Recursive state estimation for state-saturated systems with two groups of measurements: Handling delayed and degraded sensors

Abstract

In this paper, the recursive fusion estimation problem is investigated for a class of state-saturated systems with two groups of sensors, one with instantaneous measurements and the other with delayed measurements. The phenomena of sensor gain degradations and sensor measurement delays are regulated by a number of mutually independent random variables that are uniformly distributed over known intervals. First, an equivalent model to the original measurement system is constructed by reorganizing the instantaneous and delayed measurements. Then, by turning to a constrained variance method, we construct an upper bound of the estimation error covariance by solving two Riccati-like recursive equations whose dimension is the same as that of the original system. Subsequently, the estimator gain matrix is computed through minimizing the constructed upper bound, and the boundedness of the acquired upper bound is also discussed. Finally, we provide a simulation example to verify the usefulness of our designed fusion estimation algorithm.