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    • 1. 发明授权
    • Motor controller
    • US11175647B2
    • 2021-11-16
    • US16004639
    • 2018-06-11
    • FANUC CORPORATION
    • Shunpei TanakaKazunori Iijima
    • G05B19/416
    • A controller of a motor that drives a driven body includes: an inertia estimating unit that estimates inertia on the basis of feedback information (torque and current) of the motor; a computing unit that computes an acceleration or deceleration time constant of the motor from the estimation inertia estimated by the inertia estimating unit; a storage unit that stores an inertia difference which is a difference between the estimation inertia and at least one known actual inertia and a time constant difference which is a difference between an actual acceleration or deceleration time constant corresponding to the actual inertia and an acceleration or deceleration time constant calculated on the basis of the estimation inertia; and a correction unit that corrects the acceleration or deceleration time constant calculated by the computing unit using the inertia difference and the time constant difference stored in the storage unit.
    • 8. 发明授权
    • Control parameter adjusting device and adjusting method using machine learning
    • US11126149B2
    • 2021-09-21
    • US16286982
    • 2019-02-27
    • FANUC CORPORATION
    • Ryoutarou TsunekiShunpei Tanaka
    • G05B19/4155G05B13/02
    • To provide an adjusting device and an adjusting method for appropriately controlling the machine learning reduced in cost with respect to calculation load and learning period of time in the case where an evaluation program for machine learning is used separately from a machining program and the like. The present invention includes a feedback information acquiring part configured to acquire, from a control device, feedback information obtained when an evaluation program including various types of learning elements is executed in the control device, a determination part configured to determine which learning element the acquired feedback information corresponds to among the various types of learning elements, a feedback information transmitting part configured to transmit the acquired feedback information to a machine learning part corresponding to the learning element, a parameter setting information acquiring part configured to acquire control parameter setting information obtained through machine learning by use of the feedback information, and a parameter setting information transmitting part configured to transmit the acquired control parameter setting information to the control device.