$mu$-Synthesis-Based Adaptive Robust Control of Linear Motor Driven Stages With High-Frequency Dynamics: A Case Study

PROJECT TITLE :

$mu$-Synthesis-Based Adaptive Robust Control of Linear Motor Driven Stages With High-Frequency Dynamics: A Case Study

ABSTRACT:

Existing management approaches for the precision motion control of linear motor driven systems are largely primarily based on rigid-body dynamics of the system. Since all drive systems are subjected to the effect of structural flexible modes of their mechanical parts, the neglected high-frequency dynamics resulting from these structural modes have become the most limiting factor when pushing for better tracking performance and better closed-loop control bandwidth. During this paper, physical modeling and dynamic analysis that take into account the flexibleness of the ball bearings between the stage and the linear guideways are presented with experimental verification. With the gained information of those high-frequency dynamics, a novel $mu$ -synthesis-primarily based adaptive strong management strategy is subsequently developed. The proposed management algorithm uses adaptive model compensation having correct online parameter estimation to effectively accommodate numerous nonlinearity effects and to remodel the tough trajectory tracking control drawback into a robust stabilization problem. The well-developed $mu$-synthesis-based linear strong control technique is then used within the fast feedback control loop style to explicitly handle the sturdy control issue associated with the high-frequency dynamics to achieve higher closed-loop bandwidth for higher disturbance rejection. Comparative experiments are performed and therefore the results show the higher tracking performance of the proposed algorithm over existing ones.

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