Roger A. Kisner

Hierarchical fuzzy control

Abstract In a conventional rule based fuzzy control system, the rules are of the following form: if (condition) then (action), and all rules are essentially in a random order. The number of rules increases exponentially as the number of the system variables, on which the fuzzy rules are based, is increased. In this paper, the rules are structured in a hierarchical way so that the total number of rules will be a linear function of the system variables. The hierarchical fuzzy control algorithm developed in this paper is applied to control the feedwater flow to a steam generator of a power plant. The simulation results show that the hierarchical fuzzy controller yields superior performance over the conventional PID controller.

Advanced automation concepts for large-scale systems

An automatic control system for large-scale systems that integrates methods in artificial intelligence, signal processing, and nonlinear control to provide fast and efficient diagnostics and reliable control is presented. The integrated system reduces the procedural load and facilitates the operator tasks by creating a condensed representation of plant status. Operator tasks are emulated by building computer-based algorithms which validate sensor signals, strategies, commands, and performance tracking and which generate reliable decisions and control actions. The advanced concepts on which the system is based are discussed. Also discussed are fault tolerance, signal and command validation, nonlinear control, and the system executive module. An application of the integrated control system to the Experimental Breeder Reactor-II (EBR-II) is described. The simulation results show that the advanced concepts yield efficient control strategies, including reactor control during startup.<<ETX>>

An axial xenon oscillation model

Abstract A two-point xenon oscillation model was developed for PWRs. The model employs the nonlinear xenon and iodine balance equations and the one group, one-dimensional neutron diffusion equation having nonlinear power reactivity feedback. A two-term spatial harmonic series solution was assumed for the flux, xenon and iodine distributions. The system was made as close to critical as possible with the assumed distributions using a variational principle. The xenon and iodine concentrations were then obtained from their governing differential equations. The input/output nature of the model makes it ideal for simulation of xenon-induced reactor transients. A comparison of the simulated plant to actual plant data was made. The period of oscillation, stability index and flux amplitude of the simulated plant were all found to match the actual plant data with less than 10% error.

In-process detection of weld defects using laser-based ultrasound

Laser-based ultrasonic (LBU) measurement shows great promise for on-line monitoring of weld quality in tailor-welded blanks. Tailor-welded blanks are steel blanks made from plates of differing thicknesses and/or properties butt- welded together, they are used in automobile manufacturing to produce body, frame, and closure panels. LBU uses a pulsed laser to generate the ultrasound and a continuous wave laser interferometer to detect the ultrasound at the point of interrogation to perform ultrasonic inspection. LBU enables in-process measurements since there is no sensor contact or near-contact with the workpiece.

Cybersecurity through Real-Time Distributed Control Systems

Critical infrastructure sites and facilities are becoming increasingly dependent on interconnected physical and cyber-based real-time distributed control systems (RTDCSs). A mounting cybersecurity threat results from the nature of these ubiquitous and sometimes unrestrained communications interconnections. Much work is under way in numerous organizations to characterize the cyber threat, determine means to minimize risk, and develop mitigation strategies to address potential consequences. While it seems natural that a simple application of cyber-protection methods derived from corporate business information technology (IT) domain would lead to an acceptable solution, the reality is that the characteristics of RTDCSs make many of those methods inadequate and unsatisfactory or even harmful. A solution lies in developing a defense-in-depth approach that ranges from protection at communications interconnect levels ultimately to the control system s functional characteristics that are designed to maintain control in the face of malicious intrusion. This paper summarizes the nature of RTDCSs from a cybersecurity perspec tive and discusses issues, vulnerabilities, candidate mitigation approaches, and metrics.

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.

Expert system driven fuzzy control application to power reactors

The authors describe a fuzzy logic application to nuclear reactor control, namely, the automated start-up control of the Experimental Breeder Reactor-II. A rule-based expert system supervises the fuzzy controller (which also uses a rule-based representation). The overall system successfully emulates the behavior of the actual power plant operator. The operator control strategy is based on linguistic statements which translate into fuzzy productions describing heuristic control rules. The developed methodology is verified through computer simulations using a valid nonlinear model of the reactor. The necessary heuristic decisions, which are vitally important for the implementation of fuzzy control in the actual plant, were identified.<<ETX>>

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).

The effect of high magnetic field on phase stability in Fe-Ni

Identically prepared samples of Fe0.85Ni0.15 were annealed either in the ambient magnetic field or in a field of 29 T. Room temperature x-ray powder diffraction measurements that were performed after magnetic annealing showed that the ratio of the volume of the γ to α phase is decreased in the field-annealed sample by a factor of 2. First-principles calculations of the magnetic structure in the presence of a magnetic field are used to compute the resulting change in free energy. Analysis in terms of the phase diagram calculated with and without a magnetic field is in substantial agreement with the measurements.Identically prepared samples of Fe0.85Ni0.15 were annealed either in the ambient magnetic field or in a field of 29 T. Room temperature x-ray powder diffraction measurements that were performed after magnetic annealing showed that the ratio of the volume of the γ to α phase is decreased in the field-annealed sample by a factor of 2. First-principles calculations of the magnetic structure in the presence of a magnetic field are used to compute the resulting change in free energy. Analysis in terms of the phase diagram calculated with and without a magnetic field is in substantial agreement with the measurements.

Parameter identification for spatial xenon transient analysis and control

Abstract The real-time, on-line control of xenon-induced spatial flux oscillations in a large PWR requires the use of fairly simple models of the process for minicomputer implementation. Model simplification requires that the analyst reduce the physical phenomena to mathematical terms with coarser approximations and greater inaccuracies. In order to make a models behavior fit that of a reactor as closely as possible, the estimation of parameters in the model requires special care. Three parameters were chosen for identification: the diffusion coefficient, D; the power reactivity coefficient, αF; and the microscopic 135Xe cross section, σx. The method of maximum likelihood was used to obtain estimates of these parameters by comparing calculated results with actual plant data. Numerical values of these parameters are presented.