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A weightedpathfollowing method for symmetric cone linear complementarity problems
Auxiliary signal design for failure detection in differentialalgebraic equations
1.  Department of Mathematics, North Carolina State University, Raleigh, North Carolina, 276958205, United States, United States 
References:
[1] 
I. Andjelkovic, K. A. Sweetingham and S. L. Campbell, Active fault detection in nonlinear systems using auxiliary signals,, in American Control Conference, (2008), 2142. Google Scholar 
[2] 
I. Andjelkovic and S. L. Campbell, Direct optimization determination of auxiliary test signals for linear problems with model uncertainty,, in 50th IEEE CDCECC, (2011), 909. Google Scholar 
[3] 
R. E. Bellman, Dynamic Programming,, Princeton University Press, (1957). Google Scholar 
[4] 
G. Besançon, I. RubioScola and D. Georges, Input selection in observer design for nonuniformly observable systems,, in 9th IFAC Symposium on Nonlinear Control Systems, (2013). Google Scholar 
[5] 
K. Brenan, S. L. Campbell and L. R. Petzold, Numerical Solution of Initial Value Problems in DifferentialAlgebraic Equations,, SIAM, (1996). Google Scholar 
[6] 
A. E. Bryson and Y. C. Ho, Applied Optimal Control,, Hemisphere, (1975). Google Scholar 
[7] 
S. L. Campbell and R. Nikoukhah, Auxiliary Signal Design for Failure Detection,, Princeton University Press, (2004). Google Scholar 
[8] 
S. L. Campbell, Least squares completions for nonlinear differential algebraic equations,, Numerical Mathematics, 65 (1993), 77. doi: 10.1007/BF01385741. Google Scholar 
[9] 
D. Choe, S. L. Campbell and R. Nikoukhah, A comparison of optimal and suboptimal auxiliary signal design approaches,, in IEEE Conference on Control Applications, (2005). Google Scholar 
[10] 
D. Garg, M. A. Patterson, W. W. Hager, A. V. Rao, D. A. Benson and G. T. Huntington, A unified framework for the numerical solution of optimal control problems using pseudospectral methods,, Automatica, 46 (2010), 1843. doi: 10.1016/j.automatica.2010.06.048. Google Scholar 
[11] 
D. Garg, W. W. Hager and A. V. Rao, Pseudospectral methods for solving infinitehorizon optimal control problems,, Automatica, 47 (2011), 829. doi: 10.1016/j.automatica.2011.01.085. Google Scholar 
[12] 
D. Garg, M. A. Patterson, C. L. Darby, C. Francolin, G. T. Huntington, W. W. Hager and A. V. Rao, Direct trajectory optimization and costate estimation of finitehorizon and infinitehorizon optimal control problems via a radau pseudospectral method,, Computational Optimization and Applications, 49 (2011), 335. doi: 10.1007/s1058900992910. Google Scholar 
[13] 
M. Gerdin, T. Glad and L. Ljung, Parameter estimation in linear differentialalgebraic equations,, in 13th IFAC Symposium on System Identification, (2003). Google Scholar 
[14] 
M. Gerdts, Parameter identification in higher DAE systems,, Technical Report, (2005). Google Scholar 
[15] 
R. Isermann, Fault Diagnosis Systems: An Introduction from Fault Detection to Fault Tolerance,, Springer, (2006). Google Scholar 
[16] 
R. Kircheis and S. Körkel, Parameter estimation for DAE models in a multiple experiment context,, 82nd Annual Meeting of the International Association of Applied Mathematics and Mechanics, 11 (2011), 715. Google Scholar 
[17] 
H. H. Niemann, Active fault diagnosis in closedloop uncertain systems,, in 6th IFAC Symposium on Fault Detection Supervision and Safety for Technical Processes, (2006), 587. Google Scholar 
[18] 
H. H. Niemann, A setup for active fault diagnosis,, IEEE Transactions on Automatic Control, 51 (2006), 1572. doi: 10.1109/TAC.2006.878724. Google Scholar 
[19] 
M. A. Patterson and A. V. Rao, Exploiting sparsity in direct collocation pseudospectral methods for solving continuoustime optimal control problems,, Journal of Spacecraft and Rockets, 49 (2012), 364. Google Scholar 
[20] 
R. J. Patton, P. M. Frank and R. N. Clark, Issues of Fault Diagnosis for Dynamic Systems,, Springer, (2000). Google Scholar 
[21] 
N. K. Poulsen and H. H. Niemann, Active fault diagnosisa stochastic approach,, in 7th IFAC Symposium on Fault Detection Supervision and Safety for Technical Processes, (2009). Google Scholar 
[22] 
I. Okay, S. L. Campbell and P. Kunkel, Completions of implicitly defined time varying vector fields,, Linear Algebra and its Applications, 431 (2009), 1422. doi: 10.1016/j.laa.2009.05.006. Google Scholar 
[23] 
I. RubioScola, G. Besançon and D. Georges, Online observability optimization for state affine systems with output injection and observer design,, in 21st IEEE Mediterranean Conference on Control and Automation, (2013). Google Scholar 
[24] 
I. RubioScola, G. Besançon and D. Georges, Input optimization for observability of state affine systems,, in 5th IFAC Symposium on System Structure and Control, (2013). Google Scholar 
show all references
References:
[1] 
I. Andjelkovic, K. A. Sweetingham and S. L. Campbell, Active fault detection in nonlinear systems using auxiliary signals,, in American Control Conference, (2008), 2142. Google Scholar 
[2] 
I. Andjelkovic and S. L. Campbell, Direct optimization determination of auxiliary test signals for linear problems with model uncertainty,, in 50th IEEE CDCECC, (2011), 909. Google Scholar 
[3] 
R. E. Bellman, Dynamic Programming,, Princeton University Press, (1957). Google Scholar 
[4] 
G. Besançon, I. RubioScola and D. Georges, Input selection in observer design for nonuniformly observable systems,, in 9th IFAC Symposium on Nonlinear Control Systems, (2013). Google Scholar 
[5] 
K. Brenan, S. L. Campbell and L. R. Petzold, Numerical Solution of Initial Value Problems in DifferentialAlgebraic Equations,, SIAM, (1996). Google Scholar 
[6] 
A. E. Bryson and Y. C. Ho, Applied Optimal Control,, Hemisphere, (1975). Google Scholar 
[7] 
S. L. Campbell and R. Nikoukhah, Auxiliary Signal Design for Failure Detection,, Princeton University Press, (2004). Google Scholar 
[8] 
S. L. Campbell, Least squares completions for nonlinear differential algebraic equations,, Numerical Mathematics, 65 (1993), 77. doi: 10.1007/BF01385741. Google Scholar 
[9] 
D. Choe, S. L. Campbell and R. Nikoukhah, A comparison of optimal and suboptimal auxiliary signal design approaches,, in IEEE Conference on Control Applications, (2005). Google Scholar 
[10] 
D. Garg, M. A. Patterson, W. W. Hager, A. V. Rao, D. A. Benson and G. T. Huntington, A unified framework for the numerical solution of optimal control problems using pseudospectral methods,, Automatica, 46 (2010), 1843. doi: 10.1016/j.automatica.2010.06.048. Google Scholar 
[11] 
D. Garg, W. W. Hager and A. V. Rao, Pseudospectral methods for solving infinitehorizon optimal control problems,, Automatica, 47 (2011), 829. doi: 10.1016/j.automatica.2011.01.085. Google Scholar 
[12] 
D. Garg, M. A. Patterson, C. L. Darby, C. Francolin, G. T. Huntington, W. W. Hager and A. V. Rao, Direct trajectory optimization and costate estimation of finitehorizon and infinitehorizon optimal control problems via a radau pseudospectral method,, Computational Optimization and Applications, 49 (2011), 335. doi: 10.1007/s1058900992910. Google Scholar 
[13] 
M. Gerdin, T. Glad and L. Ljung, Parameter estimation in linear differentialalgebraic equations,, in 13th IFAC Symposium on System Identification, (2003). Google Scholar 
[14] 
M. Gerdts, Parameter identification in higher DAE systems,, Technical Report, (2005). Google Scholar 
[15] 
R. Isermann, Fault Diagnosis Systems: An Introduction from Fault Detection to Fault Tolerance,, Springer, (2006). Google Scholar 
[16] 
R. Kircheis and S. Körkel, Parameter estimation for DAE models in a multiple experiment context,, 82nd Annual Meeting of the International Association of Applied Mathematics and Mechanics, 11 (2011), 715. Google Scholar 
[17] 
H. H. Niemann, Active fault diagnosis in closedloop uncertain systems,, in 6th IFAC Symposium on Fault Detection Supervision and Safety for Technical Processes, (2006), 587. Google Scholar 
[18] 
H. H. Niemann, A setup for active fault diagnosis,, IEEE Transactions on Automatic Control, 51 (2006), 1572. doi: 10.1109/TAC.2006.878724. Google Scholar 
[19] 
M. A. Patterson and A. V. Rao, Exploiting sparsity in direct collocation pseudospectral methods for solving continuoustime optimal control problems,, Journal of Spacecraft and Rockets, 49 (2012), 364. Google Scholar 
[20] 
R. J. Patton, P. M. Frank and R. N. Clark, Issues of Fault Diagnosis for Dynamic Systems,, Springer, (2000). Google Scholar 
[21] 
N. K. Poulsen and H. H. Niemann, Active fault diagnosisa stochastic approach,, in 7th IFAC Symposium on Fault Detection Supervision and Safety for Technical Processes, (2009). Google Scholar 
[22] 
I. Okay, S. L. Campbell and P. Kunkel, Completions of implicitly defined time varying vector fields,, Linear Algebra and its Applications, 431 (2009), 1422. doi: 10.1016/j.laa.2009.05.006. Google Scholar 
[23] 
I. RubioScola, G. Besançon and D. Georges, Online observability optimization for state affine systems with output injection and observer design,, in 21st IEEE Mediterranean Conference on Control and Automation, (2013). Google Scholar 
[24] 
I. RubioScola, G. Besançon and D. Georges, Input optimization for observability of state affine systems,, in 5th IFAC Symposium on System Structure and Control, (2013). Google Scholar 
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