Distributed semi-cooperative filter for a nonlinear multi-agent system with heterogeneous and homologous unknown inputs

In this study, the simultaneous estimation of the states and unknown inputs for a nonlinear multi-agent system with homologous and heterogeneous unknown inputs is performed. The decentralized sub-filter is used to estimate the states and heterogeneous unknown inputs, whereas the distributed sub-filter is used to estimate the homologous unknown inputs. The extended Kalman filter is used to solve the estimation problem for nonlinear systems. Compared with previous studies, the distributed solution is improved to relax the existence of the homologous unknown input sub-filter. Moreover, the updating method of the residual generator is improved to relax the heterogeneous unknown input sub-filter. The practical problem of estimating the state of charge and temperature of the battery pack is used to verify the effectiveness of the proposed filter.