The new approach of system identification through Liapunov functions is applied to stochastic systems. We demonstrate the possibility of constructing a consistent identification scheme to estimate the system parameters in the presence of noise, providing that the input is persistently exciting. A practical identification scheme is provided to obtain estimates with bounded estimation errors, where the bound can be made arbitrarily small.
ASJC Scopus subject areas
- Control and Systems Engineering
- Computer Science Applications