Nonlinear state estimation by Extended Parallelotope Set-Membership Filter

In this paper, we propose a state estimation method called the Extended Parallelotope Set-Membership Filter that provides a higher estimation accuracy than existing methods for discrete-time nonlinear systems. The Extended Parallelotope Set-Membership Filter is motivated by the fact that the iteration operations in existing methods generate much redundancy, and will deteriorate the accuracy of the state estimation. To account for this issue, an innovative parallelotope envelope method is proposed for the purpose of reducing the redundancy arising from the process of the noise envelope. In addition, a cofactor separation method is designed for nonlinear systems to obtain a tight envelope of the parallelotope set. Furthermore, we develop a novel parallelotope intersection method suitable for the parallelotope envelope to update the state set. The simulation results verified the effectiveness of the proposed method as well as its superiority over conventional methods in terms of both the maximum and average accuracies of the state estimation. (c) 2021 ISA. Published by Elsevier Ltd. All rights reserved.

Automated summary

In this paper, a state estimation method called the Extended Parallelotope Set-Membership Filter is proposed, which achieves higher estimation accuracy for discrete-time nonlinear systems compared to existing methods. The method reduces redundancy generated by iteration operations in existing methods and improves accuracy through an innovative parallelotope envelope method and cofactor separation method. It also introduces a novel parallelotope intersection method for updating the state set.