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For a linear control system in the Hessenberg form, we obtain new sufficient conditions for Lyapunov reducibility to a system in the Frobenius canonical form, for uniform global attainability, and for global Lyapunov reducibility.
Fermilab is undergoing the most ambitious upgrade to its accelerator control system of the 21st century. As part of the ACORN project, hundreds of legacy control system applications written in C/C++ will be re-imagined and developed from the ground up. In addition, applications to support Fermilab’s new super-conducting linear accelerator are already under construction. To manage the development of modern controls applications, the Controls department has adopted an Agile software development process based on eXtreme Programming. In this paper we will describe our process and detail our experience applying it to the development of two case studies.
The Experimental Physics Software and Computing Infrastructure (EPSCI) group at Jefferson Lab is leading the use of machine learning (ML) to enhance control systems in nuclear physics experiments. Collaborating closely with domain experts and data scientists, we have developed an ML-based control system that uses a Gaussian process to dynamically adjust the high voltage of the GlueX Central Drift Chamber. This results in stable detector performance by adapting to environmental changes, thereby reducing the offline calibration effort. Furthermore, we are developing ML-driven systems for optimizing the polarization of photon beams and polarized cryotargets. These systems will maintain the optimal microwave frequency in cryogenic targets and make real-time adjustments to diamond radiators for polarized photon sources, tasks traditionally handled by human operators. By automating these functions, we aim to optimize the polarization, reduce downtime, and minimize human error. This talk will highlight the development of reliable ML-based control systems and the policies to ensure they are both effective and trustworthy.
The Internet of Things (IoT) technology has dramatically improved the efficiency of today's building operation and management. By connecting controllable devices into a communication network, control signals can be easily passed to the devices, and operating status can be acquired from measurable ends with minimal effort. However, this all-connected configuration could also expose the network-based control system (NBCS) to malicious actions, such as cyberattacks. One of the common NBCSs is the building automation system. With the promotion of grid-interactive efficient buildings (GEBs), there has been increasing attention on securing the buildings from the network perspective. This research proposes a maximum-impact adversary design framework so that the adversary can provide the most adversarial impact on the controlled system while remaining stealthy. The proposed framework is numerically demonstrated on a network-based building energy and control system. The building energy system is built in a Modelica-based simulation environment and controlled by the state-of-the-art ASHRAE Guideline 36 control sequences. The control commands at the supervisory level, generated from the Guideline 36 controller, are assumed to be sent to local devices through communication networks using the BACnet protocol. Simulation results show that the proposed maximum-impact adversary on such a system can stealthily affect the building system's performance to its maximum extent. It is anticipated that results can be used by researchers and practitioners in the building automation industry to design efficient and robust cyber-attack detection algorithms, especially for stealthy attacks.
This presentation provides an overview of technical debt in the context of control systems for large-scale physics facilities. We explore various forms, common causes, and potential consequences on system reliability, maintainability, and extensibility. Drawing on experiences from multiple projects, including the ACORN control system modernization at Fermilab, we present a range of strategies for proactively managing technical debt, including best practices in design, development, testing, and documentation, as well as reactive approaches for identifying and mitigating existing issues.
A GDCI engine control system provides rapid heating of intake air to the combustion chamber when the engine is cold. The engine uses an intake air pathway that includes a compressor having a compressor inlet and a compressor outlet. A loop fluidly connects the compressor outlet to the compressor inlet. First and second valves are arranged in the loop and are arranged near the compressor outlet and the compressor inlet respectively. First and second passages converge at a first junction, and the first passage fluidly connects the first valve and the first junction. The second passage fluidly connects to the loop at a second junction arranged fluidly between the first and second valves. An intake air heat exchanger is arranged in the first passage and fluidly between the first valve and the first junction.
This report details the results of a survey conducted by Idaho National Laboratory (INL) to identify existing tools which could be used to prevent, detect, mitigate, or investigate a cyber-attack in an industrial control system (ICS) environment. This report compiles a list of potentially applicable tools and shows the coverage of the tools in an ICS architecture.
The Second Target Station (STS) Project will expand the capabilities of the existing Spallation Neutron Source (SNS), with a suite of neutron instruments optimized for long wavelengths. A new accelerator transport line will be built to deliver one out of four SNS pulses to the new target station. The Integrated Control Systems (ICS) will provide remote control, monitoring, OPI, alarms, and archivers for the accelerator systems, such as magnets power supply, vacuum devices, and beam instrumentation. The ICS will upgrade the existing Linac LLRF controls to allow independent operation of the FTS and STS and support different power levels of the FTS and STS proton beam. The ICS accelerator controls are in the phase of preliminary design for the control systems of magnet power supply, vacuum, LLRF, Timing, Machine protection system (MPS), and computing and machine network. The accelerator control systems build upon the existing SNS Machine Control systems, use the SNS standard hardware and EPICS software, and take full advantage of the performance gains delivered by the PPU Project at SNS.
GitOps is a foundational approach for modernizing infrastructure by leveraging Git as the single source of truth for declarative configurations. The poster explores how GitOps transforms traditional control system infrastructure, services and applications by enabling fully automated, auditable, and version-controlled infrastructure management. Cloud-native and containerized environments are shifting the ecosystem not only in the IT industry but also within the computational science field, as is the case of CERN and Diamond Light Source among other Accelerator/Science facilities which are slowly shifting towards modern software and infrastructure paradigms. The ACORN project, which aims to modernize Fermilab’s control system infrastructure and software is implementing proven best-practices and cutting-edge technology standards including GitOps, containerization, infrastructure as code and modern data pipelines for control system data acquisition and the inclusion of AI/ML in our accelerator complex.
This presentation provides a comprehensive overview of technical debt in the context of control systems for large-scale physics facilities. We will explore its various forms, common causes, and potential consequences on system reliability, maintainability, and upgradability. Drawing on experiences from multiple projects, we will present a range of strategies for proactively managing technical debt, including best practices in design, development, testing, and documentation, as well as reactive approaches for identifying and mitigating existing issues. The presentation will also emphasize the importance of a collaborative approach and the use of modern tools, like fault tracking systems, to ensure the long-term health and success of control systems in our field.
Fundamental solutions for improvement of the hydraulic section of the control system for the PJSC “Turboatom” K-300-240 turbine, which is equipped with a standard electronic part of the control system from JSC “Interavtomatika.” Results from tests and normal operation are presented.
We continue the study of statistically invariant and statistically weakly invariant sets with respect to controllable systems and differential inclusions launched by Prof. E. L. Tonkov. We examine properties of such statistical characteristics as the lower freq{sub *}(𝜑) and upper freq{sup *}(𝜑) relative frequencies of hitting a solution 𝜑(t) of a differential inclusion in a prescribed set. We obtain estimates and conditions of coincidence of these characteristics for functions whose difference tends to zero at infinity. We also present conditions of statistically weak invariance of a given set of a relatively controllable system.
A system and method are provided for operating a powertrain control system. The method includes receiving data measured from a plurality of sensors, the measured data relating to distance dependent speed values, and receiving information from one or more vehicle modules, the vehicle module information relating to distance independent speed values. The method further includes building a speed trajectory profile for a horizon window that includes a plurality of speed change regions represented by at least some distance dependent speed values or at least some distance independent speed values, and creating a synthesized speed profile for the horizon window by processing the speed trajectory profile. The synthesized speed profile optimizes efficiency of the powertrain control system at each of the plurality of speed change regions.
The Spallation Neutron Source at Oak Ridge National Laboratory is planning two major upgrades to the facility. The Proton Power Upgrade project, currently underway, will double the machine power from 1.4 to 2.8 MW by adding seven additional cryomodules and associated equipment. The Second Target Station project, currently in conceptual design, will construct a new target station effectively doubling the potential scientific output of the facility. This paper discusses the control system upgrades required to integrate these projects into the existing EPICS based control systems used for the machine and neutron instrument beamlines. While much of the control system can be replicated from existing solutions, some systems require new hardware and software. Operating two target stations simultaneously will require a new run permit system to safely manage beam delivery.
We examine the merit of Bernoulli packet drops in actively detecting integrity attacks on control systems. The aim is to detect an adversary who delivers fake sensor measurements to a system operator in order to conceal their effect on the plant. Physical watermarks, or noisy additive Gaussian inputs, have been previously used to detect several classes of integrity attacks in control systems. In this paper, we consider the analysis and design of Gaussian physical watermarks in the presence of packet drops at the control input. On one hand, this enables analysis in a more general network setting. On the other hand, we observe that in certain cases, Bernoulli packet drops can improve detection performance relative to a purely Gaussian watermark. This motivates the joint design of a Bernoulli-Gaussian watermark which incorporates both an additive Gaussian input and a Bernoulli drop process. We characterize the effect of such a watermark on system performance as well as attack detectability in two separate design scenarios. Here, we consider a correlation detector for attack recognition. We then propose efficiently solvable optimization problems to intelligently select parameters of the Gaussian input and the Bernoulli drop process while addressing security and performance trade-offs. Finally, we provide numerical results which illustrate that a watermark with packet drops can indeed outperform a Gaussian watermark.
Researchers at Sandia National Labs have developed a control system to improve damping of inter-area oscillations to improve power grid reliability. Current grids operate will below transmission capacity to avoid widespread outages due to inter-area oscillations. This control system is the first successful grid demonstration of feedback control making it a game changer for the smart grid.
In this article, a fault-tolerant tracking control strategy is investigated for nonlinear probability density function (PDF) control systems with the actuator fault, uncertainties, unknown disturbance, and random packet losses. The control input signal dropout and measurement signal dropouts are described as the independent Bernoulli distribution. An adaptive fault diagnosis (FD) observer based on the Lyapunov function is given to simultaneously estimate the fault, disturbance, and state with packet losses. Furthermore, different from the traditional robust fault-tolerant control (FTC), a new active fault-tolerant tracking controller is designed based on the model predictive control framework, which has better adaptive fault-tolerant performance. Finally, the validity of the proposed FTC method has been proved by a simulation study of a papermaking process.
The proposed supervisory control system (SCS) may provide considerable benefits to advanced small modular reactors, including reduced plant staffing, optimized maintenance activities, greater plant availability, and higher operating efficiency. The SCS makes risk-informed decisions based on (1) a probabilistic assessment of the likelihood of success given the status of the plant/systems and component health, and (2) a deterministic assessment between plant operating parameters and reactor protection parameters to prevent unnecessary trips and challenges to plant safety system—one measure of SCS success. The probabilistic portion of the decision-making engine of the SCS is based on the control actions associated with an advanced liquid-metal reactor (ALMR) Power Reactor, Innovative, Small Module (PRISM). Within the SCS, the probabilistic assessment provides a ranking of viable control actions; however, certain instructions generated by the probabilistic model only include an abstract notion of action without specifications. For instance, one instruction may be to reduce power without specifying how much reduction is needed. The prognostic/diagnostic models incorporate the health of components into the decision-making process. Once the control options are identified and ranked based on the likelihood of success, the SCS transmits the options to the deterministic portion of the platform. The performance-based system models assess and rank each of the probabilistically identified control actions by taking into account the physical behavior (current and projected) of the system. The performance-based decision making module receives inputs from the probabilistic decision-making module and the ERM module to generate a single solution. Interfaces to these modules are defined later in the section. A utility theory algorithm factors into the decision making by estimating the distance from and approach to a trip setpoint for each control option. If the magnitude of a negative utility value increases rapidly as the system approaches the trip setpoint, that option is not likely to be the preferred option. This can lead to a re-ranking of the control options. The SCS then transmits a control signal(s) to a component or system and informs the operator of actions taken based on the action chosen. The SCS successfully coupled probabilistic and performance-based system models to arrive at optimal control decisions based on the actual status of the plant and components. The automatic, autonomous, and real-time performance requirements for a control system were met by the SCS. The value of coupling probabilistic and performance-based system models was demonstrated by the re-ranking of control options based on the use of a utility algorithm. The use of ERM monitors provides added value to the SCS as demonstrated by the re-ranking of control options based on a components degraded state.