Balancing robustness and optimality in sensor placement for dynamic state estimation

Abstract The paper derives a Lyapunov equation whose solution is the sensitivity of the Kalman filter state error covariance matrix to structured and parametric model errors in the stiffness and damping of structural systems. This result is utilized to propose an expression to balance optimality and robustness for sensor placement in the presence of parametric model uncertainties. The proposed expressions are successfully verified and illustrated using a six-story steel moment-resisting frame subjected to a ground motion in the presence of uncertainty in element and support stiffness properties.

[1]  Eric M. Hernandez,et al.  Efficient sensor placement for state estimation in structural dynamics , 2017 .

[2]  Costas Papadimitriou,et al.  Optimal sensor placement methodology for parametric identification of structural systems , 2004 .

[3]  Thilo Penzl,et al.  Numerical solution of generalized Lyapunov equations , 1998, Adv. Comput. Math..

[4]  T. Soong,et al.  Mathematics of Kalman-Bucy filtering , 1985 .

[5]  Geert Lombaert,et al.  Dynamic strain estimation for fatigue assessment of an offshore monopile wind turbine using filtering and modal expansion algorithms , 2016 .

[6]  S. Hammarling Numerical Solution of the Stable, Non-negative Definite Lyapunov Equation , 1982 .

[7]  Keith Worden,et al.  Optimal sensor placement for fault detection , 2001 .

[8]  Joel P. Conte,et al.  Material Parameter Identification in Distributed Plasticity FE Models of Frame-Type Structures Using Nonlinear Stochastic Filtering , 2015 .

[9]  Eleni Chatzi,et al.  Experimental application of on-line parametric identification for nonlinear hysteretic systems with model uncertainty , 2010 .

[10]  S. S. Law,et al.  Optimum sensor placement for structural damage detection , 2000 .

[11]  Sankaran Mahadevan,et al.  Structural Health Monitoring Sensor Placement Optimization Under Uncertainty , 2010 .

[12]  Rafael Castro-Triguero,et al.  Robustness of optimal sensor placement under parametric uncertainty , 2013 .

[13]  G. Roeck,et al.  Design of sensor networks for instantaneous inversion of modally reduced order models in structural dynamics , 2015 .

[14]  M.A. Demetriou,et al.  Optimization of a joint sensor placement and robust estimation scheme for distributed parameter processes subject to worst case spatial disturbance distributions , 2004, Proceedings of the 2004 American Control Conference.

[15]  Qingshan Yang,et al.  Sensor placement method for dynamic response reconstruction , 2014 .

[16]  Ernesto Heredia-Zavoni,et al.  Optimal instrumentation of uncertain structural systems subject to earthquake ground motions , 1998 .

[17]  Vikram Krishnamurthy,et al.  Robust Meter Placement for State Estimation in Active Distribution Systems , 2015, IEEE Transactions on Smart Grid.

[18]  Ben Wang,et al.  A minimax sensor placement approach for damage detection in composite structures , 2012 .

[19]  Costas Papadimitriou,et al.  Experimental validation of the Kalman-type filters for online and real-time state and input estimation , 2017 .

[20]  C. Papadimitriou,et al.  A dual Kalman filter approach for state estimation via output-only acceleration measurements , 2015 .

[21]  Ruben Garrido,et al.  Simultaneous parameter and state estimation of shear buildings , 2016 .

[22]  Shamim N. Pakzad,et al.  Optimal Sensor Placement for Modal Identification of Bridge Systems Considering Number of Sensing Nodes , 2014 .

[23]  Costas Papadimitriou,et al.  Fatigue predictions in entire body of metallic structures from a limited number of vibration sensors using Kalman filtering , 2011 .

[24]  James L. Beck,et al.  Updating Properties of Nonlinear Dynamical Systems with Uncertain Input , 2003 .

[25]  Costas Papadimitriou,et al.  Optimal sensor placement for multi-setup modal analysis of structures , 2017 .

[26]  M. Hoshiya,et al.  Structural Identification by Extended Kalman Filter , 1984 .

[27]  Joel P. Conte,et al.  Bayesian nonlinear structural FE model and seismic input identification for damage assessment of civil structures , 2017 .

[28]  G. Golub,et al.  A Hessenberg-Schur method for the problem AX + XB= C , 1979 .

[29]  D. Kammer Sensor Placement for On-Orbit Modal Identification and Correlation of Large Space Structures , 1990, 1990 American Control Conference.

[30]  Yi-Qing Ni,et al.  Optimal sensor placement for damage detection of bridges subject to ship collision , 2017 .

[31]  Yl L. Xu,et al.  Optimal multi-type sensor placement for response and excitation reconstruction , 2016 .

[32]  Ian R. Petersen,et al.  Robust Kalman Filtering for Signals and Systems with Large Uncertainties , 1999 .

[33]  Kalil Erazo,et al.  A model-based observer for state and stress estimation in structural and mechanical systems: Experimental validation , 2014 .

[34]  Sheng Zhan,et al.  Multi-Type Sensor Placement for Multi-Scale Response Reconstruction , 2013 .

[35]  Oliver Sawodny,et al.  Optimal sensor placement for state estimation of a thin double-curved shell structure , 2013 .

[36]  Mohinder S. Grewal,et al.  Kalman Filtering: Theory and Practice Using MATLAB , 2001 .

[37]  Daniel C. Kammer,et al.  Optimal sensor placement for modal identification using system-realization methods , 1996 .

[38]  Songye Zhu,et al.  Multi-type sensor placement and response reconstruction for structural health monitoring of long-span suspension bridges , 2016 .

[39]  Costas Papadimitriou,et al.  Bayesian optimal estimation for output‐only nonlinear system and damage identification of civil structures , 2018 .

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

[41]  Eric B. Flynn,et al.  A Bayesian approach to optimal sensor placement for structural health monitoring with application to active sensing , 2010 .

[42]  Andrew W. Smyth,et al.  Particle filtering and marginalization for parameter identification in structural systems , 2017 .

[43]  Richard G. Cobb,et al.  Sensor Placement and Structural Damage Identification from Minimal Sensor Information , 1997 .

[44]  David V. Rosowsky,et al.  Estimation of element‐by‐element demand‐to‐capacity ratios in instrumented SMRF buildings using measured seismic response , 2018 .