A Self-Tuning PID Controller Fused Artificial Neural Networks

摘要

Recently, neural network techniques have widely used in adaptive and learning control schemes for nonlinear systems. However, generally, it costs a lot of time for learning in the case applied in control systems. Furthermore, the physical meaning of neural networks constructed as a result, is not obvious. In this paper, a design method of self-tuning PID controllers is proposed, which has a fusional structure of self-tuning and neural network schemes. This method enables us to understand a physical meaning of the control parameters, and also to adjust PID gains quickly.