Conceptual design of multiple parallel switching controller

Ugolini, D.; Yoshikawa, Shinji; Ozawa, Kenji

PNC TN9410 96-109, 12 Pages, 1996/05

PNC-TN9410-96-109.pdf:0.68MB

This report discusses the conceptual design and the development of a preliminary model of a multiple parallel switching (MPS) controller. The introduction of several advanced controllers has widened and improved the control capability of nonlinear dynamical systems. However, it is not possible to uniquely define a controller that always outperforms the others, and, in many situations, the controller providing the best control action depends on the operating conditions and on the intrinsic properties and behavior of the controlled dynamical system. The desire to combine the control action of several controllers with the purpose to continuously attain the best control action has motivated the development of the MPS controller. The MPS controller consists of a number of single controllers acting in parallel and of an artificial intelligence (AI) based selecting mechanism. The AI selecting mechanism analyzes the output of each controller and implements the one providing the best control performance. An inherent property of the MPS controller is the possibility to discard unreliable controllers while still being able to perform the control action. To demonstrate the feasibility and the capability of the MPS controller the simulation of the on-line operation control of a fast breeder reactor (FBR) evaporator is presented.

Implementation of an MRACnn System on an FBR Building Block Type Simulator

Ugolini; Yoshikawa, Shinji; Ozawa, Kenji

PNC TN9410 95-253, 13 Pages, 1995/10

PNC-TN9410-95-253.pdf:0.5MB

This report presents the implementation of the a model reference adaptive control system based on the artificial neural network technique (MRAC) in a fast breeder reactor (FBR) building block type (BBT) simulator representing the Monju prototype reactor. The purpose of this report is to improve the control of the outlet steam temperature of the three evaporators of the Monju prototype reactor. The connection between the MRAC system and the BBT simulator is achieved through an external shared memory accessible by both systems. The MRAC system calculates the demand for the position of the feedwater valve replacing the signal of a PID controller collocated inside the heat transport system model of the Monju prototype reactor. Two series of simulation tests havc been performed, one with one loop connected to the MRAC system (leaving the remaining two connected to the original PID controller), and the other with three loops connected to the MRAC system. In both simulation tests the MRAC system performed better than the PID controller, keeping the outlet steam temperature of the evaporators closer to the required set point value through all the transients.

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Ugolini; Yoshikawa, Shinji;

Donen Giho, (95), p.59 - 62, 1995/09

https://jopss.jaea.go.jp/pdfdata/PNC-TN1340-95-003.pdf

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Inplementation of a Model Ref-erence Adaptive Control System Using Neural Network to Control a Fast Breeder Reactor Steam Evaporator

Ugolini, D.; Yoshikawa, Shinji; Endo, Akira

PNC TN9410 94-069, 30 Pages, 1994/02

PNC-TN9410-94-069.pdf:0.97MB

This paper discusses the development of an indirect model reference adaptive control (MRAC) system, using the artificial neural network (ANN) technique, and its implementation to control the outlet steam temperature of a sodium to water helical-coil once-through evaporator. The ANN technique is applied in the identification process and in the control process of the indirect MRAC system. The evaporator is simulated with a nonlinear dynamic modular model representing a superheated cycle with three regions, subcooled, saturated, and superheated, and moving boundaries. The emphasis is placed on demonstrating the efficacy of the indirect MRAC system in the control of the outlet steam temperature of the evaporator model, and on showing the important function covered by the ANN technique, whose adaptation and learning capabilities, contribute to improve the performance of the control action of the indirect MRAC system. The implementation of the ANN technique in the indirect MRAC system generates a strong control system. An important characteristic of this control system is that it relays only on some selected input variables and on the output variables of the evaporator model. These are the variables that can be actually measured or calculated in a real environment. Therefore, the internal variables, which are needed to develop the model, but that can be hardly measured or calculated in a real environment, are not utilized during the control action performed by the indirect MRAC system. The results obtained applying the indirect MRAC system to control the evaporator model are quite remarkable. The outlet temperature of the steam is almost perfectly kept close to its desired set point, when the evaporator model is forced to depart from steady state conditions, either due to the variation of some input variables or due to the alteration of some of its internal parameters. The results also show the importance of the role played by the ANN technique in the overall ...

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Yoshikawa, Shinji; Saeki, Akira; Ugolini;

Genshiro No Kanshi To Shindan Ni Kansuru Dai-7-Kai Shimpojiumu (SMORN 7), , 

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