An alternative approach to state estimation in linear time-invariant systems

An alternative approach to state estimation problem in linear, time-invariant dynamic systems is presented in this paper. The approach developed first identifies the initial state of the system by using a proportional plus integral parameter identification method. The Lyapunov design technique is used to guarantee the asymptotic convergence of the initial state identifier. A state estimator is then constructed to operate in series with the initial state identifier. The estimator generates an estimate of the unobserved part of the system state. Simulation studies have shown that satisfactory state estimation can be achieved in the presence of measurement or disturbance noise. An example problem is considered to demonstrate the response characteristics of the estimator-identifier combination.