Mixed H2/H∞ Feedback Control of Multivariable Dynamically Substructured Systems

• Main Authors: Wang, Chi-Lun, 王啟倫
• Other Authors: Tu, Jia-Ying
• Format: Others
• Language: zh-TW
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/85488487888968585574

碩士 === 國立清華大學 === 動力機械工程學系 === 102 === 　　Dynamically substructured system testing method divides an original system into several substructures. In the numerical substructure, linear components are simulated via real-time computation. In the physical substructure, a transfer system, which includes actuators and sensors, is installed to interface the numerical and physical parts. During the test, the unwanted dynamic and disturbance noise from the actuator inevitably cause synchronization errors between the outputs of numerical and physical substructures at the interface, and consequently result in unsuccessful tests. Therefore, this study proposes advanced control using the feedforward state-space linear substructuring controller plus the H∞ feedback controller to ensure robust control performance and use the feedforward state-space linear substructuring controller plus the mixed H2/H∞ feedback controller to ensure optimal and robust synchronization. The problem of controller design is transformed to convex optimization problem according to a numerical-substructure-based framework and is solved based on the algorithm provided by MATLAB LMI toolbox to synthesis the controller. 　　A multivariable mass-spring-damper substructured system is developed to verify the proposed control strategy via numerical studies and experiment studies. After comparing the advantages, disadvantages, and robustness of different control system design, this thesis shows that the pole-placement feedback controller has good robust performance but do not know how to choose the pole location; the H∞ feedback controller provide a theoretical way to design the robust controller but there exist some limits in the design process; the mixed H2/H∞ feedback controller provide a theoretical way to design the robust controller using the minimum control energy but it is easy to be affected by the eigenmode matrix of control system.