During the reactive sputtering process, due to the hysteresis effect, the sputtering state should be maintained in the transition region of the hysteresis curve which can used to obtain stoichiometric compound films at a high deposition rate. If sputtering state changes, it is impossible to make the sputtering state step back to the original point by manually control the process parameters, because the hysteresis is irreversible. Thus it requires a method of fast feedback to control the sputtering power and the reaction gas flow rate into the chamber. In this paper the PEM (plasma emission monitor) control system and the single neuron self-adaptive PID algorithm have been designed to maintain the sputtering state in proper condition, namely preventing the target from poisoned in the reactive sputtering. The signal acquisition and the controller design were the major parts of the PEM system. The signal acquisition was realized by the optical emission spectrometer. And the single neuron self-adaptive PID controller has been designed in the paper. Using the MATLAB software, the simulation experiments have been done. The output waveforms showed that using traditional non-adaptive PID control algorithm, the overshoot is over 6% and the regulation time is over 1.8s, but using single neuron self-adaptive PID algorithm the overshoot 0 and regulation time 0.5s. Monitoring the target spectral intensity at various reaction gas flow rate, several conclusions could be obtained. The overshoot 6% indicated that the reactive gas flow into the chamber was excessive, the target was poisoned and the sputtering state in chemical mode. And while the overshoot was zero which indicated that the target poisoned was avoided and the reaction ran in defined condition. The PEM using the single neuron self-adaptive PID algorithm responded faster than that using the traditional PID algorithm. The PEM system designed in the paper can effectively avoid the target poisoned and make the reactive sputtering maintain at an ideal state.
A Study on Piezoelectric Ammunition based on Improved Single Neuron Adaptive PID Algorithm