摘要：AbstractFor feedback control designs, one of the fundamental problems is to handle the unknown system dynamics. In this paper, an alternative unknown system dynamics estimator (USDE) with low-pass filter operations is presented based on an invariant manifold method, in which we only need to set a scalar, the filter parameter. The convergence performance and robustness of this USDE are analysed in both the time-domain and frequency-domain. To circumvent the sensitiveness to the measurement noise, a further enhanced USDE (EUSDE) with two-layer of low-pass filters is constructed. With the proposed estimators, all time-varying components, such as unmodeled dynamics, nonlinearities and external disturbances, can be viewed as a lumped unknown system dynamics term and then effectively estimated even in the presence to fair measurement noise. The function of these estimators is the same as the well-known disturbance observer (DOB) and extended state observer (ESO). Hence, they can be easily incorporated into control schemes. Numerical simulation results are presented to show the effectiveness of the proposed estimation schemes.
关键词：KeywordsUnknown system dynamics estimatornonlinear uncertain systemsmeasurement noisefilter operationrobustness
