A novel analysis and design of a neural network assisted nonlinear controller for a bioreactor

A novel approach is presented for the analysis and the design of a controller for a bioreactor. It is based on the model reference control theory, assisted by a neural network identifier. The control objectives specified in the paper require the controller to be a nonlinear one, however, it is shown that it is stable in the sense of bounded input bounded output and locally stabilizing in the sense of Lyapunov. The feasibility and the efficacy of the proposed approach are tested on the benchmark problem.