Robust Estimation and Adaptive Controller Tuning for Variance Minimization in Servo Systems

For most servo systems, servo performance is quantified by the variance of a system dependent or user defined Servo Performance Signal (SPS). The smaller the variance of the SPS, the better is the performance of the servo control system. However, the variance of the SPS may be determined by both period and non-repeatable disturbances for which the characteristics are often not known a-priori during the servo algorithm design. Moreover, the servo control algorithm is often limited to a standard Proportional, Integral and Derivative (PID) controller as more complicated algorithms are viewed to be less robust. In this paper it is shown how a standard (PID) servo control algorithm can be augmented with an additional feedback loop that can be tuned automatically by estimating the actual disturbance spectra seen in a system dependent or user defined SPS. Adaptation to the disturbance spectra is done in lieu of possible model uncertainties in the servo actuator, guaranteeing stability robustness. As such, the control algorithm provides a Robust Estimation and Adaptive Controller Tuning (REACT) to disturbance spectra to maximize servo performance by minimizing SPS variance in high performance servo systems.