Optimal sensors' allocation strategies for a class of stochastic distributed systems

Abstract

The minimum-variance state-estimator for a class of linear distributed parameter systems, with both process and measurement disturbances, is derived. A new algorithm is presented for the optimal simultaneous spatial allocation of sensors. The algorithm minimizes recursively the spatial integral of the covariancc matrix of the error in the state estimates. For time-invariant systems the algorithm leads to the minimization of the spatial integral of the steady-state error covariance matrix. The influence of the system disturbances and measurement noise on these locations is discussed. An illustrative example is given to demonstrate the numerical performance of the algorithm