Startsida
Keywords: Nonlinear State and Parameter Estimation; Unscented Kalman Filter (UKF); Smoothing; Functional Mockup Interface (FMI); Fault Detection and Diagnosis (FDD)
Proceedings of the 10th International Modelica Conference; March 10-12; 2014; Lund; Sweden
[1] S. J. Julier and J. K. Uhlmann. A general method for approximating nonlinear transformations of probability distributions. Robotics Research Group Technical Report, Department of Engineering Science, University of Oxford, pages 1–27, November 1996.
[2] S.J. Julier. The scaled unscented transformation. In American Control Conference, 2002. Proceedings of the 2002, volume 6, pages 4555–4559 vol.6, 2002.
[3] Simon S Haykin et al. Kalman filtering and neural networks. Wiley Online Library, 2001.
[4] D. Crisan and Arnaud Doucet. A survey of convergence results on particle filtering methods for practitioners. Signal Processing, IEEE Transactions on, 50(3):736–746, 2002.
[5] Modelon AB. PyFMI a package for working with dynamic models compliant with the functional mock-up interface standard, September 2013.
[6] E.A. Wan and R. Van der Merwe. The unscented kalman filter for nonlinear estimation. In Adaptive Systems for Signal Processing, Communications, and Control Symposium 2000. AS-SPCC. The IEEE 2000, pages 153–158, 2000.
[7] S. Sarkka. On unscented kalman filtering for state estimation of continuous-time nonlinear systems. Automatic Control, IEEE Transactions on, 52(9):1631–1641, 2007.
[8] S. Sarkka. Unscented rauch–tung–striebel smoother. Automatic Control, IEEE Transactions on, 53(3):845–849, 2008.
[9] Venkat Venkatasubramanian, Raghunathan Rengaswamy, Kewen Yin, and Surya N. Kavuri. A review of process fault detection and diagnosis: Part I: Quantitative model-based methods. Computers & Chemical Engineering, 27(3):293–311, 2003.
[10] Venkat Venkatasubramanian, Raghunathan Rengaswamy, and Surya N Kavuri. A review of process fault detection and diagnosis: Part II: Qualitative models and search strategies. Computers& Chemical Engineering, 27(3):313 – 326, 2003.
[11] Venkat Venkatasubramanian, Raghunathan Rengaswamy, Surya N. Kavuri, and Kewen Yin. A review of process fault detection and diagnosis: Part III: Process history based methods. Computers& Chemical Engineering, 27(3):327 – 346, 2003.
[12] Michael Wetter, Wangda Zuo, Thierry S Nouidui, and Xiufeng Pang. Modelica buildings library. Journal of Building Performance Simulation, (In press):1–18, 2013.