Computationally Efficient Design of Semiactive Structural Control in the Presence of Measurement Noise
Designing control strategies for smart structures, such as those with semiactive devices, is complicated by the nonlinear nature of the feedback control, secondary clipping control, and other additional requirements such as device saturation. The authors have previously developed an approach for semiactive control system design, based on a nonlinear Volterra integral equation (NVIE) that provides a low-order computationally efficient simulation of such systems, for state feedback semiactive clipped-optimal control. This paper expands the applicability of the approach by demonstrating that it can also be adapted to accommodate more realistic cases when, instead of full-state feedback, only a limited set of noisy response measurements is available to the controller. This extension requires incorporating a Kalman filter estimator, which is linear, into the nominal model of the uncontrolled system. The efficacy of the approach is demonstrated by a numerical study of a 100-DOF frame model, excited by a filtered Gaussian random excitation, with noisy acceleration sensor measurements to determine the semiactive control commands. The results show that the proposed method can achieve more than two orders of magnitude improvement in computational efficiency while retaining a comparable level of accuracy.
Keywordssmart structures semiactive control nonlinear Volterra integral equation clipped-optimal control Kalman filter
The authors gratefully acknowledge the partial support of this work by the National Science Foundation through awards CMMI 08-26634, 11-00528 and 11-33023. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. The authors also acknowledge support of a Viterbi Doctoral Fellowship at the University of Southern California.
- 6.Kamalzare M, Johnson EA, Wojtkiewicz SF, Zheng Y (2012) Computationally efficient parameter studies for semiactive control design. In: 2012 joint conference of the engineering mechanics institute and the 11th ASCE joint specialty conference on probabilistic mechanics and structural reliability, Notre Dame, IN, June 2012Google Scholar
- 7.Kamalzare M, Johnson EA, Wojtkiewicz SF (XXXX) Computationally efficient design of optimal strategies for controllable damping devices. Struct Contr Health Monit, SubmittedGoogle Scholar
- 9.Kalman R, Bucy R (1961) New results in linear filtering and prediction. J Basic Eng (ASME) 83(D):95–108Google Scholar
- 10.Kamalzare M, Johnson EA, Wojtkiewicz SF (XXXX) Computationally efficient design of optimal output feedback strategies for controllable passive damping devices. Smart Mater Struct, SubmittedGoogle Scholar
- 11.Skinner RI, Robinson WH, McVerry GH (1993) An introduction to seismic isolation. Wiley, ChichesterGoogle Scholar
- 13.Reinhorn AM, Soong TT, Wen CY (1987) Base-isolated structures with active control. In: Proceedings (ASME) PVP conference, pp 413–420, San Diego, CA, 1987Google Scholar
- 14.Reinhorn AM, Riley M (1994) Control of bridge vibrations with hybrid devices. In: Proceedings 1st World conference on structural control, vol. TA2, pp 50–59, Los Angeles, CA, 1994Google Scholar
- 15.Feng Q, Shinozuka M (1990) Use of a variable damper for hybrid control of bridge response under earthquake. In: Proceedings of the U.S. national workshop on structural control research, pp 107–112, 25–26 October 1990. University of Southern California, Los AngelesGoogle Scholar
- 16.Nagarajaiah S (1994) Fuzzy controller for structures with hybrid isolation system. In: Proceedings 1st World conference on structural control, vol TA2, pp 67–76, Los Angeles, CA, 1994Google Scholar
- 17.Soong TT, Grigoriu M (1993) Random vibration of mechanical and structural systems. Prentice Hall, Englewood CliffsGoogle Scholar