Research On The Key Technologies Of Giant Magnetostrictive Actuator Drive System

Giant magnetostrictive material has unique characteristics of large strains, great output force, high power density, fast response and high reliability. Actuator based on giant magnetostrictive material show a good prospect in the areas of precision machining, precision positioning, active vibration control, robotics, and micro-electromechanical systems. However, there is a strong nonlinearity in actuator due to the inherent hysteresis characteristics of the giant magnetostrictive material, which makes it difficult to precisely control the actuator and thus hinders the development and applications of such actuator. How to solve the nonlinear problems in the giant magnetostrictive actuator system and to further improve the output accuracy of the actuator system has become a research of popularity.The giant Magnetostrictive actuator drive system is both the power source to drive the giant magnetostrictive material to complete the retractable action and the controller to achieve the real-time control of the expansion volume. Therefore, the giant Magnetostrictive actuator drive system is the core of the giant magnetostrictive actuator system and the performance of such drive system exerts an important impact on the output of the actuator system. This paper analyzes in depth the research status quo of the giant magnetostrictive actuator drive system, points out the shortcomings of such drive system in the areas of power drive, system modeling and control strategies, and applies the power drive technology, nonlinear dynamic model and its linearization, order reduction of the high-order model, and the system identification to the giant magnetostrictive actuator driver based on the in-depth study of the giant magnetostrictive actuator power driver technology, system modeling and nonlinear control. At the same time, a magnetostrictive actuator drive system is also developed, which achieves the accurate tracking of the system output using the generalized predictive control strategy, thus improving the control accuracy under the condition of a wide input range. The main contents of this paper are as follows:1. Analyzing the operating principle of the giant magnetostrictive actuator, establishing the non-linear dynamic model for the giant magnetostrictive actuator based on the hierarchical modeling principle considering the electric-magnetic-mechanical coupling characteristics of the giant magnetostrictive actuator:using polynomial fitting method of handling the relationship between the giant magnetostrictive material magnetization and current non-linear characteristic which is different from the past modeling theories of Preisach model, Jile-Atheton model or free-energy hysteresis model, thus smoothing the non-linear curve, reducing the noise impact, and reducing the operation time to achieve the purposes of fast, real-time control; analyzing the dynamic mechanism of Terfenol-D rods and generalized loads of the giant magnetostrictive actuator consisting of non-linear elastic materials using Lagrange equation with dissipative forces and establishing the dynamic model for the giant magnetostrictive actuator.2. Analyzing the non-linear dynamic model for the giant magnetostrictive actuator, getting the relationship between sub-models, then linearizing such non-linear model and reducing the order of the high-order linear model using the balance-realizing theory:Reordering the modules according to the characteristics of each sub-model based on the hierarchical modeling theory; using pure time delay unit instead of the nonlinear unit of the magnetization hysteresis module combining the power drive module, coil magnetic module, magnetic drive module and structural dynamics module to get the linear unit and thus achieving the transformation from the non-linear model to the linear model for the magnetostrictive actuator; carrying out order-reduction research on the linear model of the magnetostrictive actuator system using the balance-realizing theory, proposing the balance-realizing algorithm for the linear model of the magnetostrictive actuator system, analyzing the error of each order-reduction system using order-reduction methods of balance truncation and balance residual, indicating the reasonability of the magnetostrictive actuator system model reducing to second-order model.3. Researching online identification of parameters of the giant magnetostrictive actuator drive system model according to the needs for the generalized predictive control of the giant magnetostrictive actuator system:Identifying the influencing factors of the power drivers, mechanical structures of the actuator and hysteresis nonlinearity as the identification objects, proposing the controlled-object online parameter identification strategy of the giant magnetostrictive actuator system based on the forgetting-factor recursive least squares method and establishing the discrete parameter identification model of the giant magnetostrictive actuator system with online identification of the giant magnetostrictive actuator system based on the forgetting-factor recursive least squares method.4. As for the precise control of the giant magnetostrictive actuator drive system, using a generalized predictive control strategy for tracking control of the giant magnetostrictive actuator system:Studying multi-step prediction, rolling optimization and feedback correction strategies of the generalized predictive control theory, deriving the optimum output prediction of the generalized predictive control by application of the Diophantine equations and acquiring the control law of the generalized predictive control by solving its objective function, analyzing the parameter selection strategy of the generalized predictive control algorithm; Analyzing by simulation the setting values and output simulation curve, the error curve and the control voltage curve under different setting signals, verifying the reasonability of giant magnetostrictive actuator controller design based on the generalized predictive control algorithm.5. Having developed the giant magnetostrictive actuator drive system prototype, detailing the process of design and development and performance testing for the giant magnetostrictive actuator drive system, verifying the feasibility and effectiveness of the giant magnetostrictive actuator drive system proposed in this paper:Analyzing theoretically the spectral distribution of the output voltage harmonics of the half-bridge chopper inverter circuit using the Fourier series, comparing the LC filter and the LCCR filter characteristics, and pointing out the shortcomings of the LC filter, thus proposing using the LCCR filter instead of the LC filter with the derivation of parameters design formulas for the LCCR filter with inductive load conditions.Designing the power driver of the giant magnetostrictive actuator based on the half-bridge chopper inverter circuit, improving the stability and response speed of the system by using the12control method; designing the hardware platform for the giant magnetostrictive actuator drive system, developing the algorithm library for the generalized predictive control of the giant magnetostrictive actuator non-linear system, designing a graphical user application at the controller for controlling and debugging the giant magnetostrictive actuator driving system. Verifying experimentally the feasibility and effectiveness of the giant magnetostrictive actuator drive system designed in this paper.This successful study in this paper provides a new and effective way of implementing the giant magnetostrictive actuator nonlinear control and presents a solution to solving the key technological problems in the precise control in the giant magnetostrictive actuators.