Engineering Commons^™

Integrated Cyberattack Detection And Resilient Control Strategies Using Lyapunov-Based Economic Model Predictive Control, Henrique Oyama, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

The use of an integrated system framework, characterized by numerous cyber/physical components (sensor measurements, signals to actuators) connected through wired/wireless networks, has not only increased the ability to control industrial systems, but also the vulnerabilities to cyberattacks. State measurement cyberattacks could pose threats to process control systems since feedback control may be lost if the attack policy is not thwarted. Motivated by this, we propose three detection concepts based on Lyapunov‐based economic model predictive control (LEMPC) for nonlinear systems. The first approach utilizes randomized modifications to an LEMPC formulation online to potentially detect cyberattacks. The second method detects attacks when …

Interactions Between Control And Process Design Under Economic Model Predictive Control, Henrique Oyama, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

conomic model predictive control (EMPC) is a model-based control scheme that integrates process control and economic optimization, which can potentially allow for time-varying operating policies to maximize economic performance. The manner in which an EMPC operates a process to optimize economics depends on the process dynamics, which are fixed by the process design. This raises the question of how process and EMPC designs interact. Works which have addressed process and control design interactions for steady-state operation have sought to simultaneously develop process designs and control law parameters to find the most profitable way to operate a process that is able …

Mitigating Safety Concerns And Profit/Production Losses For Chemical Process Control Systems Under Cyberattacks Via Design/Control Methods, Helen Durand, Matthew Wegener

Chemical Engineering and Materials Science Faculty Research Publications

One of the challenges for chemical processes today, from a safety and profit standpoint, is the potential that cyberattacks could be performed on components of process control systems. Safety issues could be catastrophic; however, because the nonlinear systems definition of a cyberattack has similarities to a nonlinear systems definition of faults, many processes have already been instrumented to handle various problematic input conditions. Also challenging is the question of how to design a system that is resilient to attacks attempting to impact the production volumes or profits of a company. In this work, we explore a process/equipment design framework for …

Responsive Economic Model Predictive Control For Next-Generation Manufacturing, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

There is an increasing push to make automated systems capable of carrying out tasks which humans perform, such as driving, speech recognition, and anomaly detection. Automated systems, therefore, are increasingly required to respond to unexpected conditions. Two types of unexpected conditions of relevance in the chemical process industries are anomalous conditions and the responses of operators and engineers to controller behavior. Enhancing responsiveness of an advanced control design known as economic model predictive control (EMPC) (which uses predictions of future process behavior to determine an economically optimal manner in which to operate a process) to unexpected conditions of these types …

Process Data Analytics Using Deep Learning Techniques, Majid Moradi Aliabadi

Wayne State University Theses

In chemical manufacturing plants, numerous types of data are accessible, which could be process operational data (historical or real-time), process design and product quality data, economic and environmental (including process safety, waste emission and health impact) data. Effective knowledge extraction from raw data has always been a very challenging task, especially the data needed for a type of study is huge. Other characteristics of process data such as noise, dynamics, and highly correlated process parameters make this more challenging.

In this study, we introduce an attention-based RNN for multi-step-ahead prediction that can have applications in model predictive control, fault diagnosis, …

Ac Conductivity Studies Of Polyethylene-Oxide-Garnet Type Li7la3zr2o12 Hybrid Composite Solid Polymer Electrolyte For Li-Ion Battery, Parisa Bashiri

Wayne State University Dissertations

Solid electrolytes including ceramics and polymers are considered to be the ultimate substitute for organic liquid electrolytes currently used in commercialized lithium ion batteries to address the safety concerns due to Li dendrite growth and internal short circuiting. However, low ionic conductivity due to high grain boundary resistance in ceramics and semi-crystalline nature of polymers has held back the solid electrolytes from being used in Li-ion batteries. Polyethylene oxide (PEO), complexed with a Li-salt, is a well-studied polymer electrolyte showing ionic conductivity properties at room temperature. However, the coexistence of amorphous and crystalline regions at room temperature (< Tm, the melting temperature) has

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Enabling 3d Printing Technologies For Artificial Compound Eye System And Penetrating Neural Probes, Boshen Zhang

Wayne State University Dissertations

3D printing has become a useful and transformative method and has applications in many different fields, including organ printing, aerospace applications, and medical devices. With higher resolution, faster production speed, and more design flexibility, 3D printing technologies can lead to more novel devices and systems. In this research, two new techniques have been developed to enable 3D printing technologies for artificial compound eye system and penetrating glassy carbon neural electrode array.

This work focuses on developing new applications based on the SLA 3D printing process, which uses the liquid resin to create a solid 3D structure. The limitation of SLA …

Seed-Mediated Crystallization Of Charge-Transfer Complexes And Their Applications For Gas Sensing, Xuecheng Yu

Wayne State University Dissertations

The dissertation focused on controllable seed-mediated nucleaton of charge transfer complex, namely tetrathiafulvalene bromide ((TTF)Br) and Krogmann’s salts (KCP), and their applications in sensing. On gold nanoparticle (AuNP) decorated highly oriented pyrolytic graphite (HOPG) substrate, the presence of AuNP promotes the formation of charge transfer salt nanowires. The size of these nanowires, both (TTF)Br and KCP, were found to be confined by the size of AuNPs, shown by SEM and AFM characterization. On micro-disk electrodes, charge transfer salt nanowires were found to own a linear time dependency, by both SEM and in-situ optical microscopy. The micro-disk electrodes promoted higher crystallization …

Advanced Electrodes And Electrolytes For Long-Lived And High-Performance Lithium-Sulfur Batteries, Deepesh Gopalakrishnan

Wayne State University Dissertations

ABSTRACT

ADVANCED ELECTRODES AND ELECTROLYTES FOR LONG-LIVED AND HIGH-PERFORMANCE LITHIUM-SULFUR BATTERIES

by

DEEPESH GOPALAKRISHNAN

August 2020

Advisor: Dr. Leela Mohana Reddy Arava

Major: Mechanical Engineering

Degree: Doctor of Philosophy

Lithium – Sulfur (Li-S) batteries have received much attention and considered as a promising candidate for next generation energy storage devices because of their high theoretical energy density (≈2600 Wh kg‒1) and environmental friendliness. However, the uncontrollable growth of lithium dendrites in the lithium metal anode and the fatal effect of polysulfide shuttle hinder their practical applications. The formation of dendrites during repeated Li plating/stripping processes results in: reduced Li availability …