Abstract: A method for identifying pitch error and yaw error of a numerically-controlled (NC) machine tool, including: acquiring a Cartesian coordinate system of a target machine tool; setting each axis of the Cartesian coordinate system as movement axis, where each movement axis has three measurement trajectories, and the three measurement trajectories are mutually parallel to the corresponding axis, and not on the same plane; selecting an axis as the movement axis; and obtaining positioning error data between an actual operation measurement point and an ideal operation measurement point of the target machine tool when the target machine tool moves along the three measurement trajectories corresponding to the movement axis; and according to spatial angle geometric relationship and the positioning error data, obtaining a pitch error angle and a yaw error angle of the target machine tool.

Abstract: A method for identifying pitch error and yaw error of a numerically-controlled (NC) machine tool, including: acquiring a Cartesian coordinate system of a target machine tool; setting each axis of the Cartesian coordinate system as movement axis, where each movement axis has three measurement trajectories, and the three measurement trajectories are mutually parallel to the corresponding axis, and not on the same plane; selecting an axis as the movement axis; and obtaining positioning error data between an actual operation measurement point and an ideal operation measurement point of the target machine tool when the target machine tool moves along the three measurement trajectories corresponding to the movement axis; and according to spatial angle geometric relationship and the positioning error data, obtaining a pitch error angle and a yaw error angle of the target machine tool.

Abstract: An error compensation system for a numerical control (NC) machine tool based on iterative learning control, including a trajectory generating module, a down-sampling module, a position controller, a first holder, a velocity-loop iterative learning controller, a velocity controller, a second holder and a control plant. The trajectory generating module is configured to generate a desired trajectory command including a first sampling command. The first sampling command is transmitted to the down-sampling module and the velocity-loop iterative learning controller. The first sampling command is down-sampled through the down-sampling module to obtain a second sampling command. The velocity-loop iterative learning controller is configured to receive the first sampling command, and obtain a first sampling error compensation sequence according to a first sampling error sequence and a first sampling error compensation sequence of a previous iteration machining process stored therein.

Abstract: A model inversion-based iterative learning control method for a printer and a printer system. An error of a desired trajectory and an actual displacement of a printing paper and an error of a reference input and an actual displacement of a motor are considered at the same time to construct an iterative learning control model for the printer based on an inversion model, so as to iteratively modify an error failing to meet requirements.

Abstract: A model inversion-based iterative learning control method for a printer and a printer system. An error of a desired trajectory and an actual displacement of a printing paper and an error of a reference input and an actual displacement of a motor are considered at the same time to construct an iterative learning control model for the printer based on an inversion model, so as to iteratively modify an error failing to meet requirements.