Estimation of State Space Model of a Power Hydraulic System Using Subspace Identification Algorithm

A data-driven modeling approach has been proposed in this paper where the state space of the whole hydraulic system is estimated from the measured input and output data. Both the traditional (TSID) and parsimonious subspace identification have been used in estimation process, and one trade-off is observed between TSID and PARSIM that TSID is a more efficient estimation algorithm where no step change occurs, but with a step change in response, PARSIM estimates both efficient and robust estimation in finite and asymptotic sense.