Adaptive control of a time delay bioeletrochemical process using neural networks

This paper studies the design and the analysis of a nonlinear and neural adaptive control strategy for a complex nonlinear and time varying wastewater treatment bioprocess. In fact a direct adaptive controller based on a radial basis function neural network used as an on-line approximator to learn the time-varying characteristics of process parameters is developed and then is compared with a classical linearizing controller. The controller design is achieved by using an input-output feedback linearization technique. A realistic case study, which consists of a complex bioprocess resulting from the association of a recycling bioreactor with an electrochemical reactor, is fully analyzed. Computer simulations are included to demonstrate the behaviour and the performance of the proposed controllers.