Requirements for automatic event analysis in substation automation systems

The project supported the Nuclear Regulatory Commission (NRC) in identifying and evaluating the regulatory implications concerning the control and protection systems proposed for use in the Department of Energy's (DOE) Next-Generation Nuclear Plant (NGNP). The NGNP, using modular high-temperature gas-cooled reactor (HTGR) technology, is to provide commercial industries with electricity and high-temperature process heat for industrial processes such as hydrogen production. Process heat temperatures range from 700 to 950 C, and for the upper range of these operation temperatures, the modular HTGR is sometimes referred to as the Very High Temperature Reactor or VHTR. Initial NGNP designs are for operation in the lower temperature range. The defining safety characteristic of the modular HTGR is that its primary defense against serious accidents is to be achieved through its inherent properties of the fuel and core. Because of its strong negative temperature coefficient of reactivity and the capability of the fuel to withstand high temperatures, fast-acting active safety systems or prompt operator actions should not be required to prevent significant fuel failure and fission product release. The plant is designed such that its inherent features should provide adequate protection despite operational errors or equipment failure. Figure 1 shows an example modular HTGR layout (prismatic core version), where its inlet coolant enters the reactor vessel at the bottom, traversing up the sides to the top plenum, down-flow through an annular core, and exiting from the lower plenum (hot duct). This research provided NRC staff with (a) insights and knowledge about the control and protection systems for the NGNP and VHTR, (b) information on the technologies/approaches under consideration for use in the reactor and process heat applications, (c) guidelines for the design of highly integrated control rooms, (d) consideration for modeling of control and protection system designs for VHTR, and (e) input for developing the bases for possible new regulatory guidance to assist in the review of an NGNP license application. This NRC project also evaluated reactor and process heat application plant simulation models employed in the protection and control system designs for various plant operational modes and accidents, including providing information about the models themselves, and the appropriateness of the application of the models for control and protection system studies. A companion project for the NRC focused on the potential for new instrumentation that would be unique to modular HTGRs, as compared to light-water reactors (LWRs), due to both the higher temperature ranges and the inherent safety features.

The problem of applying the various computational methods of mathematical programming in the design of an optimal control system is discussed. A general case of non-linear, non-autonomous, state equations, subject to inequality constraints on both state and control variables, is considered. Both continuous and discrete time systems are investigated. In case of discrete time systems, the sampling intervals are assumed generally unequal and aperiodic, with inequality constraints imposed upon them. Systems like these impose considerable computational difficulties when treated by the maximum principle or dynamie programming. Using mathematical programming, one may simplify a wide class of those computational problems. Several examples of applying mathematical programming to particular control problems are presented.

This chapter will summarise the fundamentals of protection and control systems design and consider the practical application with reference to the requirements of power network construction.Protection systems automatically detect and remove faults from the power system. Equally important are control systems which provide operational information and enable the manual and automatic operation and reconfiguration of the power system.

A sensitivity analysis for feedforward‐controlled finite domain systems is presented. Using an analytical approach, the sensitivity of a controlled system to variations in the design variables of the control inputs and the error sensors is obtained. Since the physical implementation of the control inputs and the error sensors is directly related to the modal control forces and the modal error sensor components, the analysis is performed in the modal domain. This modal domain analysis offers the advantage that the highest computational effort in obtaining the sensitivities is independent of the physical characteristics of the transducers. From the results in the modal domain, the sensitivities of the controlled system with respect to particular physical parameters are obtained by using the chain rule of differentiation. Therefore, different types of transducers can be investigated within a minimum computational cost. The formulation can be easily incorporated into an optimization procedure for the optimal design of feedforward control systems. A numerical example in which the proposed formulation is compared to results obtained using finite differences is included.

В работе развивается полиномиальный подход к синтезу оптимальных регуляторов пониженного порядка для одноканальных линейных стационарных систем, описываемых дифференциально-алгебраическими уравнениями. Критические корневые диаграммы и корневые многочлены применялись для синтеза оптимальных регуляторов в классических системах автоматического управления, а также в системе, описываемой дифференциально-алгебраическими уравнениями (ДАУ системе), включающей неустойчивый объект управления, заданный неправильной передаточной дробью с числителем шестой и знаменателем четвертой степени, и ПИ3-регулятор (пропорционально-интегральный). Здесь этот же объект стабилизируется ПИ-регулятором, который включает апериодическую составляющую и обеспечивает лучшую степень устойчивости замкнутой системы и возможность упрощения его структуры без существенного снижения эффективности. Схема метода по сравнению с классическими системами управления не меняется; переходная характеристика подтверждает астатизм и безымпульсность ДАУ-системы; некоторые особенности отмечены в заключении. We explore a polynomial approach for design of optimal low-order controllers for SISO LTI DAE control systems. The critical root diagram technique and root polynomials were developed for optimal controllers design of classical control systems; both notions were successfully used for design of the DAE system including an unstable plant defined by an incorrect transfer fraction with a 6th degree numerator and a 4th degree denominator, closed by a PI3-controller. In our paper the same plant is stabilized by a PI-controller, which includes an aperiodic term; it provides better relative stability of the closed loop system and a possibility of simplifying controller’s structure without noticeable decrease of efficiency. The scheme of the method is the same as in classical control systems; it involves forming a root polynomial and then a system of polynomial equations; the solution or lack of it allows establishing whether pole location of a closed-loop system is realized in accordance with the critical root diagram; optimal and sub optimal values of control parameters in the case are found using the same equations. The transient response confirms an a statism and impulse free ness of the closed loop DAE system. Thus, the polynomial approach turns out to be a useful alternative to state-space design methods in DAE systems. Some features and problems of DAE control system polynomial design are mentioned in the conclusion.

Several different interrelated processes often take place in high performance industrial heating furnaces simultaneously. It is necessary to take into account the interaction of these processes when they controlled by means of local control loops. The issue of control loops interaction is especially important for design of optimal control systems of heating furnace thermal rate when the total thermal energy consumption on heating is kept to a minimum. Control loops interaction in the energy saving optimal control of thermal rate in the industrial furnace working chamber results in a fairly complex control process, especially in the through furnaces for continuous cast billet heating before rolling at the variable performance operating mode of the rolling mill. The paper is concerned with the development of the optimal control system of the industrial furnace thermal rate with three main interrelated loops: the optimal control loop of temperature distribution within the furnace zones, the optimization control loop of fuel burning and the optimization control loop of gas fuel mode in the industrial furnace working chamber. The authors described the design of each loop, defined the interrelated factors, simulated the transient processes in the optimal control system of thermal rate taking into account the interaction of the control loops.

This paper presents a now method of optimal digital PID feedback control for a linear multivariate system by using a, parameter optimization technique. The most difficult points for the design of optimal digital PID feedback control system by the modern control theory are : (1) the control structure of it is specified in advance, (2) unless all the state variables are fed back, the optimal control cannot be obtained by dynamic programming or the maximum principle. However, the optimal digital PID feedback gains are determined by using the parameter optimization technique in this paper. When there are some states which are not fed back in the control system, the optimal feedback gains depend on the initial states. First, the optimal solution is presented in the case where all the initial Btates are known. Next, it is extended to the case where the initial states are random variables and their statistical properties are known,

Design of Continuous and Discrete Optimal Control Systems with Prescribed Transient Response

For the forth generation fighter aircraft, with thrust vector is one of the key technique characters. In condition of High AOA (Angle of attack), the dynamic of aircraft has strong nonlinear characteristic, and the general effectors lose the maneuver efficiency or get poorly, most control energy will be produced by the thrust vector, so new type of control law must be found. This control law should not only overcome those problems but also satisfy requirements of the forth generation aircraft. Nonlinear optimal control theory has merit on solving those problems. In this paper linearization method at Sampling Point and Receding Horizon Optimal (RHO) Control is brought forward. This control system can solve problem of a class of affine nonlinear system. Simulation result shows that the system can solve those problems perfectly and accord with the requirements of the forth generation fighter aircraft.

9 - Optimal and robust control system design

Simultaneous structure/control design synthesis for aero-servo-elastic system

A method for the optimal design of linear time-invariant systems with low sensitivity is proposed. The criterion of optimality is to choose system parameters and the corresponding optimal control so as to obtain zero or near-zero sensitivity of the optimal cost function. The proposed method yields a transient response, not only with faster settling time, but also insensitive to small parameter variations. The procedure is simple and can be extended to the optimal design of multi-parameter systems. It can be easily programmed on a digital computer without excessive increase in computer memory.

The paper describes a new algorithm of optimal control system design for a linear, time-invariant, single-input single-output plant. The proposed algorithm has low computational complexity, high stability and possesses the clear physical sense of the existence conditions of the design problem solution. The reference (command) signal and disturbances can include random and regular components. The algorithm is based on the matrix method solution of the polynomial equations. Numerical examples are given.

Indeed, designing a system aims to find the best architecture of components and functions among a set of numerous possible architectures. The need of fast evaluation tools and optimization algorithms integrated in a design methodology of dependable system is thus required.

We formulate a simultaneous optimal design problem of structural and control systems including discrete design variables. The problem generally becomes nonlinear and/or nondifferentiable optimization problem whose design variables are continuous or discrete. Since the nondifferentiability of the problem, we can not apply standard descent-based nonlinear optimization techniques such as steepest descent method, Quasi-Newton method etc.. Even if a subproblem, which is generated by fixing discrete design variables of the original problem, is corresponding to BMI(Bilinear Matrix Inequality), it is difficult to obtain the(global)optimal solution efficiently because of NP hardness nature of BMI. In this paper, we apply SA(Simulated Annealing)which is known as the one of the probabilistic optimization method. We present a new controller parametrization of the controller based on Youla parametrization. This parametrization does not need numerical computational procedure, such as solving Riccati equation or LMI to obtain stabilizing controller. Moreover, the class of the controller is at least larger than that of DVFB control(which is also a stabilizing control law without numerical computational procedure). We give a design example and show the effectiveness of the proposed design method.