Abstract
The standard way to compute H ∞ feedback controllers uses algebraic Riccati equations and is therefore of limited applicability. Here we present a new approach to the H ∞ output feedback control design problem, which is based on nonlinear and nonsmooth mathematical programming techniques. Our approach avoids the use of Lyapunov variables, and is therefore flexible in many practical situations.
Similar content being viewed by others
References
Apkarian P. and Noll D. (2006). Controller design via nonsmooth multi-directional search. SIAM J. Control Optim. 44(6): 1923–1949
Apkarian P. and Noll D. (2006). Nonsmooth H ∞ synthesis. IEEE Trans. Autom. Control 51(1): 71–86
Apkarian P. and Noll D. (2006). Nonsmooth optimization for multidisk H ∞ synthesis. Eur. J. Control 12(3): 229–244
Apkarian P. and Noll D. (2007). Nonsmooth optimization for multiband frequency domain control design. Automatica 43(4): 724–731
Apkarian P., Noll D., Thevenet J.-B. and Tuan H.D. (2004). A spectral quadratic SDP method with applications to fixed-order H 2 and H ∞ synthesis. Eur. J. Control 10(6): 527–538
Apkarian P. and Tuan H.D. (2000). Robust control via concave minimization—local and global algorithms. IEEE Trans. Autom. Control 45(2): 299–305
Balakrishnan V., Boyd S. and Balemi S. (1991). Branch and bound algorithm for computing the minimum stability degree of parameter-dependent linear systems. Int. J. Robust Nonlinear Control 1(4): 295–317
Bompart, V., Apkarian, P., Noll, D.: Nonsmooth techniques for stabilizing linear systems. In: Proceedings of the American Control Conference, New York (2007)
Boyd S. and Balakrishnan V. (1990). A regularity result for the singular values of a transfer matrix and a quadratically convergent algorithm for computing its L ∞-norm. Syst. Control Lett. 15(1): 1–7
Boyd, S., El Ghaoui, L., Feron, E., Balakrishnan, V.: Linear matrix inequalities in system and control theory. In: SIAM Studies in Applied Mathematics, vol 15. SIAM, Philadelphia (1994)
Bruinsma N.A. and Steinbuch M. (1990). A fast algorithm to compute the H ∞-norm of a transfer function matrix. Syst. Control Lett. 14(5): 287–293
Conn, A., Gould, N., Toint, Ph.: Trust-region methods. In: MPS-SIAM Series on Optimization, Philadelphia (2000)
Fares B., Apkarian P. and Noll D. (2001). An augmented Lagrangian method for a class of LMI-constrained problems in robust control. Int. J. Control 74(4): 348–360
Fares B., Noll D. and Apkarian P. (2002). Robust control via sequential semidefinite programming. SIAM J. Control Optim. 40(6): 1791–1820
Fletcher R. (1985). Semi-definite matrix constraints in optimization. SIAM J. Control Optim. 23(4): 493–513
Gahinet, P., Apkarian, P.: Numerical computation of the L ∞-norm revisited. In: Proceedings of the IEEE Conference on Decision and Control, Tucson, pp 2257–2258 (1992)
Golub G. and Van Loan C. (1989). Matrix Computations. Johns Hopkins University Press, Baltimore, London
Hettich R. and Kortanek K. (1993). Semi-infinite programming: theory, methods and applications. SIAM Rev. 35(3): 380–429
Jarre F. (1993). An interior-point method for minimizing the maximum eigenvalue of a linear combination of matrices. SIAM J. Control Optim. 31(5): 1360–1377
Jongen H.Th., Meer K. and Triesch E. (2004). Optimization Theory. Kluwer, Dordrecht
Kato T. (1980). Perturbation theory for linear operators. Springer, New York
Laub A. (1981) Efficient multivariable frequency response computations. IEEE Trans. Autom. Control 26(2), 407–408
Leibfritz, F.: COMPl e ib: COnstrained Matrix-optimization Problem ph library—a collection of test examples for nonlinear semidefinite programs, control system design and related problems. Technical report, Universität Trier (2003)
Leibfritz F. and Mostafa E.M.E. (2002). An interior-point constrained trust region method for a special class of nonlinear semi-definite programming problems. SIAM J. Optim. 12(4): 1048–1074
Leibfritz F. and Mostafa E.M.E. (2003). Trust region methods for solving the optimal output feedback design problem. Int. J. Control 76(5): 501–519
MacFarlane A.G.J. and Hung Y.S. (1983). Analytic properties of the singular value of a rational matrix. Int. J. Control 37(2): 221–234
Mayne D.Q. and Polak E. (1975). Algorithms for the design of control systems subject to singular value inequalities. IEEE Trans. Autom. Control AC-20(4): 546–548
Nocedal J. and Wright S. (1999). Numerical Optimization. Springer, New York
Noll D. and Apkarian P. (2005). Spectral bundle methods for nonconvex maximum eigenvalue functions: second-order methods. Math. Program. Ser. B 104(2): 729–747
Noll D., Torki M. and Apkarian P. (2004). Partially augmented Lagrangian method for matrix inequality constraints. SIAM J. Optim. 15(1): 161–184
Overton M.L. (1983). A quadratically convergent method for minimizing a sum of Euclidean norms. Math. Program. 27: 34–63
Overton M.L. (1988). On minimizing the maximum eigenvalue of a symmetric matrix. SIAM J. Matrix Anal. Appl. 9(2): 256–268
Polak E. and Wardi Y. (1982). A nondifferentiable optimization algorithm for the design of control systems subject to singular value inequalities over a frequency range. Automatica 18(3): 267–283
Safonov, M.G., Goh, K.C., Ly, J.H.: Control system synthesis via bilinear matrix inequalities. In: Proceedings of the American Control Conference, pp 45–49 (1994)
Shapiro A. (1997). First and second order analysis of nonlinear semidefinite programs. Math. Program. 77(2): 301–320
Thevenet J.-B., Noll D. and Apkarian P. (2006). Nonlinear spectral SDP method for BMI-constrained problems: applications to control design. In: Braz, J., Araújo, H., Vieira, A., and Encarnação, B. (eds) Informatics in Control, Automation and Robotics I., pp 61–72. Springer, Heidelberg
Tuan H.D., Apkarian P. and Nakashima Y. (2000). A new Lagrangian dual global optimization algorithm for solving bilinear matrix inequalities. Int. J. Robust Nonlinear Control 10(7): 561–578
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Bompart, V., Noll, D. & Apkarian, P. Second-order nonsmooth optimization for H ∞ synthesis. Numer. Math. 107, 433–454 (2007). https://doi.org/10.1007/s00211-007-0095-9
Received:
Revised:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00211-007-0095-9