto, P. Young, 2011, Technometrics.

Data-based mechanistic modeling, forecasting, and control

A. Chotai, P. Young, P. Young, 2001 .

A systems model of stream flow and water quality in the bedford-ouse river—1. stream flow modelling

Peter C. Young, Paul Whitehead, George M. Hornberger, 1979 .

Systematic Identification of DO-BOD Model Structure

Peter C. Young, Bruce Beck, P. Young, 1976 .

Data‐Based Mechanistic Modelling and the Emulation of Large Environmental System Models

Peter C. Young, David Leedal, P. Young, 2013 .

Rainfall‐Runoff Modeling: Transfer Function Models

Peter C. Young, P. Young, 2006 .

1 st , 12 : 00 AM PUB and Data-Based Mechanistic Modelling : the Importance of Parsimonious Continuous-Time Models

P. Young, R. Romanowicz, 2004 .

Data-Based Mechanistic and Top-Down Modelling

Peter C. Young, P. Young, 2002 .

DATA-BASED MECHANISTIC MODELLING OF ENVIRONMENTAL SYSTEMS

Peter C. Young, P. Young, 2001 .

A data based mechanistic approach to nonlinear flood routing and adaptive flood level forecasting

Peter C. Young, Florian Pappenberger, Keith Beven, 2008 .

Simulation Model Emulation in Control System Design

Peter C. Young, N. W. Rees, C. X. Lu, 2012 .

A re-evaluation of the Earth’s surface temperature response to radiative forcing

P. Young, J. Bruun, P. Geoffrey Allen, 2021, Environmental Research Letters.

Data-Based Mechanistic Modelling: Natural Philosophy Revisited?

Peter C. Young, P. Young, 2012 .

Uncertainty, sensitivity analysis and the role of data based mechanistic modeling in hydrology

P. Young, M. Ratto, F. Pappenberger, 2006 .

Testing probabilistic adaptive real‐time flood forecasting models

Peter C. Young, Keith Beven, Albrecht Weerts, 2014 .

Data-based mechanistic modelling and river flow forecasting

Peter C. Young, P. Young, 2006 .

On univariate forecasting comparisons the case of the spanish automobile industry

P. Young, Antonio García Ferrer, Juan del Hoyo Bernat, 1994 .

Some Comments on the Use and Abuse of the Hodrick-Prescott Filter

P. Young, D. J. Pedregal, 2001 .

Instrumental variable methods for identifying partial differential equation models

P. Young, M. Gilson, H. Garnier, 2013, Int. J. Control.

Recent Developments in the CAPTAIN Toolbox for Matlab

Peter C. Young, C. James Taylor, P. Young, 2012 .

Atmospheric temperature responses to solar irradiance and geomagnetic activity

P. Young, M. Jarvis, R. Horne, 2007 .

Refined Instrumental Variable methods for closed-loop system identification

Peter C. Young, Hugues Garnier, Marion Gilson, 2009 .

New Approaches to Volcanic Time Series Analysis

P. Young, 2005 .

Commentaries. Comments on ‘A Unified View of Statistical Forecasting Procedures’ by A. C. Harvey

Peter C. Young, P. Young, 1984 .

A second generation adaptive autostabilization system for airborne vehicles

Peter C. Young, P. Young, 1979, Autom..

2 – THE MODELLING AND CONTROL OF NUTRIENT FILM SYSTEMS

Peter C. Young, Arun Chotai, M. A. Behzadi, 1987 .

Adaptive true digital control (TDC) of continuous-time systems using -operator models.

Peter C. Young, Arun Chotai, Wlodek Tych, 1992 .

Self-adaptive and self-tuning control of a nutrient film technique (NFT) system

Peter C. Young, Arunkumar Chotai, P. Young, 1991 .

True digital control: A unified design procedure for linear sampled data control systems

Peter C. Young, A. Chotai, W. Tych, 1991 .

An event classification approach to the identification of hydrological change.

Peter C. Young, Keith Beven, John Ewen, 2008 .

Data-Based Mechanistic Modelling & Real-Time Adaptive Flood Forecasting

Peter C. Young, Keith Beven, Renata J. Romanowicz, 2011 .

E: Block Diagram Derivation of PIP Pole Placement Algorithm

Peter C. Young, Arun Chotai, C. James Taylor, 2013 .

Reduced order emulation of distributed hydraulic models

Peter C. Young, Keith Beven, David Leedal, 2009 .

Hydrology and Earth System Sciences Discussions Uncertainty, Sensitivity Analysis and the Role of Data Based Mechanistic Modeling in Hydrology

P. Young, M. Ratto, F. Pappenberger, 2022 .

A recursive estimation approach to the spatio-temporal analysis and modelling of air quality data

Peter C. Young, Renata J. Romanowicz, Peter Diggle, 2006, Environ. Model. Softw..

Data assimilation in the identification of flood inundation models: derivation of on-line muti-step ahead predictions in flows.

Peter C. Young, K. J. Beven, P. Young, 2004 .

A recursive approach to time-series analysis for multi-variable systems

Peter C. Young, Paul Whitehead, P. Young, 1977 .