Encrypted Decentralized Model Predictive Control of Nonlinear Processes with Input Delays

Yash A. Kadakia, Aisha Alnajdi, Fahim Abdullah, Panagiotis D. Christofides

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This work focuses on enhancing the operational safety, cybersecurity, computational efficiency, and closed-loop performance of large-scale nonlinear processes with input delays. This is achieved by employing a decentralized model predictive controller (MPC) with encrypted networked communication. Within this decentralized setup, the nonlinear process is partitioned into multiple subsystems, each controlled by a distinct Lyapunov-based MPC. These controllers take into account the interactions between subsystems by utilizing full state feedback. To address the performance degradation associated with input delays, we integrate a predictor with each LMPC to compute the states after the input delay period. The LMPC process model is initialized with these predicted states. Furthermore, to enhance cybersecurity, all signals transmitted to and received from each subsystem are encrypted. Guidelines are established to implement this proposed control structure in any nonlinear system with input delays. The simulation results, conducted on a nonlinear chemical process network, illustrate the effective closed-loop performance of the decentralized MPCs alongside the predictor with encrypted communication when dealing with input delays in a large process.

Original languageEnglish
Title of host publication2024 American Control Conference, ACC 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4216-4223
Number of pages8
ISBN (Electronic)9798350382655
DOIs
StatePublished - 2024
Externally publishedYes
Event2024 American Control Conference, ACC 2024 - Toronto, Canada
Duration: Jul 10 2024Jul 12 2024

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619

Conference

Conference2024 American Control Conference, ACC 2024
Country/TerritoryCanada
CityToronto
Period07/10/2407/12/24

Funding

Financial support from the National Science Foundation, CBET-2227241, is gratefully acknowledged.

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