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Name of experiment：single-neuron adaptive hysteresis compensation for piezoelectric ceramic actuator based on Hebb learning rules

Research direction：micro-nano positioning

Content of experiment: the hysteresis nonlinearity of piezoelectric ceramic actuator greatly reduces its motion accuracy. The difficulty of modeling and compensation of hysteresis is increased because of the time - varying and asymmetric characteristics of hysteresis. In this experiment, single-neuron adaptive control method is used to compensate the hysteresis nonlinearity of the piezoelectric ceramic actuator, so as to improve the trajectory tracking performance of the piezoelectric ceramic actuator.

Purpose of experiment：verify the performance of hysteresis compensation algorithm

Test equipment: DSPACE real-time acquisition module, dynamic bridge strain gauge, high frequency power amplifier ATA-4052

Experimental process: 

The measured object is  PZS001 piezoelectric ceramic driver produced by Thorlabs. The maximum displacement is 12.925μm at the maximum driving voltage of 100V. The ATA-4052 amplifier is used to control the piezoelectric amplification into the driving voltage of the piezoelectric ceramic driver. The piezoelectric ceramic driver is equipped with four resistance strain gauges, which constitute a four-bridge resistance strain gauge. The SDY2105 bridge amplifier is used to measure the deformation of the piezoelectric ceramic driver. The hardware connection diagram of the test system is shown below:

The test program is written in Matlab/Simulink and run by Microlabbox real-time controller produced by dSPACE company. Testing process is as follows: first, generate a sine wave signal from 0 to 10 v in the control program. After amplification, the piezoelectric ceramic is driven to move forward and back, and the control signal and displacement signal are measured in real time by Microlabbox. According to the characteristics of the piezoelectric ceramic, the single-neuron adaptive compensation algorithm is written, and the performance of the algorithm is tested by the equipment.

The Simulink code of the test program is shown below：

Result of experiment:

The effectiveness of the control algorithm in tracking sinusoidal trajectory and triangular trajectory is tested respectively. For sinusoidal trajectories, the single-neuron adaptive compensation algorithm can effectively eliminate the influence of hysteresis nonlinearity. Compared with the conventional PID control, the single-neuron adaptive compensation algorithm has higher adaptability and robustness, and can eliminate hysteresis nonlinearity well for sinusoidal trajectories within 50Hz. For triangular trajectories, the single neuron adaptive compensation algorithm can also achieve similar results. The experimental results are shown in the figure below:

The role of the amplifier in this experiment:

The control signal is weak current and its voltage range is 0-10V, which is not enough to drive the piezoelectric ceramic driver. The control signal is amplified by an amplifier to generate a driving voltage to drive the piezoelectric ceramic.