Magnetic control shape memory alloy actuator displacement control method

Abstract

The invention discloses a magnetic control shape memory alloy actuator displacement control method, and belongs to the field of intelligent material and mechanism modeling and control thereof. The invention aims to combine a neural network with iterative learning control, design an iterative learning controller based on the neural network, and provide a magnetic control shape memory alloy actuatordisplacement control method of a system convergence condition when an initial state of the system changes in a bounded range. The method comprises the steps that a Volterra series model capable of describing the hysteresis nonlinearity related to the magnetic control shape memory alloy actuator rate is built, and a kernel function of Volterra series is built through a neural network; a neural network fitting iterative learning controller is adopted, and convergence conditions of the system when the initial state of the system changes in a bounded range are given. According to the method, application conditions of iterative learning control are broadened, an actual application environment is better met, the robustness of iterative learning control is improved, and the control quality is improved.

Description

technical field [0001] The invention belongs to the field of intelligent material and its mechanism modeling and control. Background technique [0002] Since the 1990s, with the vigorous development of the precision manufacturing industry, the traditional machining and manufacturing methods can no longer meet the needs of the rapid development of modern industry, and people have put forward new requirements for high-precision, high-resolution positioning technology. Actuators with emerging smart materials such as piezoelectric ceramics, shape memory alloys, and giant magnetostrictive materials as core devices have become a research field in the field of high-precision manufacturing in various countries in recent years because of their micro-nano precision positioning capabilities. hotspots. [0003] The magnetically controlled shape memory alloy actuator is a high-precision micro-positioning mechanism that uses the magnetic shape memory effect of the magnetically controlled...

AI Technical Summary

Problems solved by technology

However, the hysteretic nonlinearity inside the magnetic control shape memory alloy material seriously restricts its application in various fields.

In order to solve the problem of complex hysteresis and nonlinearity in the displacement of magnetically controlled shape memory alloy actuators, and realize the micronano-level precision positioning control of magnetically controlled shape memory alloy actuators, it is necessary to propose more effective control strategies and design controllers with excellent performance

[0004] Magnetically controlled shape memory alloy actuators have the characteristics of complex hysteresis dynamic characteristics and unknown system parameters, so traditional control methods are difficult to achieve satisfactory control effects

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