In this paper, an effective and simple internal model control (IMC) with extended Kalman filter (EKF) is presented for low-velocity smoothness control of air bearing linear feed stage (ABLFS) driven by permanent magnet synchronous linear motors (PMLSMs). Firstly, the ABLFS is modeled as an inertia system with the nonlinear force ripples which correlates with phase current. The identification experiment is conducted using white noise method to get the approximate linear model of the air-bearing stage. Then, a typical linear feedback controller is derived from the standard IMC principle for the fundamental close-loop control. However, the IMC controller is sensitive to disturbances and modal uncertainties which limits the tracking accuracy. To overcome these drawbacks, the Kalman filter is employed as a state observer which makes the optimal estimation of system state variables (current, velocity and displacement). Since the Kalman filter is a synthesis process by calculating the probability density of measured values and predicted values, the results are more reliable to take place of the encoder feedback. Finally, the effectiveness of this modified method is validated by comparative experiments on a practical ABLFS system.
The material removal mechanism of aluminate magnesium spinel was investigated by nanoindentation and microscratch test. The hardness increases with the increase of load. The influence of scratch speed and scratch load on the removal mechanism of spinel was analyzed based on the penetration depth, tangential force and acoustic emission (AE) signal. It was found that with the increase of scratch speed, the area of elastic-plastic removal and brittle plastic transition increased. The AE signal appears at the beginning of a brittle plastic transition for the first time. Moreover, the tangential force growth rate of spinel in the elastic-plastic stage is lower than that in the brittle removal stage. The results indicated that improving scratch speed and reducing the scratch load is beneficial to reduce the range of brittle removal of spinel, thus increasing the range of plastic removal and brittle plastic transition.
For the existing ultraprecision fly-cutting machine tools, the cutting depth needs to be adjusted by the engineer manually, the cutting efficiency of Potassium Dihydrogen Phosphate (KDP) crystal is low and the error is large. In order to solve the problems of the existing ultraprecision fly-cutting machine tools, such as the need for engineers to manually adjust the cutting depth, low cutting efficiency and large error of KDP crystal. In this paper, a parallel high bandwidth nanometer feeding mechanism driven by piezoelectric ceramics with high resonance frequency and compact structure is designed for ultraprecision fly-cutting machine tools. The designed three-degree-of-freedom nanometer feeding platform can achieve precise deflection in θx and θy directions, and precise vertical movement in z-axis direction which can be used for micro-feeding and fine-tuning of KDP crystal. The static analysis and modal identification of the micro-feed platform are carried out to verify the static and dynamic characteristics of the designed device. In order to further verify the correctness of the finite element simulation, the experimental modal analysis of the micro-feed platform is carried out. The correctness of the finite element model is verified, and the natural frequency is high, which enables the micro-feed platform to obtain better dynamic response performance.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.