Transient-Performance-Guaranteed Robust Adaptive Control and Its Application to Precision Motion Control Systems

This paper investigates the adaptive tracking-control problem for a class of nonlinear systems with uncertain parameters, disturbance, and unmodeled dynamics. A novel model reference adaptive control (MRAC) with external filter is proposed to not only stabilize the error system but also guarantee its transient performance. The proposed control strategy can mathematically ensure designable $L-{\infty}$ norm bounds of the difference between the original model's and the reference model's state and their control inputs as well. On the other hand, the reference model, which is deemed as a linear time-invariant (LTI) system, can be designed to run in a desired performance level by selecting a suitable filter in the control structure. Another improvement emphasizes that the proposed approach can attain the above performance without using a high-static adaptation gain, which avoids the possible negative effects in the context of robustness. Finally, simulation on a high-accuracy motion-system model driven by a direct-current (dc) motor is given to verify the proposed approach, and the effectiveness is shown based on the simulation curves and analysis.