A controller of a motor includes: an acceleration/deceleration time constant storing unit that stores an acceleration/deceleration time constant; a position command creating unit that creates a position command value based on the acceleration/deceleration time constant; a position detection unit that detects a rotation position of the motor; a speed command creating unit that creates a speed command for the motor on the basis of the position command value and a position detection value detected by the position detection unit; an ideal response computing unit that computes an ideal response from the position command value; and a response comparing unit that compares the ideal response with an actual response detected by the position detection unit. The response comparing unit changes the acceleration/deceleration time constant stored in the acceleration/deceleration time constant storing unit when it is determined that the ideal response does not match the actual response.

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.

A processor-implemented method based on an acceleration sensor and a geomagnetic sensor for determining an angular velocity of an object includes: deriving a state variable and a variance of the state variable based on an error quaternion and converting a quaternion-based rotation matrix into an error quaternion-based rotation matrix; calculating an observation matrix and an output matrix of the Kalman filter based on the error quaternion-based rotation matrix; calculating a gain of the Kalman filter based on the transferred variance of the state variable and the observation matrix of the Kalman filter after transferring the state variable and the variance of the state variable through a discretized transfer matrix; calculating a quaternion-based on a calibrated state variable and an estimated quaternion after calibrating the state variable and the variance of the state variable through the gain of the Kalman filter; and calculating angular velocity based on the quaternion.

An automatic system level testing (ASLT) system for testing smart devices is disclosed. The system comprises a system controller operable to be coupled with a smart device in an enclosure, wherein the system controller comprises a memory comprising test logic and a processor. The system also comprises the enclosure, wherein the enclosure comprises a plurality of components, the plurality of components comprising: (i) a robotic arm comprising a stylus, wherein the stylus is operable to manipulate the smart device to simulate human interaction therewith; and (ii) a platform comprising a device holder, wherein the device holder is operable to receive a smart device inserted there into. The processor is configured to automatically control the smart device and the plurality of components in accordance with the test logic.

Provided is an abnormality diagnosis device for a machine tool, and an abnormality diagnosis method, whereby it is possible to diagnose the degree of damage to a spindle system due to a collision. An abnormality diagnosis device (40) for a machine tool (1) has: a displacement sensor (36) for detecting the amount of displacement of a spindle bearing (30); an acceleration sensor (38) for detecting the acceleration of a ram (28); a collision determination unit (46) for determining whether the ram or a spindle (32) has collided with a work piece, on the basis of at least the amount of displacement of the spindle bearing detected by the displacement sensor or the acceleration of the ram detected by the acceleration sensor; and a damage determination unit (50) for determining the degree of damage to the spindle bearing on the basis of at least the amount of displacement of the spindle bearing, the acceleration of the ram, or a frequency characteristic of vibration of the ram due to rotation of the spindle obtained from the acceleration of the ram, when the collision determination unit determines that the ram or the spindle has collided with the work piece.

Embodiments of the present invention provide methods and systems to analyze wearable technology. A robot with snake assembly works in conjunction with a server in order to simulate the locomotive actions of appendages and to concomitantly determine the response of wearable technology devices, which are attached to the snake robot assembly, to the simulated locomotive actions.

A motor drive having controller settings which will result in improved tuning-less performance is disclosed. Gain values for the control loops and/or observer are determined independently of the mechanical loading and the resultant effects of that loading on the motor. The motor drive includes a control loop operable to receive a command signal and to generate a controller reference signal to achieve desired operation of a motor connected to the motor drive. The motor drive also includes a load observer operable to generate a signal that estimates a response required by the motor drive as a result of a load present on the motor. The response estimate signal is provided to the controller to isolate the effects of the load dynamics from operation of the control loops within the controller. A modified controller reference signal is generated as a function of the response estimate signal and the controller reference signal.

A device (10) is placed on an object (30) handled by a robot (100). Based on measurements performed by at least one sensor of the device (10), engagement of the robot (100) with the object (30) is detected. The measurements may for example include acceleration measurements which allow for detecting movement of the object (30) caused by the robot (100).

A substrate processing system comprising, a frame forming a substrate transport space within the substrate processing system, a substrate transport apparatus operably coupled to the frame with a movable arm and a drive section configured to move the movable arm and transport a substrate, held on an end effector of the arm, through the transport space from a first position of the substrate processing system to a second position of the substrate processing system different than the first position; and a controller operably coupled to the movable arm and drive section so as to effect movement of the movable arm to the different system positions, the controller is communicably coupled to at least one arm motion sensor and at least one system metrology sensor, and the at least one system metrology sensor senses system metrology predetermined characteristics, different that the arm motion predetermined characteristics.

A machine tool comprises: a servomotor feeding a workpiece or a tool; a motor control section controlling the servomotor; and a processor connected to the motor control section, in a parameter adjustment mode while rotating a load by the servomotor with a given speed command issued to the motor control section under a condition where torque is limited, the processor calculating load inertia based on the torque and an angular acceleration of the servomotor that is obtained based on an output from the servomotor, calculating a parameter based on the load inertia, and adjusting a control parameter set to the motor control section based on the parameter.