Iterative proportional-integral interval estimation of linear discrete-time systems

An iterative proportional-integral interval estimation strategy for linear discrete-time systems is investigated in this paper. A sequence iterative proportional-integral observers are built on system output and unknown disturbance iterative estimation. With the help of a structure separation technique, a sufficient condition in terms of linear matrix inequality is proposed to make the observer error system be asymptotically stable. The boundary reachability of the observer error system is analyzed via zonotope. Zonotope-based iterative algorithms with and without the output integral are built to generate estimated state intervals. Compared with the existing result, the proposed algorithms render tighter estimation intervals illustrated by a simulation study.