Abstract: The feedback control device takes information regarding a control deviation between a measured value and a target value of a controlled object as input, and outputs a control amount for the controlled object; comprising: a first control unit that takes information regarding the control deviation as input, and outputs a first control amount for the controlled object; a second control unit that takes information regarding the control deviation as input and outputs a second control amount for the controlled object, and in which a parameter for calculating the second control amount is determined by machine learning; an operation unit that operates the controlled object using the first control amount output from the first control unit and the second control amount output from the second control unit; and a sampling unit for thinning out at a predetermined period information regarding the control deviation input to the second control unit.

Abstract: The feedback control device takes information regarding a control deviation between a measured value and a target value of a controlled object as input, and outputs a control amount for the controlled object; comprising: a first control unit that takes information regarding the control deviation as input, and outputs a first control amount for the controlled object; a second control unit that takes information regarding the control deviation as input and outputs a second control amount for the controlled object, and in which a parameter for calculating the second control amount is determined by machine learning; an operation unit that operates the controlled object using the first control amount output from the first control unit and the second control amount output from the second control unit; and a sampling unit for thinning out at a predetermined period information regarding the control deviation input to the second control unit.

Abstract: Provided is a management apparatus for managing a processing apparatus including a driver configured to drive a target object in regard to a plurality of drive axes, and a controller configured to control the driver using a neural network for which a parameter for outputting a manipulated variable to the target object is decided by reinforcement learning. The management apparatus includes a learning unit configured to decide the parameter of the neural network by reinforcement learning. The learning unit performs the reinforcement learning by evaluating a reward obtained from a control result of the target object by the controller, and relatively adjusts rewards regarding the respective drive axes in accordance with required precisions for the respective drive axes.

Abstract: A motion control apparatus includes a first movable part, a second movable part, a first measurement device for measuring a motion of the first movable part, a first compensator for generating a first manipulated variable based on an output from the first measurement device and a target value for controlling the motion of the first movable part, a generator for generating an observed value concerning a relative motion between the first movable part and the second movable part, a second compensator for generating a second manipulated variable based on the observed value, and a calculator for generating a manipulated variable for driving the first movable part based on an output from the first compensator and an output from the second compensator. For the second compensator, a parameter value for generating the second manipulated variable is decided by machine learning.

Abstract: The feedback control device takes information regarding a control deviation between a measured value and a target value of a controlled object as input, and outputs a control amount for the controlled object; comprising: a first control unit that takes information regarding the control deviation as input, and outputs a first control amount for the controlled object; a second control unit that takes information regarding the control deviation as input and outputs a second control amount for the controlled object, and in which a parameter for calculating the second control amount is determined by machine learning; an operation unit that operates the controlled object using the first control amount output from the first control unit and the second control amount output from the second control unit; and a sampling unit for thinning out at a predetermined period information regarding the control deviation input to the second control unit.

Abstract: A display device is constructed with conductive fibers which are coated with a display medium and are woven together with transparent conductive fibers. The conductive fibers coated with a display medium serve as warps and the transparent conductive fibers serve as wefts. The display device is not provided with an external electrode and is therefore flexible like plain cloth.

Abstract: A display device is constructed with conductive fibers which are coated with a display medium and are woven together with transparent conductive fibers. The conductive fibers coated with a display medium serve as warps and the transparent conductive fibers serve as wefts. The display device is not provided with an external electrode and is therefore flexible like plain cloth.