Neural Control based on Incomplete Derivative PID Algorithm

Abstract

In the actual control, complete differential digital PID algorithms have been widely used. But the differential will amplify high-frequency noise. If the differential response is too sensitive, it is easy to cause the control process oscillation, incomplete PID control algorithms can overcome the differential oscillation. Incomplete derivative PID algorithm combined with neural network improves the system control quality, it has the important practical significance. The simulation shows it has good position tracking performance and high robustness. DOI: http://dx.doi.org/10.11591/telkomnika.v11i4.2392