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Related papers: $L_2$-Gain Analysis of Coupled Linear 2D PDEs usin…

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We introduce a Partial Integral Equation (PIE) representation of Partial Differential Equations (PDEs) in two spatial variables. PIEs are an algebraic state-space representation of infinite-dimensional systems and have been used to model 1D…

Analysis of PDEs · Mathematics 2024-06-18 Declan S. Jagt , Matthew M. Peet

Any suitably well-posed PDE in two spatial dimensions can be represented as a Partial Integral Equation (PIE) -- with system dynamics parameterized using Partial Integral (PI) operators. Furthermore, $L_2$-gain analysis of PDEs with a PIE…

Optimization and Control · Mathematics 2024-06-18 Declan S. Jagt , Matthew M. Peet

In this paper, we present solvable, convex formulations of $H_2$-optimal state estimation and state-feedback control problems for a general class of linear Partial Differential Equations (PDEs) with one spatial dimension. These convex…

Optimization and Control · Mathematics 2024-04-29 Sachin Shivakumar , Matthew Peet

We present a new Partial Integral Equation (PIE) representation of Partial Differential Equations (PDEs) in which it is possible to use convex optimization to perform stability analysis with little or no conservatism. The first result gives…

Analysis of PDEs · Mathematics 2020-09-14 Matthew M. Peet

In this paper, we present the Partial Integral Equation (PIE) representation of linear Partial Differential Equations (PDEs) in one spatial dimension, where the PDE has spatial integral terms appearing in the dynamics and the boundary…

Numerical Analysis · Mathematics 2022-12-19 Sachin Shivakumar , Amritam Das , Matthew Peet

In this paper, we propose an LMI-based approach to analyze input-output properties of coupled linear PDE systems. This work expands on a newly developed state-space theory for coupled PDEs and extends the positive-real and bounded-real…

Optimization and Control · Mathematics 2020-05-01 Sachin Shivakumar , Matthew M. Peet

Physical processes evolving in both time and space are often modeled using Partial Differential Equations (PDEs). Recently, it has been shown how stability analysis and control of coupled PDEs in a single spatial variable can be more…

Analysis of PDEs · Mathematics 2026-05-20 Declan S. Jagt , Matthew M. Peet

The $H_2$ norm is a commonly used performance metric in the design of estimators. However, $H_2$-optimal estimation of most PDEs is complicated by the lack of transfer function and state-space representations. To address this problem, we…

Optimization and Control · Mathematics 2026-05-19 Danio Braghini , Sachin Shivakumar , Matthew M. Peet

In this work, we present a scalable Linear Matrix Inequality (LMI) based framework to verify the stability of a set of linear Partial Differential Equations (PDEs) in one spatial dimension coupled with a set of Ordinary Differential…

Optimization and Control · Mathematics 2018-12-21 Amritam Das , Sachin Shivakumar , Siep Weiland , Matthew Peet

The Partial Integral Equation (PIE) framework was developed to computationally analyze linear Partial Differential Equations (PDEs) where the PDE is first converted to a PIE and then the analysis problem is solved by solving operator-valued…

Numerical Analysis · Mathematics 2022-04-04 Sachin Shivakumar , Matthew Peet

We consider $\hinf$-optimal state-feedback control of the class of linear Partial Differential Equations (PDEs) which admit a Partial Integral Equation (PIE) representation. While linear matrix inequalities are commonly used for optimal…

Optimization and Control · Mathematics 2026-04-07 Sachin Shivakumar , Amritam Das , Matthew Peet

Partial Integral Equations (PIEs) have been used to represent both systems with delay and systems of Partial Differential Equations (PDEs) in one or two spatial dimensions. In this paper, we show that these results can be combined to obtain…

Optimization and Control · Mathematics 2024-06-18 Declan S. Jagt , Matthew M. Peet

It has recently been shown that the evolution of a linear Partial Differential Equation (PDE) can be more conveniently represented in terms of the evolution of a higher spatial derivative of the state. This higher spatial derivative (termed…

Analysis of PDEs · Mathematics 2023-09-12 Declan Jagt , Peter Seiler , Matthew Peet

PDEs with periodic boundary conditions are frequently used to model processes in large spatial environments, assuming solutions to extend periodically beyond some bounded interval. However, solutions to these PDEs often do not converge to a…

Analysis of PDEs · Mathematics 2025-09-04 Declan Jagt , Sergei Chernyshenko , Matthew Peet

Impulse-to-peak response (I2P) analysis for state-space ordinary differential equation (ODE) systems is a well-studied classical problem. However, the techniques employed for I2P optimal control of ODEs have not been extended to partial…

Optimization and Control · Mathematics 2026-04-07 Tristan Thomas , Sachin Shivakumar , Javad Mohammadpour Velni

It has been shown that the existence of a Partial Integral Equation (PIE) representation of a Partial Differential Equation (PDE) simplifies many numerical aspects of analysis, simulation, and optimal control. However, the PIE…

Optimization and Control · Mathematics 2024-03-14 Sachin Shivakumar , Amritam Das , Siep Weiland , Matthew Peet

In this paper, we present a convex formulation of $H_{\infty}$-optimal control problem for coupled linear ODE-PDE systems with one spatial dimension. First, we reformulate the coupled ODE-PDE system as a Partial Integral Equation (PIE)…

Optimization and Control · Mathematics 2020-06-26 Sachin Shivakumar , Amritam Das , Siep Weiland , Matthew M. Peet

This paper considers the H\infty-optimal estimation problem for linear systems with multiple delays in states, output, and disturbances. First, we formulate the H\infty-optimal estimation problem in the Delay-Differential Equation (DDE)…

Optimization and Control · Mathematics 2020-04-10 Shuangshuang Wu , Sachin Shivakumar , Matthew M. Peet , Changchun Hua

Learning the evolutionary dynamics of Partial Differential Equations (PDEs) is critical in understanding dynamic systems, yet current methods insufficiently learn their representations. This is largely due to the multi-scale nature of the…

Machine Learning · Computer Science 2024-10-16 Aoming Liang , Zhaoyang Mu , Pengxiao Lin , Cong Wang , Mingming Ge , Ling Shao , Dixia Fan , Hao Tang

We consider the stability analysis of a large class of linear 1-D PDEs with polynomial data. This class of PDEs contains, as examples, parabolic and hyperbolic PDEs, PDEs with boundary feedback and systems of in-domain/boundary coupled…

Systems and Control · Computer Science 2017-09-19 Aditya Gahlawat , Giorgio Valmorbida
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