CAJ | 학술논문

在反应溅射工艺中,反应气体流量和沉积速率、反应气体气压、靶电压之间存在迟滞关系.为了保证反应溅射稳定以及保持溅射率高和反应气体利用率高,需要对反应溅射系统进行精确控制.PID神经网络(PIDNN)控制器具有PID控制的快速收敛特点和神经网络的非线性逼近能力,适合对非线性反应溅射系统的控制.本文用PID神经网络(PIDNN)控制器对反应溅射系统进行精确控制.在S.Berg给出的反应溅射系统模型基础上,对反应溅射系统的PIDNN控制进行仿真.仿真结果表明,PIDNN控制器能够稳定反应溅射过程,并且收敛速度较快,输出响应迅速,抗干扰能力强.
재반응천사공예중,반응기체류량화침적속솔、반응기체기압、파전압지간존재지체관계.위료보증반응천사은정이급보지천사솔고화반응기체이용솔고,수요대반응천사계통진행정학공제.PID신경망락(PIDNN)공제기구유PID공제적쾌속수렴특점화신경망락적비선성핍근능력,괄합대비선성반응천사계통적공제.본문용PID신경망락(PIDNN)공제기대반응천사계통진행정학공제.재S.Berg급출적반응천사계통모형기출상,대반응천사계통적PIDNN공제진행방진.방진결과표명,PIDNN공제기능구은정반응천사과정,병차수렴속도교쾌,수출향응신속,항간우능력강.
The reactive sputtering,controlled by the proportion integration differentiation neural network(PIDNN),was simulated on the basis of S.Berg's model.The hysteresis effect,that is,the impact of the changes in gas flow rate on dramatic variations in gas partial pressure,deposition rate and target voltage,was studied to achieve a steady film growth and to make the best use of the reactive gas.The simulated results show that the PIDNN controller does a good job in stabilizing the reactive sputtering with quite a few strengths,including fast convergence,rapid response and strong resistance to interference.