Transfer robots for large-sized panels used in the display industry need to compensate for path error and reduce vibration. The iterative learning control (ILC) technique can simply compensate for the uncertainty of a control system in a repetitive motion. This study introduces an ILC compensation system applied with an accelerometer to a display panel transfer robot control system. The ILC technique was used to reduce the path error and vibration induced the flexibility of the large size robot. This method was applied to a robot system without the system model of the mechanical and measurement elements. To improve the iterative learning performance through the accelerometer, the ILC is configured by applying an acceleration element and time shift method to the PD-Offline ILC algorithm. In addition, based on the characteristics of repetitive motion, the ILC derives an acceleration data-based position estimation value. In this study, the ILC system and a large-sized panel transfer robot were implemented in MATLAB-Simulink with RECURDYN. The path errors and vibration level of the robot with a suggested ILC of 20 repeated learnings were reduced by more than 90%.

We present Error Compensation Software (ECS) which uses a decic polynomial model and three-dimensional surface measurement data for the fabrication of high precision freeform mirrors. ECS is designed based on a graphic user interface that includes an error calculation mechanism and surface distribution maps, and it accepts the Ultrahigh Accurate 3D Profilometer (UA3P) measurement data of the fabricated mirror surface. It exports surface coefficients and tool paths for the Single Point Diamond Turning (SPDT) machine which allows engineers to utilize the software during the compensation process. The ECS is based on Visual C++ and runs on the Windows operating system. The error compensation process with ECS has been applied to the 90 mm diameter aluminum freeform mirrors for usage in view infrared satellites, and the root mean square and peak-to-valley surface errors were reduced from 1.52 to 0.11 μm, and from 7.05 to 1.99 μm, respectively, satisfying the requirement of the infrared camera.

In ultra-precision processes, such as aerospace parts and precision mold machining, the accuracy of a feed drive system should be secured to achieve sufficient form accuracy. Dual-Servo stages, which compensate for multi-DOF motion errors, are being developed depending on the applied processes. This paper deals with the fine stage of a dual-servo stage to compensate for 6-DOF motion errors of a linear stage. The proposed fine stage measured 6-DOF errors of the linear stage motion with capacitive sensors, a reference mirror, and an optical encoder. It compensated for the errors using the flexure hinge mechanism with piezo actuators. The error equations and the inverse kinematics were derived to calculate the 6- DOF errors and displacements of piezo actuators for 6-DOF motions, respectively. Performance evaluation was implemented to verify feasibility of the developed fine stage of the fabricated dual-servo stage. Through the step response test of the fine stage, compensation resolutions for the translational and the rotational motion were confirmed to be less than 10 nm and 1/3 arcsec, respectively. The 6-DOF motion errors in the verification test were reduced by 73% on average.

In the framework of the 4th industrial revolution, modern machine-building rapidly converges with IOT technology. This requires very high precision machining of the parts and assemblies, such as electronics, vehicle and components, agricultural and construction machines, optical instruments, and machine tools. However, high precision machinery is quite expensive, and there exists a general need for low-cost equipment. While many researchers are working on this, their major focus is on cutting tools. This study aimed to compensate for errors and enhance machinery precision by adding a servo controller to the processing unit. Consequently, the study is on servo control and processing precision for processing utilizing ECTS (Error Compensation Tool Servo) to compensate for errors.

Predicting the response of a system, even several steps ahead, offers tremendous advantage to improve the system performance, to acquire an ideal model of a system and disturbances. The best way of predicting a response signal from a system is to use the sinusoidal extrapolation based on its frequency characteristics. Sinusoidal extrapolation is a statistical method for predicting future data through frequency analysis of past data. Practically speaking, the prediction from a frequency analysis in a control system is appropriate, because the output of a system can be modeled by several dominant frequencies from input and system models. In this study, we developed a novel and reliable prediction filter, using multi frequency sinusoidal extrapolation and a prediction error compensation algorithm. In this paper, we also suggest the design guidelines, regularity, and overall process of obtaining optimal predictions from an efficient and practical view, for the widely used industrial equipment. Results show that the performance of the proposed prediction filter is considered reliable and effective for improving the performance of a system, such as a motion controller.