Abstract: The present disclosure relates to an electronic control system based on three-dimensional (3D) concrete printing, including: a control card, a three-way axis driver, a printing device head, a servo motor, a camera and a monitoring system. The monitoring system includes the camera and a display module. The control card is configured to parse a 3D digital model of a to-be-printed object into a program instruction. The three-way axis driver is configured to receive the program instruction to drive the servo motor. The servo motor is configured to control movement of the printing device head. The camera is configured to acquire video data of a discharge port of the printing device head in real time. The monitoring system is configured to remotely monitor concrete discharge conditions of the printing device head according to the camera. The control card is connected with the three-way axis driver based on an EtherCAT bus.

Abstract: The present disclosure presents a feedback active noise control system and strategy with online secondary-path modeling, and belongs to the technical field of active noise control. The linear prediction subsystem takes the residual noise as its input and separates the remaining sinusoidal noise from the broadband noise. The remaining sinusoidal noise is used effectively not only to update the controller but also to scale the auxiliary noise, while the broadband noise serves as a desired input of online secondary-path modeling subsystem. In this way, the coupling between the controller and the online secondary-path modeling subsystem is significantly mitigated, leading to both faster convergence and improved noise reduction performance. A practical scheme for refreshing the entire system is also developed to enhance its robustness against even abrupt changes with the secondary path or the primary noise.

Abstract: The present disclosure presents a feedback active noise control system and strategy with online secondary-path modeling, and belongs to the technical field of active noise control. The linear prediction subsystem takes the residual noise as its input and separates the remaining sinusoidal noise from the broadband noise. The remaining sinusoidal noise is used effectively not only to update the controller but also to scale the auxiliary noise, while the broadband noise serves as a desired input of online secondary-path modeling subsystem. In this way, the coupling between the controller and the online secondary-path modeling subsystem is significantly mitigated, leading to both faster convergence and improved noise reduction performance. A practical scheme for refreshing the entire system is also developed to enhance its robustness against even abrupt changes with the secondary path or the primary noise.