Experimental Active Vibration Control in Truss Structures Considering Uncertainties in System Parameters

This paper deals with the study of algorithms for robust active vibration control in flexible structures considering uncertainties in system parameters. It became an area of enormous interest, mainly due to the countless demands of optimal performance in mechanical systems as aircraft, aerospace, and automotive structures. An important and difficult problem for designing active vibration control is to get a representative dynamic model. Generally, this model can be obtained using finite element method (FEM) or an identification method using experimental data. Actuators and sensors may affect the dynamics properties of the structure, for instance, electromechanical coupling of piezoelectric material must be considered in FEM formulation for flexible and lightly damping structure. The nonlinearities and uncertainties involved in these structures make it a difficult task, mainly for complex structures as spatial truss structures. On the other hand, by using an identification method, it is possible to obtain the dynamic model represented through a state space realization considering this coupling. This paper proposes an experimental methodology for vibration control in a 3D truss structure using PZT wafer stacks and a robust control algorithm solved by linear matrix inequalities.

[1]  Eric John Ruggiero.  Active Dynamic Analysis and Vibration Control of Gossamer Structures Using Smart Materials , 2002 .

[2]  Karolos M. Grigoriadis,et al.  Low-order control design for LMI problems using alternating projection methods , 1996, Autom..

[3]  Bart De Moor,et al.  N4SID: Subspace algorithms for the identification of combined deterministic-stochastic systems , 1994, Autom..

[4]  Lennart Ljung,et al.  System Identification: Theory for the User , 1987 .

[5]  R. E. Kalman,et al.  New Results in Linear Filtering and Prediction Theory , 1961 .

[6]  Michael J. Brennan,et al.  Design of a Control System using Linear Matrix Inequalities for the Active Vibration Control of a Plate , 2006 .

[7]  R. E. Kalman,et al.  A New Approach to Linear Filtering and Prediction Problems , 2002 .

[8]  Roy Ikegami,et al.  Potential applications of SMART Layer technology for homeland security , 2004, SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring.

[9]  L. H. Yam,et al.  A SYNTHETIC ANALYSIS ON DESIGN OF OPTIMUM CONTROL FOR AN OPTIMIZED INTELLIGENT STRUCTURE , 2002 .

[10]  Fernando Sarracini Júnior,et al.  Reduced Model in H∞ Vibration Control Using Linear Matrix Inequalities , 2006 .

[11]  E. Yaz.  Linear Matrix Inequalities In System And Control Theory , 1998, Proceedings of the IEEE.

[12]  Zhu Chang-sheng.  Active vibration control based on linear matrix inequality for rotor system under seismic excitation , 2008 .

[13]  B. Erkus,et al.  Structural control with dissipative damping devices , 2002, Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301).

[14]  Stephen P. Boyd,et al.  Linear Matrix Inequalities in Systems and Control Theory , 1994 .

[15]  R. E. Kalman,et al.  Contributions to the Theory of Optimal Control , 1960 .