Robust Stability and Performance Analysis for Multi-actuator Real-Time Hybrid Substructuring

Real-time hybrid substructuring (RTHS) is a relatively new method of vibration testing for characterizing the system-level performance of physical components or substructures. With RTHS, the coupled system is partitioned into physical and numerical substructures and interfaced together in real-time as cyber-physical system similar to hardware-in-the-loop testing. Control actuation and sensing is used to enforce the compatibility and equilibrium conditions between the physical and numerical substructures. Since RTHS involves a feedback loop, the frequency-dependent magnitude and inherent time delay of the actuator dynamics can introduce inaccuracy and instability. This paper presents a robust stability and performance analysis method for multi-actuator RTHS based on robust stability theory for multiple-input-multiple-output (MIMO) feedback control. This analysis method involves casting the actuator dynamics as a multiplicative uncertainty and applying the small gain theorem to derive the sufficient conditions for robust stability and performance. The attractive feature of this robust stability and performance analysis method is that it accommodates linearized modeled or measured frequency response functions for both the physical substructure and actuator dynamics.

[1]  F. Jin,et al.  Delay-dependent stability and added damping of SDOF real-time dynamic hybrid testing , 2010 .

[2]  James M. Ricles,et al.  Adaptive time series compensator for delay compensation of servo‐hydraulic actuator systems for real‐time hybrid simulation , 2013 .

[3]  James M. Ricles,et al.  Tracking Error-Based Servohydraulic Actuator Adaptive Compensation for Real-Time Hybrid Simulation , 2010 .

[4]  Ian Postlethwaite,et al.  Multivariable Feedback Control: Analysis and Design , 1996 .

[5]  Martin S. Williams,et al.  REAL-TIME SUBSTRUCTURE TESTS USING HYDRAULIC ACTUATOR , 1999 .

[6]  Sung Jig Kim,et al.  Real-time hybrid simulation of a complex bridge model with MR dampers using the convolution integral method , 2013 .

[7]  James M. Ricles,et al.  Stability and accuracy analysis of outer loop dynamics in real‐time pseudodynamic testing of SDOF systems , 2007 .

[8]  James M. Ricles,et al.  Stability analysis for real‐time pseudodynamic and hybrid pseudodynamic testing with multiple sources of delay , 2008 .

[9]  Graham C. Goodwin,et al.  Control System Design , 2000 .

[10]  Xiuyu Gao,et al.  Real time hybrid simulation: from dynamic system, motion control to experimental error , 2013 .

[11]  D. Wagg,et al.  Real-time dynamic substructuring in a coupled oscillator–pendulum system , 2006, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[12]  Arun Prakash,et al.  Establishing a predictive performance indicator for real‐time hybrid simulation , 2014 .

[13]  James M. Ricles,et al.  Large-scale real-time hybrid simulation for evaluation of advanced damping system performance , 2015 .

[14]  Juan Carrion,et al.  Model-Based Strategies for Real-Time Hybrid Testing , 2007 .

[15]  Masayoshi Nakashima,et al.  Real-time on-line test for MDOF systems , 1999 .

[16]  David J. Wagg,et al.  Robust real-time substructuring techniques for under-damped systems , 2007 .

[17]  David J. Wagg,et al.  Stability analysis of real‐time dynamic substructuring using delay differential equation models , 2005 .

[18]  Y. Namita,et al.  Real‐time hybrid experimental system with actuator delay compensation and its application to a piping system with energy absorber , 1999 .

[19]  James M. Ricles,et al.  Analysis of actuator delay compensation methods for real-time testing , 2009 .

[20]  Billie F. Spencer,et al.  Model-Based Framework for Real-Time Dynamic Structural Performance Evaluation , 2012 .

[21]  Abbas Emami-Naeini,et al.  Feedback Control of Dynamic Systems (6th edition) , 2010 .