Nonlinear set membership filter with state estimation constraints via consensus-ADMM

This paper considers the state estimation problem for nonlinear dynamic systems with unknown but bounded noises. Set membership filter (SMF) is a popular algorithm to solve this problem. In set setting, we investigate where requires be constrained by linear or equality. We propose consensus alternating direction method of multipliers (ADMM) based SMF systems. To deal difficulty nonlinearity, instead linearizing system, semi-infinite programming (SIP) approach used transform system into one, which allows us obtain more accurate ellipsoid. For solution SIP, an ADMM proposed handle constraints, and each iteration can solved efficiently. Finally, applied typical numerical examples demonstrate its effectiveness.