Hysteresis nonlinearity modeling and position control for a precision positioning stage based on a giant magnetostrictive actuator

Abstract

A precision positioning stage based on giant magnetostrictive actuator (PPS-GMA) shows nonlinear displacement when it is used in the field of precision positioning control. To improve the defect, the Jiles-Atherton hysteresis model and the dynamic recurrent neural network (DRNN) feed forward-fuzzy PID feedback control strategy were adopted. An accurate hysteresis nonlinearity model of PPS-GMA was established with the Jiles-Atherton model and its parameters were identified using the particle swarm optimization (PSO) algorithm. A dynamics inverse model of the PPS-GMA was established with the DRNN learning method to compensate the hysteresis nonlinearity characteristic. A fuzzy PID feedback control was used to compensate for the mapping error of DRNN. Using these control methods, the positioning accuracy of the precision positioning stage was improved. The simulation and experimental results show that the Jiles-Atherton hysteresis model can describe the hysteresis nonlinear characteristic of the precision positioning stage, the PSO algorithm has high precision for parameter identification, the DRNN feed forward-fuzzy PID feedback control strategy can effectively eliminate the nonlinear characteristics of the PPS-GMA, which has practical significance for improving the positioning accuracy of the PPS-GMA.

Temperature compensation design and experiment for a giant magnetostrictive actuator

“…A GMM has a larger thermal expansion coefficient, and the magnetostriction coefficient is the same order of magnitude; this indicates that the thermal elongation of the GMM will considerably affect the precision of the giant magnetostrictive actuator (GMA) in a negative manner. For GMA applications requiring precise positioning [4][5][6][7] , the rise in temperature will have a direct impact on the accuracy of the GMA positioning; therefore, steps must be taken to eliminate or suppress the adverse effects due to the increasing temperature.…”

Research on Control Strategy in Giant Magnetostrictive Actuator Based on Lyapunov Stability

“…So, how to establish an accurate mathematic model and apply it into real-time control system with lower memory consumption is the key point. Jiles-Atherton (J-A) model has a better description of hysteresis, is easier to be solved and consumes less memory in the control algorithm [13]- [15]. J-A dynamic model was established by Jiles DC and Atherton DL based on domain wall theory to describe internal characteristics of ferromagnetic materials.…”

Compensation control strategy of hybrid driven three-dimensional elliptical vibration assisted cutting system based on piezoelectric hysteresis model

“…Regarding the compensation control strategy that accommodates the hysteresis characteristics of the system, scholars tend to adopt the most suitable control strategy according to the differences of the system under study, such as adaptive sliding mode [13][14][15][16] and PID feedback control strategy. 17,18 As controlled objects become diversified and complex, higher-order control strategies are increasingly applied. Jian et al 19 proposed a new control strategy that combines iterative learning control (ILC) with hysteresis direct inversion to compensate for the nonlinearity and uncertainty of the system.…”