David Fugate

A mathematical framework for the analysis of cyber-resilient control systems

The increasingly recognized vulnerability of industrial control systems to cyber-attacks has inspired a considerable amount of research into techniques for cyber-resilient control systems. The majority of this effort involves the application of well known information security techniques to protect system networks. These techniques are primarily concerned with the prevention of unauthorized access and the protection of data integrity. While these efforts are important to protect the control systems that operate critical infrastructure, they are never perfectly effective thus motivating a need to develop control systems that will operate successfully during a cyber attack. Little research has focused on the design of control systems with closed-loop dynamics that are resilient to cyber-attack. An understanding of the types of modifications to the system and signals that could be employed by an attacker after they have gained access to the control system and the effects of these attacks on the behavior of the control systems can guide efforts to develop attack detection and mitigation strategies. To formulate this problem, consistent mathematical definitions of concepts within resilient control need to be established to enable a mathematical analysis of the vulnerabilities and resiliencies of a particular control system design methodology and architecture. In this paper, we propose rigorous definitions for state awareness, operational normalcy, and resiliency as they relate to realtime control systems. We will also discuss some mathematical consequences that arise from the proposed definitions. The goal is to begin to develop a mathematical framework and testable conditions for resiliency that can be used to build a sound theoretical foundation for resilient control research.

Cost-effective retrofit technology for reducing peak power demand in small and medium commercial buildings

This article describes a cost-effective retrofit technology that uses collective control of multiple rooftop air-conditioning units to reduce the peak power consumption of small and medium commercial buildings. The proposed control uses a model of the building and air-conditioning units to select an operating schedule for the air-conditioning units that maintains a temperature set-point subject to a constraint on the number of units that may operate simultaneously. A prototype of this new control system was built and deployed in a large gymnasium to coordinate four rooftop air-conditioning units. Based on data collected while operating this prototype, it is estimated that the cost savings achieved by reducing peak power consumption is sufficient to repay the cost of the prototype within a year.

Advanced instrumentation for extreme environments

Oak Ridge National Laboratory (ORNL) is investigating embedded instrumentation and controls (I&C) technology for next generation nuclear power generation applications. Embedded systems encompass a wide range of configurations and technologies; we define embedding in this instance as the integration of the sensors and the control system design into the component design using a systems engineering process. Embedded I&C systems are often an essential part of developing new capabilities, improving reliability, enhancing performance, and reducing operational costs. The next generation reactor technologies with passive safety features will benefit from the development and application of new I&C technologies. Some of these new designs raise extreme environmental challenges such as high temperatures (over 1,400 °C) and material compatibility (e.g., molten salts).

Non-Intrusive Energy Disaggregation Using Non-Negative Matrix Factorization With Sum-to-k Constraint

Energy disaggregation or non-intrusive load monitoring addresses the issue of extracting device-level energy consumption information by monitoring the aggregated signal at one single measurement point without installing meters on each individual device. Energy disaggregation can be formulated as a source separation problem, where the aggregated signal is expressed as linear combination of basis vectors in a matrix factorization framework. In this paper, an approach based on Sum-to-k constrained non-negative matrix factorization (S2K-NMF) is proposed. By imposing the sum-to-k constraint and the non-negative constraint, S2K-NMF is able to effectively extract perceptually meaningful sources from complex mixtures. The strength of the proposed algorithm is demonstrated through two sets of experiments: Energy disaggregation in a residential smart home; and heating, ventilating, and air conditioning components energy monitoring in an industrial building testbed maintained at the Oak Ridge National Laboratory. Extensive experimental results demonstrate the superior performance of S2K-NMF as compared to state-of-the-art decomposition-based disaggregation algorithms.

Minimum state awareness for resilient control systems under cyber-attack

State awareness for a control system is the accurate knowledge of the internal states of the system realization. By definition, a cyber-attacker decreases the state awareness by modifying or removing the information available to the operator and control system. By decreasing state awareness, the attacker can directly cause damage to the physical system through the control system, or indirectly by causing the operator to react in a damaging manner to the false information. One of the central problems of resilient control is developing methods to retain the minimal state awareness necessary to continue stable operation during a cyber-attack. The characterization of the necessary minimal state awareness is currently an unanswered question. In this paper, we will define state awareness, discuss the consequences of loss of state awareness, and some potential research directions for maintaining state awareness.

Non-intrusive load monitoring of HVAC components using signal unmixing

Heating, Ventilating and Air Conditioning units (HVAC) are a major electrical energy consumer in buildings. Monitoring of the operation and energy consumption of HVAC would increase the awareness of building owners and maintenance service providers of the condition and quality of performance of these units, enabling conditioned-based maintenance which would help achieving high efficiency in energy consumption. In this paper, a novel non-intrusive method based on constrained non-negative matrix factorization is proposed for monitoring the different components of HVAC unit by only having access to the whole building aggregated power signal. At the first level of this hierarchical approach, power consumption of the building is decomposed to energy consumption of the HVAC unit and all the other electrical devices operating in the building such as lighting and plug loads. Then, the estimated power signal of the HVAC is used to estimate the power consumption profile of the HVAC major electrical loads such as compressors, condenser fans and indoor blower. Experiments conducted on real data collected from a building testbed maintained at the Oak Ridge National Laboratory (ORNL) demonstrate high accuracy on disaggregation task.

Embedded Sensors and Controls to Improve Component Performance and Reliability Conceptual Design Report

The overall project objective is to demonstrate improved reliability and increased performance made possible by deeply embedding instrumentation and controls (IC adequate performance was obtained through over-design. This report describes the progress and status of the project and provides a conceptual design overview for the embedded I&C pump.

Development of an Automated Decision-Making Tool for Supervisory Control System

This technical report was generated as a product of the Supervisory Control for Multi-Modular Small Modular Reactor (SMR) Plants project within the Instrumentation, Control and Human-Machine Interface technology area under the Advanced Small Modular Reactor (AdvSMR) Research and Development Program of the US Department of Energy. The report documents the definition of strategies, functional elements, and the structural architecture of a supervisory control system for multi-modular AdvSMR plants. This research activity advances the state of the art by incorporating real-time, probabilistic-based decision-making into the supervisory control system architectural layers through the introduction of a tiered-plant system approach. The report provides background information on the state of the art of automated decision-making, including the description of existing methodologies. It then presents a description of a generalized decision-making framework, upon which the supervisory control decision-making algorithm is based. The probabilistic portion of automated decision-making is demonstrated through a simple hydraulic loop example.

Optimizing investments in cyber-security for critical infrastructure

Investments in the cyber-security of critical infrastructure must balance preventing intrusion, detecting a cyber-attack, and mitigating the attackers physical effects on computer controlled equipment. For this purpose, we outline a method for making optimal investment decisions that balance these three aspects of a cyber-defense. The proposed method accounts for the physical process that is being controlled and the relative cost and performance of technologies for prevention, detection, and mitigation. We illustrate the proposed method with a model of a chiller that is based on the supercomputer chillers at Oak Ridge National Laboratory. This model is used to select security capabilities that yields the greatest protection for a fixed budget.

Update on Small Modular Reactors Dynamic System Modeling Tool: Web Application

Previous reports focused on the development of component and system models as well as end-to-end system models using Modelica and Dymola for two advanced reactor architectures: (1) Advanced Liquid Metal Reactor and (2) fluoride high-temperature reactor (FHR). The focus of this report is the release of the first beta version of the web-based application for model use and collaboration, as well as an update on the FHR model. The web-based application allows novice users to configure end-to-end system models from preconfigured choices to investigate the instrumentation and controls implications of these designs and allows for the collaborative development of individual component models that can be benchmarked against test systems for potential inclusion in the model library. A description of this application is provided along with examples of its use and a listing and discussion of all the models that currently exist in the library.