A subspace algorithm for simultaneous identification and input reconstruction

摘要

This paper considers the concept of input and state observability, that is, conditions under which both the unknown input and initial state of a known model can be determined from output measurements. We provide necessary and sufficient conditions for input and state observability in discrete-time systems. Next, we develop a subspace identification algorithm that identifies the state-space matrices and reconstructs the unknown input using output measurements and known inputs. Finally, we present several illustrative examples, including a nonlinear system in which the unknown input is due to the endogenous nonlinearity.