Stability Analysis of Constrained Distributed Nonlinear and Linear Kalman Filters for Dynamical Systems With State Constraints
Xiaoxu Lyu, Peihu Duan, Zhisheng Duan, Zhao Zhang
Abstract
This paper investigates the distributed nonlinear and linear Kalman filters for dynamical systems with state equality constraints via a sensor network, where each sensor estimates the system states by utilizing its own and neighbors' information. First, a constrained distributed extended Kalman filter is proposed, and its stability is proven under feasibility conditions. Then, this constrained distributed extended Kalman filter is relaxed to the linear form, obtaining more precise results under weaker conditions. Moreover, a local constraint fusion algorithm is proposed. Finally, the effectiveness of the proposed filters is demonstrated by two simulation examples.
Topics & Concepts
Kalman filterControl theory (sociology)Constraint (computer-aided design)Stability (learning theory)Nonlinear systemFast Kalman filterExtended Kalman filterInvariant extended Kalman filterLinear systemState (computer science)Computer scienceAlpha beta filterFilter (signal processing)Linear dynamical systemMathematicsAlgorithmMoving horizon estimationArtificial intelligencePhysicsMathematical analysisQuantum mechanicsMachine learningComputer visionGeometryControl (management)Target Tracking and Data Fusion in Sensor NetworksDistributed Control Multi-Agent SystemsDistributed Sensor Networks and Detection Algorithms