Nonlinear control of a batch polymerization reactor with on-line parameter and state estimations

Nonlinear control strategies are suitable for output tracking problems encountered in batch processes, but a precise dynamic model is usually required. In the present work, an adaptive control of input-output linearizable systems, together with an extended Kalman filter, was applied to a simulated batch polymerization reactor to realize the output (monomer conversion) tracking in the presence of model parameter uncertainties. Simulation results show that this technique is robust and the output tracking performance can be ensured even in the presence of large model parameter errors and disturbances