Provided is an information processing apparatus including a control unit configured to control a gain of a drive signal for an actuator that is used for vibration control of an object to be controlled, according to a processing result of adaptive processing using an output signal from a sensor and the drive signal for the actuator that have been decimated, the sensor being configured to detect vibration of the object to be controlled, the drive signal being generated according to the output signal from the sensor.

A feedback control device determines a first target angular velocity that is a target angular velocity of an output angular velocity of the target device, using a first transfer function, determines a control input to the target device, based on a difference between the first target angular velocity and the output angular velocity, determines, based on the operation input, a second target angular velocity that is the target angular velocity requested by an operator, determines a degree of comfort of the operator, based on a difference between the output angular velocity and the second target angular velocity, sequentially accumulates the first target angular velocity, the degree of comfort, and a target degree of comfort in a database, and adjusts a first moment of inertia in such a way as to reduce a difference between the target degree of comfort and the degree of comfort, using data accumulated in the database.

A feedback control device determines a first target angular velocity that is a target angular velocity of an output angular velocity of the target device, using a first transfer function, determines a control input to the target device, based on a difference between the first target angular velocity and the output angular velocity, determines, based on the operation input, a second target angular velocity that is the target angular velocity requested by an operator, determines a degree of comfort of the operator, based on a difference between the output angular velocity and the second target angular velocity, sequentially accumulates the first target angular velocity, the degree of comfort, and a target degree of comfort in a database, and adjusts a first moment of inertia in such a way as to reduce a difference between the target degree of comfort and the degree of comfort, using data accumulated in the database.

An artificial intelligence device is disclosed. In an embodiment, the artificial intelligence device includes a sensor configured to acquire an output value according to control of a control system, and an artificial intelligence unit comprising one or more processors configured to obtain one or more updated parameters of a control function of the control system based on the output value using reinforcement learning, and update the control function for providing a control value to the control system with the one or more updated parameters.

Provided in the present invention are a microgrid control system and a microgrid, the microgrid control system comprising: a grid-connected switch, an energy router, a first controller and a second controller; the first controller controls the grid-connected switch and sends a first control instruction; the second controller receives the first control instruction and responds to the first control instruction for controlling the energy router.

Provided in the present invention are a microgrid control system and a microgrid, the microgrid control system comprising: a grid-connected switch, an energy router, a first controller and a second controller; the first controller controls the grid-connected switch and sends a first control instruction; the second controller receives the first control instruction and responds to the first control instruction for controlling the energy router.

A camera module actuator includes: a magnet disposed on a lens barrel; a driving coil disposed opposite to the magnet; and a driving device including a comparer that calculates an error value by comparing a target position of the lens barrel with a current position of the lens barrel, a controller IC that generates a control signal by applying control gains to the error value, and a driving circuit that generates a driving signal in response to the control signal. The controller IC determines the control gains based on a friction coefficient between a guide groove guiding movement of the lens barrel and a ball bearing contacting the guide groove. The controller IC provides a detection signal having a gradually increasing level to the driving coil, and determines the friction coefficient based on a level of the detection signal at a point in time of movement of the lens barrel.

A camera module actuator includes: a magnet disposed on a lens barrel; a driving coil disposed opposite to the magnet; and a driving device including a comparer that calculates an error value by comparing a target position of the lens barrel with a current position of the lens barrel, a controller IC that generates a control signal by applying control gains to the error value, and a driving circuit that generates a driving signal in response to the control signal. The controller IC determines the control gains based on a friction coefficient between a guide groove guiding movement of the lens barrel and a ball bearing contacting the guide groove. The controller IC provides a detection signal having a gradually increasing level to the driving coil, and determines the friction coefficient based on a level of the detection signal at a point in time of movement of the lens barrel.

Scenario discriminative hybrid motion control for robots and methods of use are disclosed herein. A method may include determining a number of objects in a space, determining when a goal is within the space, and selectively switching between a plurality of control schemes based on the number of objects in the space and whether the goal is within the space. The plurality of control schemes including a model predictive control scheme, a simplified model predictive control scheme, and a proportional-integral-derivative scheme. Selectively switching between the plurality of control schemes reduces power consumption of an automated system compared to when the automated system utilizes only the model predictive control scheme.

Scenario discriminative hybrid motion control for robots and methods of use are disclosed herein. A method may include determining a number of objects in a space, determining when a goal is within the space, and selectively switching between a plurality of control schemes based on the number of objects in the space and whether the goal is within the space. The plurality of control schemes including a model predictive control scheme, a simplified model predictive control scheme, and a proportional-integral-derivative scheme. Selectively switching between the plurality of control schemes reduces power consumption of an automated system compared to when the automated system utilizes only the model predictive control scheme.