Modelling and optimal control of fed-batch processes using a novel control affine feedforward neural network

Abstract

Many fed-batch processes can be considered as a class of control affine nonlinear systems. In this paper, a new type of neural network for modelling fed-batch processes, called as control affine feedforward neural network (CAFNN), is proposed. For constrained nonlinear optimal control of fed-batch processes, CAFNN offers an effective and simple optimal control strategy by sequential quadratic programming (SQP) where the gradient information can be computed directly from CAFNN. Thus the nonlinear programming problem can then be solved more accurately and efficiently. The proposed modelling and optimal control scheme are illustrated on a nonlinear system and a simulated fed-batch ethanol fermentation process.