A design of neural-net based predictive PID controllers

PID control schemes have been widely used for various real control systems. However, in practice, since it is difficult to find suitable PID gains, a lot of research has been reported with respect to tuning schemes of PID gains. In this paper, a design scheme of neural net-based PID controllers is proposed for nonlinear systems. The modeling error between a linear nominal model and a controlled object is compensated by a multilayered neural network whose outputs are given as additive PID gains. Furthermore, the fixed PID gains are calculated for the linear nominal model based on a generalized predictive control scheme.