Desired Dynamics-Based Generalized Inverse Solver for Estimation Problems

An important task for estimators is to solve the inverse. However, as designs of different solving inverse vary widely, it difficult engineers be familiar with all their properties and design suitable situations. Therefore, we propose a more structurally unified functionally diverse estimator, called generalized solver (GIS). GIS inspired by desired dynamics control systems understanding It similar closed-loop system, consisting nominal models an error-correction mechanism (ECM). The can model-based, semi-model-based, or even model-free, depending on prior knowledge system. In addition, ECM based parameterization following simple meaningful rule, where states are directly used in accelerate convergence GIS. A case study considering rotary flexible link shows that greatly improve noise suppression performance lower loss dynamic estimation performance, when compared other common observers at same bandwidth. Moreover, performances three approaches (i.e., model-free) almost under parameters. These results demonstrate strong robustness (although means uniform method). Finally, some cases studied, including comparison DOB ESO, order illustrate approximate equivalence