George T. Bereznai

Optimum approximation of high-order systems by low-order models†

A method has been proposed for the determination of optimum low-order models for a high-order system which minimize a specified error criterion for a given order of the model. The method is based on the pattern-search algorithm of Hooke and Jeeves. Starting from an approximate first or second-order model, an optimum model of that order is determined, and the process is continued with the order increasing progressively. As an example of the application of the method, optimum second-order models of a seventh-order system have been obtained using a number of different criteria for optimization. A third and a fourth-order optimum model have then been derived for a given criterion.

Adaptive Control of Nuclear Reactors Using a Digital Computer

An adaptive system for the control of the power level of a nuclear reactor is described. The controller has a square-law element of variable gain, optimum values for which have been obtained from off-line computations for certain power levels and parameter values. When conditions in the reactor deviate from those assumed for the off-line optimization, the gain factor is adapted on-line, such that the difference between actual and demanded power levels is minimized. An existing power reactor and associated control system have been simulated, as well as the proposed adaptive scheme. The results show that the adaptive controller gives improvements by at least an order of magnitude in the accuracy of following power demand changes, and at the same time reduces the necessary control effort. Since the scheme entails only a small number of arithmetic and logical operations and has limited memory requirements, it may be implemented on a conventional process computer, or built as a special purpose digital control system.

Adaptive Nuclear Reactor Control Based on Optimal Low-Order Linear Models

The problem of optimally controlling the power level changes of a nuclear reactor for a wide variety of cost functions is considered. Admissible performance indexes are arbitrary functions of the power level and its derivative as well as of the reactivity input and its derivative. The proposed method is based on the use of optimal second-order models, the parameters of which are computed on-line to produce piece-wise approximations to the response of the plant. While the controller parameters, which give optimal performance for the model, result in only a suboptimal system response, the deviations between the two converge rapidly to zero. The proposed technique is illustrated by computing the responses of a power reactor for integral quadratic cost functions, as well as for least pth and minimax criteria. The results indicate that near-optimal performance may be achieved under conditions encountered in practice.

Adaptive Nuclear Reactor Control for Integral Absolute Error and Minimax Criteria

Abstract Adaptive control of a nuclear power plant is considered for the case when it is required that the response to a change in the demanded power should be a close approximation to a ramp between the initial and final power levels. This is implemented by on-line identification of the parameters of an optimum second-order model for the system, followed by the computation of the feedback coefficients for optimum system response using either the integral absolute error or the minimax error criterion.

Nuclear education and manpower development

The successful applications of nuclear technology in areas as diverse as research, healthcare, nondestructive examinations, agriculture and electrical power generation are all dependent on the expert human resources available to the country or region utilising this technology. The expertise needed to understand and safely employ nuclear energy includes skilled craftsmen, operators, technicians and technologists, engineers and scientists, managers and executives. Nuclear technology is complex, has unique safety and resource requirements, and represents a significant financial investment. To embark on a nuclear power programme and to successfully manage it, the governing bodies of the locality where the nuclear installation is to be located, as well as the countrys government, must be active supporters of the related facilities. Furthermore, the countrys government must put in place a regulatory system that is independent of the designers, owners and operators of the nuclear facilities, as well as systems that meet such international agreements as the Nuclear Non-Proliferation Treaty. The paper reviews Canadian and other international experience in providing the education and training needed for a country or region to successfully initiate and maintain the expert human resources complement in order to benefit from the peaceful uses of nuclear technology.

Educating the Next Generation of Energy Professionals

Energy is a strategic focus area for research and education at University of Ontario Institute of Technology (UOIT). In the area of energy engineering and science, innovative programs are offered in energy systems engineering, nuclear engineering, energy engineering (an option in mechanical engineering), and energy and the environment (an option in physics). The academic highlights of the programs are presented.

Adaptive control of large-scale nonlinear systems using optimal low-order models

The problem of adaptive control of high-order nonlinear time-varying systems is solved by using low-order linear models to approximate, in a piece-wise optimal manner, the response of the system. Extensive use is made of recent, highly efficient gradient search technique. The theory is illustrated by an application to a nuclear power reactor.