Abstract
Dynamically substructured system (DSS) is a hybrid testing technique, which decompose a complex, entire engineering system into numerical and physical substructures. Components are tested via numerical simulation or full-size experiments, and thus the required testing space and costs are reduced. Additional actuator systems, which interface the numerical and physical parts, are required within the physical substructure. A high-quality controller, which is designed to cancel unwanted dynamics introduced by actuators, is important in order to synchronize the numerical and physical outputs and ensure successful tests. The current DSS control literature is divided into geometry-based and dynamics-based strategies. The highly-citied adaptive forward prediction algorithm is defined as the geometry-based control method, which uses curve fitting, least-squares polynomial, and delay differential equations to tailor the control system. This thesis first improves the controller settling performance and numerical conditions by using new direct-compensation and singular value decomposition methods. Then, the least-squares technique is analyzed in order to discuss the control implementation issues. On the other hand, the numerical-substructure-based state-space linear substructuring controller (N-SSLSC) is selected as the example of dynamics-based method for DSS control comparison, which are designed based on typical ordinary differential equations and state-space model. From theoretical analysis, controller development, experimental verification, and using a nonlinear mass-spring-pendulum system as an example, the thesis proves that adaptive forward prediction algorithm possesses inevitable prediction error, the feasibility changes with the wave form, and the adaptive compensation is non-real-time, non-continuous. Therefore, even if adaptive forward prediction is a high-citation compensation method, its controllability, stability, robustness, and feasibility are not comparable with the new N-SSLSC. Furthermore, this thesis also points out that, the theoretical background and feasibility of using time delays and delay differential equations to model the actuator dynamics and to design the DSS controller, requires more stringent validation.