A model reference adaptive system approach for nonlinear online parameter identification

Abstract Dynamical systems, for instance in model predictive control, often contain unknown parameters, which must be determined during system operation. Online, or on-the-fly, parameter identification methods are therefore necessary. The challenge of online is that one continuously estimate parameters as experimental data becomes available. existing techniques the context time-dependent partial differential equations exclude case where depends nonlinearly on parameters. Based a reference adaptive approach, we present an method nonlinear infinite-dimensional evolutionary systems.