DC Programming Based Ellipsoid Bounding Algorithm for Guaranteed State Estimation
This paper presents a new ellipsoid bounding algorithm in the framework of the set-membership filter for real-time state estimation of nonlinear systems with bounded-error assumptions. The nonlinear model of the system is linearized as the normal extended Kalman filter does, but the linearization errors are taken into account and outer bounded strictly by DC programming approach, which will be propagated to the model errors with ellipsoidal approximations. An ellipsoid bounding algorithm composed of ellipsoid summing and iterative ellipsoid-strip intersection steps is proposed to give the feasible set estimation of the states in which they are guaranteed to lie, with some approximations to keep the trade-off between the computation complexity and conservativeness of the whole algorithm. Simulation results are given by comparing our proposed algorithm to the extended set-membership algorithm to show the performance improvements of the new algorithm.
Bounded-error state estimation ellipsoid bounding set-membership DC programming
ZHOU Bo DAI Xianzhong
Key Laboratory of Measurement and Control of CSE (School of Automation, Southeast University),Minist Key Laboratory of Measurement and Control of CSE (School of Automation, Southeast University), Minis
国际会议
The 31st Chinese Control Conference(第三十一届中国控制会议)
合肥
英文
1759-1764
2012-07-01（万方平台首次上网日期，不代表论文的发表时间）