Many industrial processes belong to distributed parameter systems (DPS) that have strong
spatial–temporal dynamics. Modeling of DPS is difficult but essential to simulation, control …

Dynamic mode decomposition with control (DMDc) is a modal decomposition method that
extracts dynamically relevant spatial structures disambiguating between the underlying …

Highly dissipative nonlinear partial differential equations (PDEs) are widely employed to
describe the system dynamics of industrial spatially distributed processes (SDPs). In this …

A temporally‐local model order‐reduction technique for nonlinear parabolic partial
differential equation (PDE) systems with time‐dependent spatial domains is presented. In …

The data-driven H∞ control problem of nonlinear distributed parameter systems is
considered in this paper. An off-policy learning method is developed to learn the H∞ control …

We present a novel control framework for the closed-loop operation of a hydraulic fracturing
process. Initially, we focus on the development of a first-principle model of a hydraulic …

Developing reduced-order models for nonlinear parabolic partial differential equation (PDE)
systems with time-varying spatial domains remains a key challenge as the dominant spatial …

In hydraulic fracturing of shale formations, compared to conventional reservoirs, the
fracturing fluid injected is of low‐viscosity and hence during pumping the proppant settles …

Time/space separation based spatiotemporal modeling methods have been proven to be
effective and efficient for modeling a class of distributed parameter systems (DPSs) …

We present a novel design framework of an optimal and practical pumping schedule to
achieve uniform proppant concentration across fracture at the end of pumping. By using the …