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

Abstract

The output characteristics of giant magnetostrictive actuator (GMA) are affected by many nonlinear factors, such as hysteresis, load, driving frequency and so on, which would lead to lower positioning precision, poorer repeatability, and even fall into nonlinear instability especially in complex dynamic environment. First, the accurate dynamic mathematical model for GMA is established after analyzing its working principle. Then, the inverse model feed-forward compensation fuzzy PD control based on Lyapunov stability is put forward and applied into the GMA control system. The experiment results indicate that Lyapunov direct method that is integrated into inverse model feed-forward compensation fuzzy PD controller can effectively improve the dynamic output features especially in the complex dynamic environment, reduce the root mean square error from 1.275 to 0.332 and maximum error rate from 26.89% to 7.12%, which not only greatly improve performance and expand the application domain of GMA, but also have very important theoretical significance and high application value in modeling and control approach for some hysteresis systems.

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Adaptive Control of a Piezo-Positioning Mechanism With Hysteresis and Input Saturation Using Time Delay Estimation

“…There are four main methods for hysteresis modeling. The first is the physics-based modeling method, which mainly includes Jiles-Atherton model [9], Maxwell-slip model [10] and so on; The second method is based on differential equations, including Bouc-Wen model [11], Duhem model [12], and so on; The third one is based on operators, which includes Preisach model [13], Prandtl-Ishlinskii model [14], etc. The last one is intelligent modeling method based on computational intelligence, such as neural network model [15] and support vector machine model [16].…”

Research on Chaos Response of the Nonlinear Vibration System of Giant Magnetostrictive Actuator

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