A Design of Neural-Net Based PID Controllers with Evolutionary Computation

Michiyo SUZUKI  Toru YAMAMOTO  Toshio TSUJI  

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E87-A    No.10    pp.2761-2768
Publication Date: 2004/10/01
Online ISSN: 
Print ISSN: 0916-8508
Type of Manuscript: PAPER
Category: Systems and Control
PID control,  neural network,  genetic algorithm,  

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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.