Distributed Unknown Input Observers for Discrete-Time Linear Time-Invariant Systems
This paper introduces a Distributed Unknown Input Observer (D-UIO) design methodology that uses a technique called node-wise detectability decomposition to estimate the state of a discrete-time linear time-invariant (LTI) system in a distributed way, even when there are noisy measurements and unknown inputs. In the considered scenario, sensors are associated to nodes of an underlying communication graph. Each node has a limited scope as it can only access local measurements and share data with its neighbors. The problem of designing the observer gains is divided into two separate sub-problems: (i) design local output injection gains to mitigate the impact of measurement noise, and (ii) design diffusive gains to compensate for the lack of information through a consensus protocol. A direct and computationally efficient synthesis strategy is formulated by linear matrix inequalities (LMIs) and solved via semidefinite programming. Finally, two simulative scenarios are presented to illustrate the effectiveness of the distributed observer when two different node-wise decompositions are adopted.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
State Estimation Using a Network of Distributed Observers With Unknown Inputs
State estimation for a class of linear time-invariant systems with distributed output measurements (distributed sensors) and unknown inputs is addressed in this paper. The objective is to design a network of observers su…
State EstimationMinimal-order Appointed-time Unknown Input Observers: Design and Applications
This paper presents a framework on minimal-order appointed-time unknown input observers for linear systems based on the pairwise observer structure. A minimal-order appointed-time observer is first proposed for the linea…
State EstimationDistributed Data-driven Unknown-input Observers for State Estimation
Unknown inputs related to, e.g., sensor aging, modeling errors, or device bias, represent a major concern in wireless sensor networks, as they degrade the state estimation performance. To improve the performance, unknown…
State EstimationData-driven Unknown-input Observers and State Estimation
Unknown-input observers (UIOs) allow for estimation of the states of an LTI system without knowledge of all inputs. In this paper, we provide a novel data-driven UIO based on behavioral system theory and the result known…
Cyber Attack DetectionLEMMAState EstimationSimultaneous State and Unknown Input Estimation for Continuous-discrete Stochastic Systems
This paper considers the simultaneous state and unknown input estimation for continuous-discrete stochastic systems. Two types of approaches (with and without modeling of unknown inputs) which can address this issue are …