Identifier-Based Adaptive Robust Control for Servomechanisms With Improved Transient Performance

This paper focuses on the adaptive robust control (ARC) for servomechanisms whose dynamic models are subject to unknown parameters, disturbance, and parameter sudden changes. To improve the control performance of the traditional ARC, a novel identifier-based ARC (IFARC) scheme is proposed. In this scheme, an identifier is utilized to accelerate the parameter tuning process and to heighten the accuracy of parameter estimation. A switching logic component based on a given performance index is introduced to select the better parameter estimate vector from those provided by the identifier and the adaptation law. As a result, transient performance can be improved according to the certainty equivalence principle. In addition, the exact reconstruction of the unknown parameters and exponential decay of the tracking error can be achieved under certain conditions. The stability and performance of IFARC are theoretically analyzed. Finally, simulation results show that the IFARC can achieve favorable tracking performance.