Disturbance-Blocking-Based Distributed Receding Horizon Estimation of Flexible Joint Robots

Considering the state monitoring problem of flexible joint robots (FJRs) caused by the easy deformation in practice, a distributed receding horizon estimation algorithm based on disturbance blocks is proposed. Based on distributed consistent receding horizon estimation, the proposed algorithm reduces the computational amount and achieves rapidity by designing the disturbance block and applying it to the process disturbance sequence in the estimation window to reduce the variables related to optimization. By analyzing the feasibility and convergence of the proposed algorithm based on the maximum block length, the assumptions are made under which the existence of equivalent solution to the optimization problem of the algorithm is guaranteed, and the results are extended to the case that the process disturbance can be divided into arbitrary blocks. The simulation results show that the proposed algorithm can effectively shorten the computation time without affecting the estimation error compared with the algorithm without disturbance blocks.