SYDec 7, 2015
Cooperative Estimation for Synchronization of Heterogeneous Multi-Agent Systems Using Relative InformationJingbo Wu, Valery Ugrinovskii, Frank Allgöwer
In this paper, we present a distributed estimation setup where local agents estimate their states from relative measurements received from their neighbours. In the case of heterogeneous multi-agent systems, where only relative measurements are available, this is of high relevance. The objective is to improve the scalability of the existing distributed estimation algorithms by restricting the agents to estimating only their local states and those of immediate neighbours. The presented estimation algorithm also guarantees robust performance against model and measurement disturbances. It is shown that it can be integrated into output synchronization algorithms.
SYApr 12, 2016
Distributed Nonlinear Observer with Robust Performance - A Circle Criterion ApproachJingbo Wu, Frank Allgöwer
In this paper, we present a distributed version of the KYP-Lemma with the goal to express the strictly positive real-property for a class of physically interconnected systems by a set of local LMI-conditions. The resulting conditions are subsequently used to constructively design distributed circle criterion estimators, which are able to collectively estimate an underlying linear system with a sector bounded nonlinearity.
SYSep 20, 2015
Distributed Filter Design for Cooperative H-Infinity-Type EstimationJingbo Wu, Li Li, Valery Ugrinovskii et al.
In this paper, we consider the distributed robust filtering problem, where estimator design is based on a set of coupled linear matrix inequalities (LMIs). We separate the problem and show that the method of multipliers can be applied to obtain a solution efficiently and in a decentralized fashion, i.e. all local estimators can compute their filter gains locally and iteratively, with communications restricted to their neighbours. The convergence properties of the iterative algorithm are analyzed and interpreted.
SYJul 2, 2015
Cooperative H-infinity Estimation for Large-Scale Interconnected Linear SystemsJingbo Wu, Valery Ugrinovskii, Frank Allgöwer
In this paper, a synthesis method for distributed estimation is presented, which is suitable for dealing with large-scale interconnected linear systems with disturbance. The main feature of the proposed method is that local estimators only estimate a reduced set of state variables and their complexity does not increase with the size of the system. Nevertheless, the local estimators are able to deal with lack of local detectability. Moreover, the estimators guarantee H-infinity-performance of the estimates with respect to model and measurement disturbances.