Process Control and Systems Commons^™

Response Of Dynamic Processes With Control Implemented On A Noisy Quantum Computer, Shilpa Narashimhan, Dominic Messina, Henrique Oyama, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

A major challenge to determining the applicability (and potential outperformance over classical computers) of a quantum computer (QC) within chemical manufacturing processes is quantum noise. Computations by a QC are error-prone due to the influence of quantum noise inherent to the hardware. Errors in control inputs may destabilize a chemical process and lead to unsafe conditions for manufacturing personnel and the environment. The response of a process with control implemented on a QC to errors due to noise must be investigated thoroughly. In this work, the impacts of control input errors due to quantum noise on a process are modeled …

Heuristic Strategies For Process Stabilization Using Proportional Control Implemented By A Noisy Quantum Simulator, Keshav Kasturi Rangan, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Processing and storage demands of industrial processes are causing fields such as optimization, scheduling, and control to assess the effectiveness of quantum devices in their applications. A key objective of control systems is to ensure process safety. This paper focuses on the potential of quantum devices to compute control inputs that maintain system safety despite sources of nondeterminism inherent to currently available quantum devices (quantum noise). In our previous work, we employed a quantum simulator to assess whether a quantum implementation of a proportional (P) control law could stabilize a single-input/single-output system under quantum noise approximated from a real quantum …

Virtual Test Beds For Image-Based Control Simulations Using Blender, Akkarakaran Francis Leonard, Govanni Gjonaj, Minhazur Rahman, Helen E. Durand

Chemical Engineering and Materials Science Faculty Research Publications

Process systems engineering research often utilizes virtual testbeds consisting of physics- based process models. As machine learning and image processing become more relevant sensing frameworks for control, it becomes important to address how process systems engineers can research the development of control and analysis frameworks that utilize images of physical processes. One method for achieving this is to develop experimental systems; another is to use software that integrates the visualization of systems, as well as modeling of the physics, such as three-dimensional graphics software. The prior work in our group analyzed image-based control for the small-scale example of level in …

Intelligent Decision Support System, Khurshid Salim Ugli Turayev

Chemical Technology, Control and Management

The article studies issues related to the development of intelligent systems located in an environment capable of perceiving this environment and acting autonomously to achieve assigned tasks. To create an intelligent process control system, it is necessary to monitor the mode to ensure high quality of finished products with minimal energy consumption at a given productivity of the entire complex. It is important to have a flow of input data to provide the system with operational information to support decision making.

The proposed intelligent control system makes it possible to analyze the results of production activities to make organizational and …

Computational Fluid Dynamics Modeling Of A Wafer Etch Temperature Control System, Henrique Oyama, Kip Nieman, Anh Tran, Bernard Keville, Yewei Wu, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Next-generation etching processes for semiconductor manufacturing exploit the potential of a variety of operating conditions, including cryogenic conditions at which high etch rates of silicon and very low etch rates of the photoresist are achieved. Thus, tight control of wafer temperature must be maintained. However, large and fast changes in the operating conditions make the wafer temperature control very challenging to be performed using typical etch cooling systems. The selection and evaluation of control tunings, material, and operating costs must be considered for next-generation etching processes under different operating strategies. These evaluations can be performed using digital twin environments (which …

Machine Learning Based Applications For Data Visualization, Modeling, Control, And Optimization For Chemical And Biological Systems, Yan Ma

LSU Doctoral Dissertations

This dissertation report covers Yan Ma’s Ph.D. research with applicational studies of machine learning in manufacturing and biological systems. The research work mainly focuses on reaction modeling, optimization, and control using a deep learning-based approaches, and the work mainly concentrates on deep reinforcement learning (DRL). Yan Ma’s research also involves with data mining with bioinformatics. Large-scale data obtained in RNA-seq is analyzed using non-linear dimensionality reduction with Principal Component Analysis (PCA), t-Distributed Stochastic Neighbor Embedding (t-SNE), and Uniform Manifold Approximation and Projection (UMAP), followed by clustering analysis using k-Means and Hierarchical Density-Based Spatial Clustering with Noise (HDBSCAN). This report focuses …

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 …

Lyapunov-Based Economic Model Predictive Control With Taylor Series State Approximations, Keshav Kasturi Rangan, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

A method for integrating optimization and control during on-line process operation is known as economic model predictive control (EMPC). EMPC optimizes a general cost function which reflects process economics subject to a model of the process. One formulation of EMPC which can maintain closed-loop stability in the presence of sufficiently small disturbances is Lyapunov-based EMPC (LEMPC). In this work, we make precise connections between closed-loop stability considerations under LEMPC and numerical approximations (via Taylor series) of the solution of the nonlinear dynamic model of the process used in the controller. A chemical process example is utilized to demonstrate the concepts …

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 …

Process/Equipment Design Implications For Control System Cybersecurity, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

An emerging challenge for process safety is process control system cybersecurity. An attacker could gain control of the process actuators through the control system or communication policies within control loops and potentially drive the process state to unsafe conditions. Cybersecurity has traditionally been handled as an information technology (IT) problem in the process industries. In the literature for cybersecurity specifically of control systems, there has been work aimed at developing control designs that seek to fight cyberattacks by either giving the system appropriate response mechanisms once attacks are detected or seeking to make the attacks difficult to perform. In this …

On Accounting For Equipment-Control Interactions In Economic Model Predictive Control Via Process State Constraints, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Traditionally, chemical processes have been operated at steady-state; however, recent work on economic model predictive control (EMPC) has indicated that some processes may be operated in a more economically-optimal fashion under a time-varying operating policy. It is unclear how time-varying operating policies may impact process equipment, which must be investigated for safety and profit reasons. It has traditionally been considered that constraints on process states can be added to EMPC design to prevent the controller from computing control actions which create problematic operating conditions for process equipment. However, no rigorous investigation has yet been performed to analyze whether, when a …

A Nonlinear Systems Framework For Cyberattack Prevention For Chemical Process Control Systems, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Recent cyberattacks against industrial control systems highlight the criticality of preventing future attacks from disrupting plants economically or, more critically, from impacting plant safety. This work develops a nonlinear systems framework for understanding cyberattack-resilience of process and control designs and indicates through an analysis of three control designs how control laws can be inspected for this property. A chemical process example illustrates that control approaches intended for cyberattack prevention which seem intuitive are not cyberattack-resilient unless they meet the requirements of a nonlinear systems description of this property.

Economic Model Predictive Control Design Via Nonlinear Model Identification, Laura Giuliani, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Increasing pushes toward next-generation/smart manufacturing motivate the development of economic model predictive control (EMPC) designs which can be practically deployed. For EMPC, the constraints, objective function, and accuracy of the state predictions would benefit from process models that describe the process physics. However, obtaining first- principles models of chemical process systems can be time-consuming or challenging such that it is preferable to develop physics-based process models automatically from process operating data. In this work, we take initial steps in this direction by suggesting that because experiments that are used to characterize first-principles models often target specific types of data, an …

State Measurement Spoofing Prevention Through Model Predictive Control Design, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Security of chemical process control systems against cyberattacks is critical due to the potential for injuries and loss of life when chemical process systems fail. A potential means by which process control systems may be attacked is through the manipulation of the measurements received by the controller. One approach for addressing this is to design controllers that make manipulating the measurements received by the controller in any meaningful fashion very difficult, making the controllers a less attractive target for a cyberattack of this type. In this work, we develop a model predictive control (MPC) implementation strategy that incorporates Lyapunov-based stability …

Cfd/Fea Of A Steam Methane Reforming Tube, Matthew Wegener

Research Opportunities for Engineering Undergraduates (ROEU) Program 2017-18

Steam methane reforming is the primary method by which hydrogen is produced; increased efficiency in hydrogen production could enable hydrogen’s usage as an alternative fuel. The objectives of this project are to construct a robust CFD/FEA model of a steam methane reforming tube, and to perform CFD/FEA analysis in both steady and transient operational states, comparing thermal stresses/strains in the tube wall in the two states and relating tube stresses/strains to properties of the process controller.

Process Control Laboratory Skid Refurbishment, Danny Crowder

Williams Honors College, Honors Research Projects

This project evaluates a salvaged process control skid for potential refurbishment and educational re-use. In-lab work evaluated the existing skid. Several process control elements have been recommended for replacement, including the process tank (due to corrosion), the pressure transmitter (operability/corrosion), the flow meters (mechanical) and the control system (age). The control valves, temperature elements and transmitters, pump, holding tanks, and the electrical heat exchanger should be salvaged. An I/P converter and pressure relief valve should be added to the pneumatic feed. Enclosing of all electrical components should be prioritized. An electrical schematic for a new control system should be implemented. …

Developing Process Control Experiments For Undergraduate Chemical Engineering Laboratories, Chase M. Swaffar

Graduate Theses and Dissertations

It is the intent of this work to develop a process control apparatus and series of experiments that will help students visualize the PID (Proportional-Integral-Derivative) control of a process and enhance their understanding of the subject. The apparatus is a computer-controlled PID mixing system that responds quickly to set point changes and process disturbances which are directly observable. The system can easily be simulated with a transfer function model in Matlab's Simulink, so that the controller can be optimized for the desired system response. Four experiments can be conducted with this system including: exploration of system modeling and controller optimization …