Interval state estimation for uncertain polytopic systems

References

• Ben Chabane, S., Stoica Maniu, C., Alamo, T., Camacho, E., & Dumur, D. (2014). Ellipsoidal state estimation for systems with interval uncertainties. IEEE conference on decision and control, Los Angeles, CA.
   Google Scholar
• Besançon, G. (2007). Nonlinear observers and applications. Berlin, Germany: Springer.
   Google Scholar
• Boubaker, O., Zhu, Q., Mahmoud, M., Ragot, J., Karimi, H., & Davila, J. (2019). New trends in observer-based control. Eastbourne, UK: Elsevier.
   Google Scholar
• Boyd, S., El Ghaoui, L., Feron, E., & Balakrishnan, V. (1994). Linear matrix inequalities in system and control theory. Philadelphia, USA: SIAM Studies in Applied Mathematics.
   Google Scholar
• Cacace, F., Germani, A., & Manes, C. (2015). A new approach to design interval observers for linear systems. IEEE Transactions on Automatic Control, 60(6), 1665–1670.
   Web of Science ®Google Scholar
• Chisci, L., Garulli, A., & Zappa, G. (1996). Recursive state bounding by parallelotopes. Automatica, 32(7), 1049–1055.
   Web of Science ®Google Scholar
• Efimov, D., Perruquetti, W., Raïssi, T., & Zolghadri, A. (2013). Interval observers for time-varying discrete-time systems. IEEE Transactions on Automatic Control, 58(12), 3218–3224.
   Web of Science ®Google Scholar
• Efimov, D., & Raïssi, T. (2016). Design of interval observers for uncertain dynamical systems. Automation and Remote Control, 77(2), 191–225.
   Web of Science ®Google Scholar
• Efimov, D., Raïssi, T., Chebotarev, S., & Zolghadri, A. (2013). Interval state observer for nonlinear time varying systems. Automatica, 49(1), 200–205.
   Web of Science ®Google Scholar
• Ellero, N., Gucik-Derigny, D., & Henry, D. (2016). Multiobjective interval observer via LMI techniques for fault detection. 2016 3rd conference on control and fault-tolerant systems (pp. 485–490), Nice, France.
   Google Scholar
• Faydasicoka, O., & Arik, S. (2013). A new upper bound for the norm of interval matrices with application to robust stability analysis of delayed neural networks. Neural Networks, 44, 64–71.
   PubMed Web of Science ®Google Scholar
• Garcia, C. M., Puig, V., Astorga-Zaragoza, C., & Osorio-Gordillo, G. (2018). Robust fault estimation based on interval Takagi-Sugeno unknown input observer. IFAC-PapersOnLine, 51(24), 508–514. 10th IFAC symposium on fault detection, supervision and safety for technical processes SAFEPROCESS 2018.
   Google Scholar
• Garcia, C., Puig, V., & Zaragoza, C. (2017). Fault estimation using a Takagi-Sugeno interval observer: Application to a PEM fuel cell. 14th international conference on informatics in control, automation and robotics, Madrid.
   Google Scholar
• Guerra, T., & Vermeiren, L. (2004). LMI-based relaxed nonquadratic stabilization conditions for nonlinear systems in the Takagi-Sugeno's form. Automatica, 40, 823–829.
   Web of Science ®Google Scholar
• Guo, S., & Zhu, F. (2017a). Actuator fault detection and interval reconstruction based on interval observers. IFAC World congres, Toulouse.
   Google Scholar
• Guo, S., & Zhu, F. (2017b). Interval observer design for discrete-time switched system. IFAC World congres, Toulouse, France.
   Google Scholar
• Guo, S., Zhu, F., Zhu, S., Hu, H., & Yang, J. (2017). State and sensor fault interval estimations for discrete-time systems. 2017 36th Chinese control conference (CCC) (pp. 7280–7284), Da lian, China.
   Google Scholar
• Haoa, C., Lianga, Y., & Roy, A. (2015). Equivalency between vertices and centers-coupled-with-radii principal component analyses for interval data. Statistics and Probability Letters, 106, 113–120.
   Web of Science ®Google Scholar
• He, Z., & Xie, W. (2016). Control of non-linear switched systems with average dwell time: interval observer-based framework. IET Control Theory & Applications, 10(1), 10–16.
   Web of Science ®Google Scholar
• Ichalal, D., Marx, B., Maquin, D., & Ragot, J. (2018). State estimation of system with bounded uncertain parameters: Interval multi-model approach. International Journal of Adaptive Control and Signal Processing, 32(3), 480–493.
   Web of Science ®Google Scholar
• Ichalal, D., Marx, B., Ragot, J., & Maquin, D. (2010). State estimation of Takagi-Sugeno systems with unmeasurable premise variables. IET Control Theory & Applications, 4(5), 897–908.
   Web of Science ®Google Scholar
• Kalman, R. (1960). A new approach to linear filtering and prediction problems. Transactions of the ASME – Journal of Basic Engineering, 82, 35–45.
   Google Scholar
• Kruszewski, A., Wang, R., & Guerra, T. M. (2008). Nonquadratic stabilization conditions for a class of uncertain nonlinear discrete time ts fuzzy models: A new approach. IEEE Transactions on Automatic Control, 53(2), 606–611.
   Web of Science ®Google Scholar
• Lamouchi, R., Raïssi, T., Amairi, M., & Aoun, M. (2018). Interval observer framework for fault-tolerant control of linear parameter-varying systems. International Journal of Control, 91(3), 524–533.
   Web of Science ®Google Scholar
• Langowski, R., & Brdys, M. (2017). An interval estimator for chlorine monitoring in drinking water distribution systems under uncertain system dynamics, inputs and chlorine concentration measurement. International Journal of Applied Mathematics and Computer Science, 27(2), 309–322.
   Web of Science ®Google Scholar
• Lendek, Z., Guerra, T., Babuska, R., & De Schutter, B. (2010). Stability analysis and nonlinear observer design using Takagi-Sugeno fuzzy models. Berlin, Germany: Springer.
   Google Scholar
• Luenberger, D. (1971). An introduction to observers. IEEE Transactions on Automatic Control, 16, 596–602.
   Web of Science ®Google Scholar
• Martinez-Sibaja, A., Astorga-Zaragoza, C., Alvarado-Lassman, A., Posada-Gómez, R., Aguila-Rodriguez, R., Rodriguez-Jarquin, J., & Adam-Medina, M. (2011). Simplified interval observer scheme: A new approach for fault diagnosis in instruments. Sensors, 11, 612–622.
   PubMed Web of Science ®Google Scholar
• Mazenc, F., & Bernard, O. (2010). Asymptotically stable interval observers for planar systems with complex poles. IEEE Transactions on Automatic Control, 55(2), 523–527.
   Web of Science ®Google Scholar
• Menasria, Y., Bouras, H., & Debbache, N. (2017). An interval observer design for uncertain nonlinear systems based on the T-S fuzzy model. Archives of Control Sciences, 27(3), 397–407.
   Web of Science ®Google Scholar
• Meyer, L., Ichalal, D., & Vigneron, V. (2018). Interval observer for LPV systems with unknown inputs. IET Control Theory & Applications, 12, 649–660, (11).
   Web of Science ®Google Scholar
• Moisan, M., Bernard, O., & Gouzé, J. (2009). Near optimal interval observers bundle for uncertain bioreactors. Automatica, 45, 291–295.
   Web of Science ®Google Scholar
• Moore, R. (1963). Interval arithmetic and automatic error analysis in digital computing (PhD thesis). Stanford University, Stanford, USA.
   Google Scholar
• Nagy, A., Mourot, G., Marx, B., Ragot, J., & Schutz, G. (2010). Systematic multimodeling methodology applied to an activated sludge reactor model. Industrial & Engineering Chemistry Research, 49(6), 2790–2799.
   Web of Science ®Google Scholar
• Park, P., Kwon, N., & Park, B. (2015). State-feedback control for LPV systems with interval uncertain parameters. Journal of the Franklin Institute, 352, 5214–5225.
   Web of Science ®Google Scholar
• Pastravanu, O., & Matcovschi, M. (2010). Diagonal stability of interval matrices and applications. Linear Algebra and its Applications, 433, 1646–1658.
   Web of Science ®Google Scholar
• Polyakov, A., Efimov, D., Perruquetti, W., & Richard, J. (2013). Interval observer approach to output stabilization of time-varying input delay systems. European control conference, Zurich.
   Google Scholar
• Raïssi, T., Efimov, D., & Zolghadri, A. (2012). Interval state estimation for a class of nonlinear systems. IEEE Transactions on Automatic Control, 57(1), 260–265.
   Web of Science ®Google Scholar
• Ramdani, N., Raïssi, T., Candau, Y., & Ibos, L. (2005). Complex interval constraint propagation for non linear bounded-error parameter identification. IEEE conference on decision and control, Seville.
   Google Scholar
• Robinson, E., Marzat, J., & Raïssi, T. (2017). Interval observer design for unknown input estimation of linear time-invariant discrete-time systems. IFAC World congres, Toulouse.
   Google Scholar
• Rotondo, D., Cristofaro, A., Johansen, T. A., Nejjari, F., & Puig, V. (2018). State estimation and decoupling of unknown inputs in uncertain LPV systems using interval observers. International Journal of Control, 91(8), 1944–1961.
   Web of Science ®Google Scholar
• Shao, G., & Su, J. (2010). Sensitivity and inverse analysis methods for parameter intervals. Journal of Rock Mechanics and Geotechnical Engineering, 2(3), 274–280.
   Google Scholar
• Takagi, T., & Sugeno, M. (1985). Fuzzy identification of systems and its applications to modeling and control. IEEE Transactions on Systems, Man, and Cybernetics, 15, 116–132.
   Web of Science ®Google Scholar
• Tanaka, K., & Wang, H. (2001). Fuzzy control systems design and analysis: A linear matrix inequality approach. New York, USA: Wiley.
   Google Scholar
• Thabet, R., Raïssi, T., Combastel, C., Efimov, D., & Zolghadri, A. (2014). An effective method to interval observer design for time-varying systems. Automatica, 50(10), 2677–2684.
   Web of Science ®Google Scholar
• Tuan, H., Apkarian, P., Narikiyo, T., & Yamamoto, Y. (2001). Parameterized linear matrix inequality techniques in fuzzy control system design. IEEE Transactions on Fuzzy Systems, 9(2), 324–332.
   Web of Science ®Google Scholar
• Udom, A. (2012). Exponential stabilization of stochastic interval system with time dependent parameters. European Journal of Operational Research, 222, 523–528.
   Web of Science ®Google Scholar
• Wang, Y., Bevly, D., & Rajamani, R. (2015). Interval observer design for LPV systems with parametric uncertainty. Automatica, 60, 79–85.
   Web of Science ®Google Scholar
• Wang, C., Li, J., & Guo, P. (2015). The normalized interval regression model with outlier detection and its real-world application to house pricing problems. Fuzzy Sets and Systems, 274, 109–123.
   Web of Science ®Google Scholar
• Wang, Z., Lim, C., & Shen, Y. (2018). Interval observer design for uncertain discrete-time linear systems. Systems & Control Letters, 116, 41–46.
   Web of Science ®Google Scholar
• Wang, C., & Sheng, Z. (2012). Positive observer for positive continuous systems with interval uncertainties and multiple time-delay. Chinese control and decision conference, Taiyuan.
   Google Scholar
• Zarch, M. G., Puig, V., Poshtan, J., & Shoorehdeli, M. A. (2018). Fault detection and isolation using viability theory and interval observers. International Journal of Systems Science, 49(7), 1445–1462.
   Web of Science ®Google Scholar
• Zhang, Z., & Yang, G. (2017). Interval observer-based fault isolation for discrete-time fuzzy interconnected systems with unknown interconnections. IEEE Transactions on Cybernetics, 47(9), 2413–2424.
   PubMed Web of Science ®Google Scholar