Adaptive nonlinear observers of microbial growth processes

Adaptive nonlinear observers are studied for a class of biochemical processes expressed by a nonlinearly parametrized Monodʹs growth model. Simultaneous on-line estimations of system states and parameters are performed for the plants with unknown parameters. Asymptotic nonlinear observers and parameter updating laws are constructed using Lyapunov stability technology. A persistence of excitation (PE) condition is investigated for the parameter convergence of the adaptive observers. Numerical simulations are provided to show the effectiveness of the proposed scheme.