Contact Information
North Carolina State University
Department of Mechanical and Aerospace Engineering
Campus Box 7910
3211 Broughton Hall
2601 Stintson Drive
Raleigh, NC, 27695
USA

Office Phone: 919 515 5260
Lab: 919 515 5686
Home: 919 370 9268
Mobile: +358 50 348 7902

E-mail: Kari.Tammi@vtt.fi

Publications
K. Tammi, G. Buckner, J. Kortelainen, “Magneto-Rheological Squeeze-Film Damper for Semi-Active Control of Rotor Vibration”, accepted, proceedings of the 9th International Conference on Motion and Vibration Control, Munich, Germany, September 15 - 18, 2008.

Tammi K. Identification and active feedback-feedforward control of rotor. International Journal of Acoustics and Vibration. International Institute of Acoustics and Vibration. Vol. 12, Number 1. 2007. pp. 7–14.

Battaglia M., Orava R., Tammi K, et al. High-resolution hybrid pixel sensors for the e+e- TESLA linear collider vertex detector. Nuclear Instruments and Methods in Physics Research A 447. 2000. pp. 202-209.

Daley S., Hätönen J. & Tammi K. Instantaneous harmonic vibration control of a flexible rotor. Proceedings of the International Symposium on Active Control of Sound and Vibration (Active 2006). Adelaide 18-20 Sept. 2006.

Tammi K., Hätönen J. & Daley S. Novel adaptive repetitive algorithm for active vibration control of a variable-speed rotor. Proc. of 8th International Conference on Motion and Vibration Control (MOVIC 2006), Daejeon, Korea. 2006. pp. 386-381.

Hätönen J., Daley S., Tammi K & Zazas I. Instantaneous Harmonic Control – Convergence Analysis and Experimental Verification. Proc. of Thirteenth International Congress on Sound and Vibration (ICSV13), Vienna. International Institute of Acoustics and Vibration. 2006.

Tammi K., Hätönen J. & Daley S. Active Vibration Control of a Rotor Using a Novel Adaptive Repetitive Control Algorithm. Proc. of Thirteenth International Congress on Sound and Vibration (ICSV13), Vienna. International Institute of Acoustics and Vibration. 2006.

Tammi K. Experiments on Shape Memory Alloy actuator and practical applicability considerations. VTT Symposium 244. Edited by Ritschkoff A-C., Koskinen J. & Paajanen M. VTT. Espoo. 2006. pp. 71-81.

Tammi K. Combined feedback-feedforward control for rotor vibrations. Proceedings of Twelfth International Congress on Sound and Vibration (ICSV12), Lisbon. International Institute of Acoustics and Vibration. 2005.

Tammi K., Hynninen A. & Klinge P. An active vibration control study for an electrical machine. Proceedings of Seventh International Conference on Computational Structures Technology (CST2004), Lisbon, 7-9 Sept. 2004. Civil-Comp Press. 2004.

Bei Lu (2005), Ph.D. from North Carolina State University. Currently an Assistant Professor at California State University, Long Beach CA.

Research
Intelligent Linear Parameter-Varying Control of An Active Magnetic Bearing – Rotor System (Sponsor: NSF) - This research is to develop linear parameter-varying (LPV) controllers for flexible high-speed rotors supported on active magnetic bearings (AMBs). The AMB – rotor system is modeled as an LPV system. A novel artificial neural network, called confidence interval network (CIN), is applied to learn parameter-dependent uncertainty weighting function, which is incorporated into the LPV control synthesis to account for unmodeled dynamics. The LPV controller is scheduled in real time according to the rotational speed, and can guarantee stability and performance for all speeds within a given speed range.

Publications
B. Lu, H. Choi, G. Buckner, “Linear Parameter-Varying Techniques for Control of A Magnetic Bearing System", accepted, Control Engineering Practice

B. Lu, H. Choi, G. D. Buckner “LPV Control Design and Experimental Implementation for a Magnetic Bearing System”, Proceedings of the 2006 American Controls Conference, Minneapolis, MN, June 2006.

E-mail: blu3@csulb.edu

Links: http://www.csulb.edu/colleges/coe/mae/views/personnel/fulltime_adj/lu.shtml

Soheil Saadat (2004), Ph.D. from North Carolina State University. Currently a Project Manager of Sensors & Structural Diagnostics, CTL Group, Skokie, IL.

Research Topic
An Intelligent Parameter Varying Approach For Structural Health Monitoring and Damage Detection - Civil structures are prone to damage and deterioration during their service life, particularly when they are subject to seismic excitation. To ensure structural integrity it is desirable to monitor and detect the existence, location, and extent of any damage. Common health monitoring and damage detection practices involve systematic visual inspections by experienced engineers. The ever-increasing complexity of civil structures makes the practicality and reliability of such manual approaches questionable, particularly following natural disasters like earthquakes. For this reason, the development of reliable, automated monitoring techniques has received increasing attention over the last decade. Among damage detection methodologies, there has been increasing interest in the use of artificial neural networks for identifying the presence, location, and extent of damage in structures. Typically, the pattern recognition and function approximation capabilities of artificial neural networks are utilized to detect and locate damage by comparing response measurements from damaged and undamaged structures. Such approaches, however, may fail if the response of the damaged structure moves beyond the representative domain of the trained neural network. In this research, a novel “Intelligent Parameter Varying” (IPV) modeling and identification technique is used to identify damage in a three-story structure with elastic, elasto-plastic, and hysteretic restoring forces. This IPV technique reveals the evolution of damage through the identification of structural restoring forces, rather than comparing the dynamic response characteristics of the structure with some ‘healthy' reference model. A direct comparison between the IPV technique and common wavelet transform techniques is presented.

Publications
S.A. Saadat, G.D. Buckner, and M.N. Noori, “Structural System Identification and Damage Detection using the Intelligent Parameter Varying Technique: An Experimental Study”, Structural Health Monitoring, vol. 6, no. 3, pp. 231-243, 2007.

S. Saadat, M. N. Noori, G.D.Buckner, T. Furukawa and Y. Suzuki, “Structural health monitoring and damage detection using an intelligent parameter varying (IPV) technique”, International Journal of Non-Linear Mechanics, vol. 39, no. 10, pp. 1687-1697, 2004.

S. Saadat, G.D. Buckner, T. Furukawa, and M.N. Noori, “An Intelligent Parameter Varying (IPV) Approach for Non-linear System Identification of Base Excited Structures”, International Journal of Non-Linear Mechanics, vol. 39, no. 6, pp. 993-1004, 2004.

S. Saadat, G.D. Buckner, and M.N. Noori, “An Intelligent Parameter Varying Approach For Structural Health Monitoring and Damage Detection”, Proceedings of the ICASP9 Conference, San Francisco, CA, July 6-9, 2003.

S. Saadat, G.D. Buckner, T. Furukawa, and M.N. Noori, “Non-linear System Identification of Base Excited Structures using an Intelligent Parameter Varying (IPV) Modeling Approach”, SPIE's 10th Annual International Symposium on Smart Structures and Materials, March 2003.

S. Saadat, F.G. Yuan, M.N. Noori, and G.D. Buckner, “Estimation of Wind Loads on Structures”, Proceedings of the 15th ASCE Engineering Mechanics Conference, no. 557, June 2002.

E-mail: ssaadat@ctlgroup.com