TY - JOUR
T1 - Representation of networks and systems with delay
T2 - DDEs, DDFs, ODE–PDEs and PIEs
AU - Peet, Matthew M.
N1 - Funding Information: This work was supported by the National Science Foundation under grants No. 1739990 and 1935453 . The material in this paper was not presented at any conference. This paper was recommended for publication in revised form by Associate Editor Nikolaos Bekiaris-Liberis under the direction of Editor Miroslav Krstic. Publisher Copyright: © 2021 Elsevier Ltd
PY - 2021/5
Y1 - 2021/5
N2 - Delay-Differential Equations (DDEs) are the most common representation for systems with delay. However, the DDE representation is limited. In network models with delay, the delayed channels are low-dimensional and accounting for this heterogeneity is not possible in the DDE framework. In addition, DDEs cannot be used to model difference equations. Furthermore, estimation and control of systems in DDE format has proven challenging, despite decades of study. In this paper, we examine alternative representations for systems with delay and provide formulae for conversion between representations. First, we examine the Differential-Difference (DDF) formulation which allows us to represent the low-dimensional nature of delayed information. Next, we examine the coupled ODE–PDE formulation, for which backstepping methods have recently become available. Finally, we consider the algebraic Partial Integral Equation (PIE) representation, which allows the optimal estimation and control problems to be solved efficiently through the use of recent software packages such as PIETOOLS. In each case, we consider a very general class of delay systems, specifically accounting for all four possible sources of delay — state delay, input delay, output delay, and process delay. We then apply these representations to 3 archetypical network models.
AB - Delay-Differential Equations (DDEs) are the most common representation for systems with delay. However, the DDE representation is limited. In network models with delay, the delayed channels are low-dimensional and accounting for this heterogeneity is not possible in the DDE framework. In addition, DDEs cannot be used to model difference equations. Furthermore, estimation and control of systems in DDE format has proven challenging, despite decades of study. In this paper, we examine alternative representations for systems with delay and provide formulae for conversion between representations. First, we examine the Differential-Difference (DDF) formulation which allows us to represent the low-dimensional nature of delayed information. Next, we examine the coupled ODE–PDE formulation, for which backstepping methods have recently become available. Finally, we consider the algebraic Partial Integral Equation (PIE) representation, which allows the optimal estimation and control problems to be solved efficiently through the use of recent software packages such as PIETOOLS. In each case, we consider a very general class of delay systems, specifically accounting for all four possible sources of delay — state delay, input delay, output delay, and process delay. We then apply these representations to 3 archetypical network models.
KW - Delay
KW - Networked control
KW - PDEs
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U2 - 10.1016/j.automatica.2021.109508
DO - 10.1016/j.automatica.2021.109508
M3 - Article
SN - 0005-1098
VL - 127
JO - Automatica
JF - Automatica
M1 - 109508
ER -