A Design of Neural-Net Based PID Controllers with Evolutionary Computation(Systems and Control)
PID control schemes have been widely used for many industrial processes, which can be represented by nonlinear systems. In this paper a new scheme for neural-net based PID controllers is presented. The connection weights and some parameters of the sigmoidal functions of the neural network are adjusted using a real-coded genetic algorithm. The effectiveness of the newly proposed control scheme for nonlinear systems is numerically evaluated using a simulation example.