Interval algorithm for membership-set identification of linear time-invariant system
线性时不变系统集员辨识的区间算法

Based on the assumption of Unknown-But-Bounded (UBB) noise, an interval algorithm is presented for parameter membership-set estimation of a linear time-invariant system. In virtue of interval mathematics, the algorithm objective is to seek the minimal hyper-rectangle (or interval vector) of parameters which is compatible with the measurements and the bounded noise, and its recursive formula are derived. Convergence of the algorithm is analyzed. The presented algorithm can obtain not only the center estimations of parameters, but also the uncertain bounds on them. Numerical examples illustrate its small computation efforts and higher accuracy in comparison with Fogel's algorithm and the least squares algorithm.