Hitachi, Ltd.

Masaaki Nakajima

Yasuo Morooka

Yasunori Katayama

Yutaka Saito

Junzo Kawakami

Hiroshi Matsumoto

Tetsuo Manchu

Shigeru Ueki

Takashi Okada

Masahiro Kayama

Yoichi Sugita

Masakane Shigyo

In order to control an apparatus, such as a rolling mill, a control device may use a pre-set operation pattern to generate a pre-set command signal, which is then modified. That first modification may be part of a feedback loop in dependence on the variation of a variable operation device of the apparatus, on a plurality of pre-set signals may be combined by fuzzy logic. Then the relationship between the modified pre-set command signal and the variation of the variable operation device is investigated to generate a compensation signal which is used to modify further the pre-set command signal. In a feedback loop, that further modification may compensate for changes in the operating point of the loop, due to changes in the apparatus being controlled. In a fuzzy logic arrangement, the compensation signal may be a further control pattern developed by the control device itself, which is combined with the pre-set patterns by fuzzy logic. The control device may be in the form of a series of modules.

Control device for controlling a controlled apparatus, and a control

A failure diagnosis apparatus for a control system at which plural sensors are provided, comprises a means for extracting correlations among output signals from the predetermined groups of the sensors based on the output signals in the normal operations of the control system by such a means as a quantization method of quantizing a signal space, a means for making up an abnormal degree of the output signals from each predetermined group of the sensors by comparing output signals to be examined from each predetermined group of the sensors and the correlation corresponding to the group of the sensors, and a means for estimating the reliability of each sensor by using the abnormal degrees and for identifying the sensor outputting an abnormal signal.

Failure diagnosis apparatus and a method thereof

In order to control an apparatus, such as a rolling mill, a control device may use a pre-set operation pattern to generate a pre-set command signal, which is then modified. That first modification may be part of a feedback loop in set command signal, which is then modified. That first modification may be part of a feedback loop in logic. Then the relationship between the modified pre-set command signal and the variation of the variable operation device is investigated to generate a compensation signal which is used to modify further the pre-set command signal. In a feedback loop, that further modification may compensate for changes in the operating point of the loop, due to changes in the apparatus being controlled. In a fuzzy logic arrangement, the compensation signal may be a further control pattern developed by the control device itself, which is combined with the pre-set patterns by fuzzy logic. The control device may be in the form of a series of modules.

In order to control an apparatus, such as a rolling mill, a control device may use a pre-set operation pattern to generate a preset command signal, which is then modified. That first modification may be part of a feedback loop in dependence on the variation of a variable operation device of the apparatus, on a plurality of pre-set signals may be combined by fuzzy logic. Then the relationship between the modified pre-set command signal and the variation of the variable operation device is investigated to generate a compensation signal which is used to modify further the pre-set command signal. In a feedback loop, that further modification may compensate for changes in the operating point of the loop, due to changes in the apparatus being controlled. In a fuzzy logic arrangement, the compensation signal may be a further control pattern developed by the control device itself, which is combined with the pre-set patterns by fuzzy logic. The control device may be in the form of a series of modules.

A method and an apparatus for controlling an object by giving commands to actuators that control the object to perform desired operations, wherein relationships between respective values of parameters of the model for the controlled object and the input/output states of the model are obtained by learning, the obtained relationships are stored in a memory unit as a result of the learning, parameter values of the model are decided by referring to the learning result stored in the memory unit based on the input/output measured values of the controlled object, and commands are obtained based on the decided parameter values and the obtained commands are given to the actuators.

Method and device for controlling object to be controlled using learning

A control system for controlling a plurality of control elements, which are effective to control of a given controlled system, is disclosed. In this control system, a characteristic value representing the characteristic of a given controlled system to be controlled is detected, and respective optimum manipulated variables of the plurality of control elements are derived on the basis of the detected characteristic value. The optimum manipulated variables are derived by setting a plurality of reference patterns representing different features of the characteristic value on the basis of a predicted value of the characteristic value, deriving degree of conviction that the detected characteristic value belongs to each of the reference patterns, presetting rules whereby a manipulated variable of each of the plurality of control elements is determined when the detected characteristic value belongs to each of the plurality of reference patterns, and deriving a manipulated variable of each control element on the basis of degree of conviction that the detected characteristic value belongs to each of the plurality of reference patterns and the manipulated variable determining rule preset with respect to each control element for each reference pattern.

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Hitachi, Japan

Masaaki Nakajima