Devices, systems, and methods for time calibration. The method comprises determining a first reference position of a robot in a robot coordinate system based on first feedback information received from the robot; determining an association between the first reference position and first sensing information receive from a sensor; receiving, from the robot, second feedback information associated with a second motion of the robot and, from the sensor, second sensing information associated with the second motion; and determining a time delay between a sensing time point when a sensing position of the robot in the second motion is sensed by the sensor and a recording time point when the sensing position is recorded by the robot in the second motion.

The present invention discloses a networked control system (NCS) time-delay compensation method based on predictive control. The method comprises the following steps: (1) acquiring random time-delay data in an NCS, and preprocessing the data; (2) predicting the current time-delay by using a fuzzy neural network (FNN) optimized by a particle swarm optimization (PSO) algorithm; (3) compensating the predicted time-delay by using an implicit proportional-integral-based generalized predictive control (PIGPC) algorithm; (4) determining whether a preset work end time is up according to a clock in the NCS; if yes, ending the process; if no, returning to step (2). The method disclosed by the present invention can accurately predict and effectively compensate the NCS time-delay and has excellent development prospect.

A system and a method for operating a robot. The system includes a first data collector coupled to the robot and configured to determine first position information of the robot based on feedback data received from the robot. The system also includes a second data collector coupled to a sensor and configured to determine second position information of an object to be operated by the robot based on sensing data received from the sensor. The system further comprises a first estimator coupled to the first data collector and the second data collector, and configured to generate a first prediction of a target position at which the object is operated by the robot and a command generator configured to generate a command for operating the robot at least partially based on the first prediction.

The present invention discloses a networked control system (NCS) time-delay compensation method based on predictive control. The method comprises the following steps: (1) acquiring random time-delay data in an NCS, and preprocessing the data; (2) predicting the current time-delay by using a fuzzy neural network (FNN) optimized by a particle swarm optimization (PSO) algorithm; (3) compensating the predicted time-delay by using an implicit proportional-integral-based generalized predictive control (PIGPC) algorithm; (4) determining whether a preset work end time is up according to a clock in the NCS; if yes, ending the process; if no, returning to step (2). The method disclosed by the present invention can accurately predict and effectively compensate the NCS time-delay and has excellent development prospect.

The present invention discloses a networked control system (NCS) time-delay compensation method based on predictive control. The method comprises the following steps: (1) acquiring random time-delay data in an NCS, and preprocessing the data; (2) predicting the current time-delay by using a fuzzy neural network (FNN) optimized by a particle swarm optimization (PSO) algorithm; (3) compensating the predicted time-delay by using an implicit proportional-integral-based generalized predictive control (PIGPC) algorithm; (4) determining whether a preset work end time is up according to a clock in the NCS; if yes, ending the process; if no, returning to step (2). The method disclosed by the present invention can accurately predict and effectively compensate the NCS time-delay and has excellent development prospect.

A system and a method for operating a robot. The system includes a first data collector coupled to the robot and configured to determine first position information of the robot based on feedback data received from the robot. The system also includes a second data collector coupled to a sensor and configured to determine second position information of an object to be operated by the robot based on sensing data received from the sensor. The system further comprises a first estimator coupled to the first data collector and the second data collector, and configured to generate a first prediction of a target position at which the object is operated by the robot and a command generator configured to generate a command for operating the robot at least partially based on the first prediction.