Abstract: According to one embodiment, a test apparatus for a variable speed controller is provided. A generator motor computation unit computes behaviors of the generator motor, using a state quantity regarding the generator motor and a predetermined transfer function. An AC machine computation unit computes behaviors of the AC machine, using a state quantity regarding the AC machine and a predetermined transfer function. A power converter computation unit computes behaviors of the power converter, using a state quantity regarding the power converter and a predetermined transfer function. Each of the computation units uses computation results of other computation units.

Abstract: A flow-data generation apparatus comprises a first unit extracting first binomial relation data to be a start point, a second unit associating second term of the first binomial relation data as a first child node with the start point as a first parent node, a third unit adding a relation type to an arc of the first binomial relation data, a fourth unit searching for third binomial relation data including first term of the third binomial relation data identical to second term of second binomial relation data, a fifth unit associating second term of the third binomial relation data as a second child node with the first term of the third binomial relation data as a second parent node, a sixth unit adding a relation type to an arc of the third binomial relation data, and an seventh unit repeating the searching, associating, and adding to generate a partial tree.

Abstract: A flow-data generation apparatus comprises a first unit extracting first binomial relation data to be a start point, a second unit associating second term of the first binomial relation data as a first child node with the start point as a first parent node, a third unit adding a relation type to an arc of the first binomial relation data, a fourth unit searching for third binomial relation data including first term of the third binomial relation data identical to second term of second binomial relation data, a fifth unit associating second term of the third binomial relation data as a second child node with the first term of the third binomial relation data as a second parent node, a sixth unit adding a relation type to an arc of the third binomial relation data, and an seventh unit repeating the searching, associating, and adding to generate a partial tree.

Abstract: An adjustment control method and apparatus of this invention assume that a dependency relationship table representing qualitative characteristics, in which manipulated variables are classified in units of change patterns of controlled variables, and are characterized in that an adjustment rule for adjustment is generated. An adjustment control method and apparatus of this invention is characterized in that it is determined whether the current object situation exhibits an exceptional behavior (vibration/saturation), on the basis of selection of an adjusted controlled variable and a manipulated variable obtained from an automatically generated adjustment rule and a past operation in response to an occasionally output deviation. If it is determined that no exceptional behavior is observed, the instruction of the generated adjustment rule is performed, otherwise, the correction amount of the.

Abstract: An adjustment control method and apparatus of this invention assume that a dependency relationship table representing qualitative characteristics, in which manipulated variables are classified in units of change patterns of controlled variables, and are characterized in that an adjustment rule for adjustment is generated. An adjustment control method and apparatus of this invention is characterized in that it is determined whether the current object situation exhibits an exceptional behavior (vibration/saturation), on the basis of selection of an adjusted controlled variable and a manipulated variable obtained from an automatically generated adjustment rule and a past operation in response to an occasionally output deviation. If it is determined that no exceptional behavior is observed, the instruction of the generated adjustment rule is performed, otherwise, the correction amount of the.

Abstract: In a vertically movable elevator group management control apparatus for control of a plurality of transversely shiftable cars among plural shafts, control is done by storing route data with respect to each said car, generating target floor data including a target floor, based on car call data obtained in correspondence with each said car and station call data as obtained correspondingly to each floor, estimating the time taken for said car to reach said target floor, based on at least said route data, said target floor data and said car call data, and assigning a certain car to a certain floor call, based on the estimated arrival time.

Abstract: The basic state feedback gain is derived and selected by the on-line identification based on the on-line input/output data of a controlled object, and at the same time, the sensitivity of the state feedback gain is directly and sequentially calculated based on the on-line input/output data of the controlled object. The state feedback gain is finely adjusted when the state feedback gain is not optimum. Further, the sensitivity of the state feedback gain of the controlled object is derived by the feedback gain sensitivity calculating unit according to the on-line input/output data of the controlled object. When the sensitivity is determined to be zero based on the criterion by the controller, the state feedback gain is determined to be optimum. When the sensitivity is determined to be near zero, the state feedback gain is finely adjusted by use of the sensitivity.