摘要

Conventionally, fixed-structure feedback controllers are designed by model-based approaches. However, such controllers are not necessarily ideal and optimal when connecting with the actual plant because of the existence of modeling uncertainty. In this paper, a paralleled damping controller as well as a novel hybrid reference model matching (RMM) and virtual reference feedback tuning (VRFT) approach for parameters' tuning of the controller is presented. The composite damping controller for piezo-actuated nanopositioners is fixed-structure and low-order that uses a high-gain notch filter and a high-pass resonant controller to damp the first resonant peak. The proposed hybrid tuning approach combines an identified system model and a set of experimental input/output data into the parameters' optimization of the proposed composite damping controller. The proposed hybrid approach simplifies the tuning process by decreasing the number of the parameters in the initial values' choosing stage from the whole nine to four. Besides, the application of experimental data improves rejection of model uncertainty. A set of optimal parameters in the controller is obtained using the proposed hybrid design approach. Experimental results with comparisons to built-in PID controller are presented to show the effectiveness of the composite damping controller optimized via the hybrid approach.