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An SQP trust region method for solving the discrete-time linear quadratic control problem

Control, Prague, Czech Republic , (on CD-ROM). Lee, J.-W. and Khargonekar, P. P. (2007). Constrained infinitehorizon linear quadratic regulation of discrete-time systems, IEEE Transactions on Automatic Control   52 (10): 1951-1958. Leibfritz, F. (2004). COMPlib: COnstraint Matrix-optimization Problem lib rary—A collection of test examples for nonlinear semi-definite programs, control system design and related problems, Technical report Leibfritz, F. and Mostafa, E

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Robust Output Regulation Of Uncertain Chaotic Systems With Input Magnitude And Rate Constraints

), Nonlinear Output Regulation: Theory and Applications , Philadelphia: Siam. 11. Ott, E., Grebogi, C., Yorke, J.A. (1990), Controlling Chaos, Physical Review Letters , 64 (11), 1196–1199. 12. Pecora, L.M., Carroll, T.L. (1990), Synchronization in Chaotic Systems, Physical Review Letters , 64 (8), 821–824. 13. Saberi, A., Stoorvogel, A.A., Sannuti, P. (2011), Control of Linear Systems with Regulation and Input Constraints , Springer; Reprint of the original 1st ed. 14. Tanaka, K., Wang, H. O. (2001), Fuzzy Control Systems Design and

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Model-free reconfiguration mechanism for fault tolerance

-252. Zhao, Q. and Jiang, J. (1998). Reliable state feedback control systems design against actuator failures, Automatica   34 (10): 1267-1272.

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Analytic Root Locus and Lambert W Function in Control of a Process with Time Delay

of the Analytic Method and Computer Alge- bra to Plot Root Loci, International Journal of Electrical Engineering Education 35 (1998), 350-356. KING-SMITH, E. A.: Stability Analysis of Linear Continuous Time-Delay Feedback Systems, International Journal of Control 13 (1971), 633-655. COGAN, B.: Optimum Stability in Control System Design, PhD thesis, Department of Electronic and Electrical Engineering, Trinity College, Dublin, 2006. COGAN, B.—de PAOR, A. M.—QUINN, A.: PI Control of

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Nonlinear model predictive control of a boiler unit: A fault tolerant control study

Chamseddine, A. (2009). Fault Tolerant Control Systems. Design and Practical Applications , Advanced in Industrial Control, Springer, London. Patan, K. (2008). Artificial Neural Networks for the Modelling and Fault Diagnosis of Technical Processes , Lecture Notes in Control and Information Sciences, Vol. 377, Springer-Verlag, Berlin. Patan, K. (2009a). Fault detection and accommodation by means of neural networks. application to the boiler unit, Proceedings of the 7th International Symposium on Fault Detection

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Estimation of the Output Deviation Norm for Uncertain, Discrete-Time Nonlinear Systems in a State Dependent Form

for robust H 1 control systems design , IEEE Transactions on Industrial Electronics , Vol. 43, No. 5, pp. 575-582. Whidborne, J. F., Postlethwaite I. and Gu D. W. (1994): Robust controller design using Hinf loop-shaping and the method of inequalities , IEEE Transactions on Control Systems Technology , Vol. 29, No. 4, pp. 455-461. Van der Schaft, A.J. (1992): L 2 -gain analysis of nonlinear systems and nonlinear state feedback H control , IEEE Transactions on Automatic Control , Vol. AC-37, No. 6, pp. 770

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Stability of softly switched multiregional dynamic output controllers with a static antiwindup filter: A discrete-time case

Systems 159 (8): 900-925, DOI: 10.1016/j.fss.2007.08.009. Qi, R. and Brdys, M.A. (2009). Indirect adaptive controller based on a self-structuring fuzzy system for nonlinear modeling and control, International Journal of Applied Mathematics and Computer Science 19 (4): 619-630, DOI: 10.2478/v10006-009-0049-8. Rhee, B.-J. and Won, S. (2006). A new fuzzy Lyapunov function approach for Takagi-Sugeno fuzzy control systems design, Fuzzy Sets and Systems 157 (9): 1211-1228, DOI:10.1016/j.fss.2005.12.020. Tanaka, K., Ikeda, T

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On an infinite dimensional linear-quadratic problem with fixed endpoints: The continuity question

References Athans, M. (1971). The role and use of the stochastic linear-quadratic-Gaussian problem in control system design, IEEE Transactions on Automatic Control, AC-16(6): 529-552. Aubin, J.-P. (2000). Applied Functional Analysis, Wiley, New York, NY. Balakrishnan, A.V. (1981). Applied Functional Analysis, Springer, New York, NY. Brockett, R.F. (1970). Finite-Dimensional Linear Systems, Wiley, New York, NY. Chow, G.P. (1976). Analysis and Control of Dynamic Economic Systems

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Disturbance modeling and state estimation for offset-free predictive control with state-space process models

, Italy , pp. 5326–5331. Tatjewski, P. (2012). Modeling deterministic disturbances and state filtering in model predictive control with state-space models, in M. Busłowicz and K. Malinowski (Eds.), Advances in Control Theory and Automation , OWPB, Białystok, pp. 263–274. Tatjewski, P. and Ławry´nczuk, M. (2006). Soft computing in model-based predictive control, International Journal of Applied Mathematics and Computer Science 16(1): 7–26. Wang, L. (2009). Model Predictive Control System Design and Implementation Using MATLAB, Springer Verlag, London.

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Analysis of sensorless control of brushless DC motor using unknown input observer with different gains

10, pp. 279 - 286, 2013. [16] R. S. Burns, ”Advanced control engineering”, Butterworth -Heinemann, 2001. [17] A. K. Mandal, ”Introduction to control engineering - modeling, analysis and design”, New Age International Pvt. Ltd. , 2006. [18] G. S. Phadke, ”Control system design”, Vipul Prakashan, 2008. [19] D. G. Luenberger, ”An introduction to observer”, IEEE Transac- tion on Automatic Control, Ac-16, no. 6, pp. 596-602, December 1971. [20] J-W. Park, S. -H. Hwang and J. -M. Kim

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