Hybrid neural network/conventional control of a benchmark process control problem

We combine neural network and conventional controllers to form a hybrid that achieves very accurate control in both stable an unstable operating regions of a simulated bioreactor. The neural network handles nonlinearity and generalizes to cover both regions. The conventional controller eliminates the offset error incurred by generalization