Development of hardware neural networks generating driving waveform for electrostatic actuator

2020 ◽  
Vol 25 (3) ◽  
pp. 446-452 ◽  
Author(s):  
Takuro Sasaki ◽  
Mika Kurosawa ◽  
Masaya Ohara ◽  
Yuichiro Hayakawa ◽  
Daisuke Noguchi ◽  
...  
Author(s):  
Takuro Sasaki ◽  
Mika Kurosawa ◽  
Yu Usami ◽  
Shinya Kato ◽  
Arisa Sakaki ◽  
...  

AbstractThe authors are studying hardware neural networks (HNN) to control the locomotion of the microrobot. The neural networks chip is the integrated circuit chip of the HNN. We proposed the electrostatic motor that is the new actuator of the microrobot in our previous research. The electrostatic motor used the waveform generator to generate the driving waveform. In this paper, the authors will propose the driving circuit using neural networks chip. The cell body model is the basic component of the neural networks chip that outputs 3 MHz frequency of electrical oscillated pulse waveform. Therefore, large capacitors need to connect outside of the neural networks chip to generate the low-frequency driving waveform. The proposal neural networks chip generates a long delay without using large capacitors. In addition, the neural networks chip generated a two-phase anti-phase synchronized waveform by incorporating a mechanism for adjusting synaptic weight. As a result, the proposal neural networks chip can generate the electrostatic motor’s driving waveform with variable frequency. The frequency of the driving waveform could vary from 40 to 126 Hz.


Sign in / Sign up

Export Citation Format

Share Document