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Supervisory-level control system demand control of an HVAC system
A supervisory-level control system is provided and includes a summation unit receptive of first and second signals, an HVAC system to generate the second signal according to first set-point signals and to a second set-point signal and a supervisory controller. The supervisory controller includes a control unit, a set-point scheduler and a zone level set-point distribution unit. The control unit is receptive of an error signal representing a difference between the first and second signals from the summation unit. The set-point scheduler is receptive of a demand signal generated by the control unit according to the error signal. The set-point scheduler generates a set-point command signal and the second set-point signal according to the demand signal. The zone level set-point distribution unit is configured to generate the first set-point signals in accordance with the set-point command signal.
Analysis and improvement of input channel selection algorithm for reliability of control systems in nuclear power plants - 138
In most of non-safety NSSS (Nuclear Steam Supply System) control systems, a process input is composed of two channels for redundancy. In a normal situation, the average of both input channels is used in the control algorithm. If a failed channel is detected, the 'channel selection algorithm' chooses the remaining normal input channel. For a bumpless transition, many implemented control systems include the 'ramping rate' function, which makes it possible for the selected input to slowly approach the new input channel. However, it recently turned out that this function adopted for positive effects may result in unintended consequences for the related control system and the plant in certain cases. Due to a process transient in the plant according to a significant event, any related sensor input signal can rapidly change and finally exceed the pre-defined range for detecting an out-of-range event in a short time. During the process of channel conversion due to a rapid transient in the plant, the processed input from the redundant channels can be distorted if the ramping rate function is not properly implemented. As a result, it can result in a plant shutdown because the control system fails to perform the critical function to mitigate a plant transient. To solve these potential problems, we analyzed the overall causes and derived a proposed algorithm for improving reliability and performance of the control systems. (authors)
Microreactor Automated Control System - Digital Twin Models and Advanced Control Systems Updates
Automation of control systems is expected to be important in the economic and safe operation of microreactors. Therefore, there is a need to develop and demonstrate automated control for microreactors, along with the development of testbeds for this purpose. This report provides updates on the status of a nonnuclear microreactor automated control system (MACS)—a real-time, hardware-in-the-loop testbed for non-nuclear testing of microreactor control system automation. A real-time hardware-in-the-loop testbed incorporates the realistic dynamics of physical systems into control system development and testing. The collaborative effort between Oak Ridge National Laboratory (ORNL) and Idaho National Laboratory (INL) resulted in the development of a prototypic microreactor plant-level digital twin that includes the reactor and a balance of plant system. Advanced control strategies were incorporated to demonstrate testing of control automation solutions. The gRPC communication protocol, which was implemented in the hardware-in-the-loop testbed by INL, was coupled to a digital twin model developed using the TRANsient Simulation Framework of Reconfigurable Models (TRANSFORM) library in Modelica. This digital twin simulation was tested with the ViBRANT hardware for realistic feedback and visual representation of control action in real time. A modular Python client structure was developed to manage functional mock-up unit-based simulation and real-time gRPC communication. Hardware-in-the-loop testing indicated that the modeled reactor—a natural-convection, molten-salt coolant loop configuration—responds well to control of drum positioning for modulation of reactor core power, as well as system-level control and downstream demand changes. Ongoing research is focused on integrating additional control algorithms that utilize data from newly included sensors within the MACS hardware testbed, as well as demonstrating and assessing the performance of the different automated control algorithms on multiple additional operational scenarios.
Resilient Hierarchical Networked Control Systems: Secure Controls for Critical Locations and at Edge
Integration of information and communication technology (ICT) offers new opportunities in improving the management and operation of critical infrastructures such as power systems as it allows connection of different sensors and control components via a communication network, leading to the so-called networked control systems (NCS). However, the use of open and pervasive ICT such as the Internet or wireless communication technologies comes at a price of making NCS vulnerable to cyber intrusions/attacks which may cause physical damage. Here, this chapter presents control algorithms to ensure resilient and safe operation of NCS under unknown cyberattacks. Specifically, a variant of dynamic watermarking strategies is presented by embedding encoding/decoding components of chaotic signals into the NCS for secure control for critical locations where the measurement/control signals are transmitted to/from the control center via a communication network. In addition, resilient cooperative control algorithms are discussed to ensure safe operation at edge of the NCS which consists of a large number of distributed controllable devices. Several numerical examples are provided to illustrate the proposed control strategies.
Electricity Distribution System Resilient Control System Metrics
In order to assess the resilience of a system, a set of measures must be defined. Varying control architecture while considering such a system of metrics targeted at resilience can determine the relative merit of the architectures with respect to the resilience of the system. Traditionally, electricity distribution is concerned with delivery of power from transmission or sub transmission to consumer loads with basic control of tap changing transformers and capacitor banks to regulate delivered voltage and provide reactive power support, respectively. In the near future, modern distribution systems architecture are anticipated to include substantially more controllable assets enabling more complicated control architectures to optimized based on reliability and economics. This paper reports on the definition of resilience metrics developed for modern distribution systems for delivery of electricity. Specifically, the metrics are focused on adaptive capacity related to the scale for which the system is able to resist, respond, recover and restore after disturbances in real or reactive power and time requirements to respond and restore the system to a complete normalcy.
Designing an Intrusion Detection for an Adjustable Speed Drive System Controlling a Critical Process
In this article, we address the cyber-security problem of industrial control systems (ICSs) when their sensor measurements may be compromised due to an attacker who has intercepted those measurements via a network. We introduce a general-purpose method “Dynamic Watermarking (DW)” to detect potential cyber-intrusions on speed sensor measurements within industrial control systems, which deploy an adjustable speed drive (ASD) to control a critical process. The DW method is injecting a random private low-amplitude signal with a zero mean Gaussian distribution, “watermark”, into one of the input phase voltages powering the ASD system. The watermark signal propagates through the system including pulse width modulation (PWM) power conversion stage and motor, then ultimately appears in the speed sensor measurements. By deploying two statistical DW tests with two proper thresholds, the system can detect potential cyber-intrusions or unobservable cyber-attacks such as replay attacks and false data injection attacks (FDIA). The DW method tested on a laboratory-scale ASD system experimentally to protect the system against cyber-intrusions. This system, powered by a commercial PWM drive operating at 208 V, 3-phase, and 3.7 kW, served as our experimental platform.
Resonance Control System for the CEBAF Separator Upgrade
Abstract The Continuous Electron Beam Accelerator Facility (CEBAF) energy upgrade from 6 GeV to 12 GeV includes the installation of four new 748.5 MHz normal conducting deflecting cavities in the 5th pass extraction region. The RF system employs two digital LLRF systems controlling four normal conducting cavities in a vector sum setting. Cavity tune information of the individual cavities is obtained using a multiplexing scheme of the forward and reflected RF signals. Water skids equipped with heaters and valves are used to control resonance. A new FPGA-based hardware and EPICS-based predictive control algorithm has been developed to support reliable operation of the beam extraction process. This paper presents the architecture design of the existing hardware and software as well as a plan to develop a model predictive control system.
Feature Classification for Control System Devices
Control systems are used to automate industrial processes, smart grids, and smart cities. Unfortunately, cyber attacks on control systems are on the rise. Additionally, control systems lack the plethora of tools available for commodity systems for forensic investigation. An important step towards the proper forensic investigation is to analyze device memory. To assist in identifying features of device memory, we present a machine learning-based technique that integrates ontology information for feature classification in a control system device’s memory.
Easing the Control System Application Development for CMS Detector Control System with Automatic Production Environment Reproduction
The Detector Control System (DCS) is one of the main pieces involved in the operation of the Compact Muon Solenoid (CMS) experiment at the LHC. The system is built using WinCC Open Architecture (WinCC OA) and the Joint Controls Project (JCOP) framework which was developed on top of WinCC at CERN. Following the JCOP paradigm, CMS has developed its own framework which is structured as a collection of more than 200 individual installable components each providing a different feature. Everyone of the systems that the CMS DCS consists of is created by installing a different set of these components. By automating this process, we are able to quickly and efficiently create new systems in production or recreate problematic ones, but also, to create development environments that are identical to the production ones. This latter one results in smoother development and integration processes, as the new/reworked components are developed and tested in production-like environments. Moreover, it allows the central DCS support team to easily reproduce systems that the users/developers report as being problematic, reducing the response time for bug fixing and improving the support quality.
Modern control system applications at Fermilab with Dart and Flutter
The control system at Fermilab is undergoing an unprecedented modernization effort. Hundreds of legacy applications originally developed with technology from the early nineties will be replaced with a suite of modern web applications. The selection of an user interface framework is a key technology decision that will impact on all the applications developed over the next decade. The Controls department at Fermilab has decided to use Google’s Dart language and Flutter framework for future application development. In this paper we will discuss the decision process that selected Dart/Flutter and the development of early general purpose control system applications with the framework.
Embedded Hardware Solution for Cybersecurity in Industrial Control Systems
Industrial Control Systems are the backbone of manufacturing, power, and critical infrastructure. These systems are made up of electronic and mechanical devices that operate on complex feedback systems that allow the production of consumer products, electricity, clean water, and nuclear industries. This broad reach of cybersecurity has earned it a place in the strategic roadmaps for many government agencies, including the Department of Energy. Their efforts stem from two general initiatives which are to improve cybersecurity in the energy sector and to strengthen effectiveness of Department of Energy incident management capabilities. Particular emphasis is in improving learning and preservations of knowledge at the labs, and to encourage collaboration between the labs. This project aims to develop Savannah River National Laboratory’s knowledge of industrial control systems cybersecurity by providing our engineers the opportunity to learn and execute advanced concepts in cybersecurity to real problems in industrial control systems. Successful execution of this project will enhance Savannah River National Laboratory’s knowledge and capability in the realm of Industrial Control System and Operational Technology cybersecurity as well as advance understanding of defensive needs in these environments. This will directly impact Savannah River National Laboratory’s capability to contribute and collaborate with Department of Energy, other Labs, and commercial partners in meeting Department of Energy national industrial control systems/Operations Technology cybersecurity goals.
Case studies on design, simulation and visualization of control and measurement applications using REX control system
REX Control System is a professional advanced tool for design and implementation of complex control systems that belongs to softPLC category. It covers the entire process starting from simulation of functionality of the application before deployment, through implementation on real-time target, towards analysis, diagnostics and visualization. Basically it consists of two parts: the development tools and the runtime system. It is also compatible with Simulink environment, and the way of implementation of control algorithm is very similar. The control scheme is finally compiled (using RexDraw utility) and uploaded into a chosen real-time target (using RexView utility). There is a wide variety of hardware platforms and real-time operating systems supported by REX Control System such as for example Windows Embedded, Linux, Linux/Xenomai deployed on SBC, IPC, PAC, Raspberry Pi and others with many I/O interfaces. It is modern system designed both for measurement and control applications, offering a lot of additional functions concerning data archiving, visualization based on HTML5, and communication standards. The paper will sum up possibilities of its use in educational process, focused on control of case studies of physical models with classical and advanced control algorithms.
Automated point mapping for building control systems: Recent advances and future research needs
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Upgrading Fermilab’s accelerator control system with ACORN
The Fermilab Accelerator Complex is the largest national user facility in the Office of High Energy Physics (DOE/HEP) program and the only national user facility operating at Fermilab. Fermilab serves as the host to the Long Baseline Neutrino Facility/Deep Underground Neutrino Experiment (LBNF/DUNE), the laboratory’s flagship project for neutrino science that is under construction. LBNF/DUNE will be powered by megawatt beams from an upgraded accelerator, the Proton Improvement Plan II (PIP-II) that will replace the laboratory’s aging linear accelerator with a new one based on superconducting radio-frequency cavities. The Accelerator Controls Operations Research Network (ACORN) Project will support LBNF/DUNE and PIP-II by modernizing the accelerator control system. The project is at the conceptual design phase and looking to achieve Critical Decision 1 (CD-1) later this year. The scope and structure of the project will be presented, along with an overview of how that has changed in the past year. Current design and technology choices will be shared. Specific challenges facing the project will be addressed, along with current thinking on solutions.
Balance of Plant Modeling and Real-Time Hardware-in-the-Loop Integration with the Microreactor Automated Control System
The advent of novel microreactor technology has driven a focused effort to explore safety and efficiency improvements that can be achieved through the use of automated system control. Development of control strategies, especially for initial demonstration, requires an adequate surrogate environment to safely research failure modes and control integration with realistic hardware delay. However, efficiency gains from control strategies are improved when the scope of controller action is expanded to include system-level dynamics such as downstream heat extraction and mass flow. For this reason, a balance-of-plant (BOP) model of a representative microreactor system has been developed using the TRANsient Simulation Framework of Reconfigurable Models library in Modelica. This model captures a reactor and primary NaK coolant loop that represent corresponding system components of the Microreactor Applications Research Validation and EvaLuation (MARVEL) design as well as a secondary coolant loop and heat extraction representative of the Microreactor Agile Non-Nuclear Experimental Test Bed (MAGNET). This model configuration allows for hardware-in-the-loop (HIL) integration with microreactor automated control system (MACS) hardware in real time through a Python-based gRPC client. Real-time simulation of model performance with emulated hardware and communication delay suggests that under independent proportional-integral-derivative control of BOP model drum dynamics and downstream heat extraction, stable power load following is achievable. A slight delay in load following, filtering of high-frequency dynamics, and localized temperature fluctation suggest room for improvement through the development of higher-level control strategies. The simulated coupling of the MAGNET facility lays the groundwork for future digital twin analysis with a coupled MACS-MAGNET HIL demonstration.
Evaluate data lake design for the accelerator control system
Increasing precision in automation for modern particle accelerators not only creates a requirement to gather data from all devices but also demands scalable and high-performance data infrastructure with the capability of handling vast incoming device data. A well architected data lake is suitable for such a system which integrates real-time data acquisition, transient data caching, and long-term storage. This paper evaluates data lake architecture for an Accelerator Control System (ACS), focusing on two critical components of a data lake, data cache and long-term storage.
Modernization Plans for Fermilab’s Accelerator Control System
The control system, ACNET, for Fermilab’s accelerator complex has enabled the lab’s scientific mission for decades. ACNET has evolved over the years to incorporate new technologies. However, as Fermilab prepares to enter a new era with its PIP-II superconducting linear accelerator, ACNET is at a crossroads. There are several components that are either obsolete or outdated, or certainly will be over the long lifetime of PIP-II. We have begun a plan to modernize our accelerator control system. This paper discusses some of the obsolete hardware and software that needs to be replaced, and lays out options and technologies that we might adopt as part of this modernization effort.