Development of Drive System of High Performance Micro Positioning Worktable Based on Giant Magnetostrictive Material

Xiao

et al. 2022

Mech. Sci.

Self Cite

Abstract. Nonlinearity is one of the important factors affecting the positioning accuracy of the macro–micro composite actuator. To improve the positioning accuracy of the driving model of the macro–micro composite actuator, this paper combines the research phenomenon of the nonlinear characteristics of the voice coil motor to model the nonlinear factors that affect the macro-moving part of the macro–micro composite actuator. Firstly, based on analyzing its structure and working principle, the variation law of the magnetic field intensity at the working air gap of the macro-motion part is analyzed by the finite element method, and the driving force model of the macro-motion part is established. Secondly, through the magnetic field simulation analysis, there is a magnetization phenomenon in the mover part, and the static friction model is established. Then, the experimental data are acquired and processed by building the experimental test platform of the actuator, and the variation model of the electromechanical time constant with the macro-motion displacement is established. Then, combined with the Stribeck model and the static friction model, the kinetic model of the macro-motion part is established. Finally, using the least square method identify the parameter model, the results are compared with the experiment. The results show that the magnetic field distribution at the working air gap of the macro-motion part of the macro–micro composite actuator is relatively uniform, but it is related to the macro-motion displacement and the macro-motion coil current. When the macro-motion part of the macro-micro composite actuator starts, the friction model can approximately reflect the change of friction force, the kinetic model of the macro-motion part can reflect the dynamic characteristics of the macro-motion part, and the matching degree is 92.97 %. The research results lay a theoretical and technical foundation for the development of a high-speed and large-stroke positioning controller of the macro-motion micro composite actuator.

Section: The Model Of the Macro-motion Part Of The Macro-micro Compos...mentioning

confidence: 99%

Nonlinear characteristics of the driving model of the coaxial integrated macro–micro composite actuator

Xiao

et al. 2022

Mech. Sci.

Self Cite

“…The structural design of the micro-motion GMA was completed in early stages [3], Its main structure is shown in FIGURE 2. The basic structural parameters of the micro-motion part designed by the research group are shown in Table 1.…”

Section: A Structural Design Scheme Of Mmcamentioning

confidence: 99%

“…These are developed based on the magnetostrictive effect of giant magnetostrictive materials (GMMs) to form a precise actuator that has the advantages of a high positioning accuracy, large output force, and strong stability. This has great potential application value in the field of precision manufacturing, but its maximum driving stroke can only reach the micron level, which significantly restricts the development of its engineering applications [3].…”

Section: Introductionmentioning

confidence: 99%

Design of Coaxial Integrated Macro–Micro Composite Actuator With Long-Stroke and High-Precision

Gan

et al. 2022

IEEE Access

Macro-micro composite-driving structures are widely used in many applications, and research has been done to improve the associated driving stroke and positioning accuracy. This article proposes a novel macro-micro composite actuator (MMCA) with a long-stroke and high-precision based on a voice coil motor (VCM) and giant magnetostrictive actuator (GMA). However, having a long stroke and high precision is contradictory. To verify this design scheme, the permanent magnet, coil, yoke, and other parts of the MMCA are designed and selected in detail. The axial and radial cross-sections of the macro-motion mechanism are studied using the magnetic equivalent circuit method. The force of the macro-motion coil is obtained based on finite element analysis (FEA). The results from both the FEA and practical experiments show the simulation results are consistent with the theoretical predictions. The maximum force of the MMCA is 53 N, the maximum displacement is 47 mm, the maximum positioning error is only 0.14µm, and the maximum acceleration is approximately 6.7g, which lays a theoretical and technical foundation to provide a high-performance actuator in the field of precision manufacturing.

“…Nonlinear feedforward compensation is a very effective method for solving hysteresis nonlinearities [24][25][26][27]. Reference [28] compensated the output displacement error of a GMM-based positioning table drive system using a dynamic recurrent neural network feedforward control strategy. The experimental results showed that this control strategy has an excellent error compensation effect.…”

Section: Introductionmentioning

confidence: 99%

Research on Hysteresis Modeling and Compensation Method of Giant Magnetostrictive Force Sensor

Shi

et al. 2021

Journal of Sensors

Self Cite

Linearity is an important index for evaluating the performance of various sensors. Under the Villari effect, there may be some hysteresis between the input force and the output voltage of a force sensor, meaning that the output will be multivalued and nonlinear. To improve the linearity and eliminate the hysteresis of such sensors, an output compensation method using a variable bias current is proposed based on the bidirectional energy conversion mechanism of giant magnetostrictive material. First, the magnetization relationship between the input force, bias current, and flux density is established. Second, a nonlinear neural network model of the force-magnetization hysteresis and a neural network model for the compensation control of the force sensor are established. These models are trained using the magnetic flux density-force curve and the magnetic flux density-current curve, respectively. Taking the optimal linearity as the objective function, the bias current under different input forces is optimized. Finally, a bias current control system is developed and an experimental test platform is built to verify the proposed method. The results show that the proposed variable bias current hysteresis compensation method enables the linearity under the return of the force sensor to reach 1.6%, which is around 48.3% higher than under previous methods. Thus, the proposed variable bias current method effectively suppresses the hysteresis phenomenon and provides improved linearity for giant magnetostrictive force sensors.