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.

Based on the principle of the Villari effect, a force sensor with a giant magnetostrictive material (GMM) as the sensitive element, high linearity, and a large range was studied. A Hall element integrated into the structure was used to detect the magnetic flux density and measure the external force. First, the finite element method was used to verify the validity of the intended magnetization process. Second, an equation for GMM magnetization was derived based on the Jiles–Atherton (J–A) model and the magneto-mechanical coupling effect. The relationships between magnetization and the biased magnetic field, and magnetization and the external force were analyzed under the dynamic coupling model of positive and negative effects. Finally, the influences of various biased magnetic fields and external forces on the sensor output characteristics were determined experimentally. The sensitivity of the designed force sensor was 0.337 mV/N when the bias current was 1.2 A and the preload was 120 N. When a force of 1000 N was applied, the linearity was 0.82%. The experimental results are consistent with the theoretical design values. These research results aid in the development of a highly linear, large-range force sensor. This study provides the theoretical and technical foundations for a high-performance force sensor that can be used in industrial testing.

The giant magnetostrictive actuator (GMA) with giant magnetostrictive material (GMM) as the core component has wide applications in the field of precision drive and control. In this paper, through the analysis of the GMA coil, the loss and temperature rise characteristics of the GMA have been studied. Then, COMSOL Multiphysics software has been used to model the heat source distribution of the GMM actuator, and the factors affecting the working temperature of the GMM rod have been analyzed. Finally, based on the use requirements of the GMA, magnetic field, and internal temperature distribution characteristics, the heat dissipation scheme of the coil is proposed, and the experimental platform of the GMA with a thermal compensation function is built to verify the temperature characteristics and thermal compensation effect. Studying the internal temperature distribution law of the GMA not only has a guiding significance for the temperature control of the actuator and the design of the cooling system but also reduces the influence of the coil thermal effect on the performance of the transducer and lays the foundation for making full use of the GMM’s potential in high-power transducers.

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.