Hanif Tahersima, Mohammadjafar Saleh, Akram Mesgarisohani and Mohammadhossein Tahersima, “Design of stable model reference adaptive system via Lyapunov rule for control of chemical reactor,” 3rd Australian Control Conference (AUCC), Fremantle, WA, pp. 348-353, 2013.
Majdi Mansouri, Hazem Nounou and Mohamed Nounou, “State estimation of a chemical reactor process model - A comparative study,” 10th Int. Multi- Conf. Syst., Signals & Devices, pp. 1-6, 2013.
Hazem N. Nouou and Mohamed N. Nounou, “Application of delay-dependent adaptive control to a continuous stirred tank reactor,” IEEE Symp. Comput. Intel. Cont. Auto. (CICA), Singapore, pp. 140-147, 2013.
Don Simon, “Optimal state estimation,” New Jersey: John Wiley & Sons, 2006.
J. Bellantoni, K. Dodge, “A square root formulation of the Kalman-Schmidt filter,” AIAA Journal, vol. 5, pp. 1309-1314, 1967.
Rudolph E. Kalman, “A new approach to linear filtering and prediction problems,” Trans. ASME-J. Basic Eng., pp. 35-45, 1960.
Andrey Romanenko, Jose A. Castro, “The unscented filter as an alternative to the EKF for nonlinear state estimation: a simulation case study,” Comput. Chem. Eng., vol. 28, no. 3, pp. 347-355, 2004.
Andrey Romanenko, Lino O. Santos and Paulo AFNA Afonso, “Unscented Kalman filtering of a simulated pH system,” Ind. Eng. Chem. Res., vol. 43, pp. 7531-7538, 2004.
Rudolph Van der Merwe, Eric A. Wan and Simon Julier, “Sigma-point Kalman filters for nonlinear estimation and sensor-fusion-applications to integrated navigation,” AIAA, pp. 2004-5120, 2004.
Eric A. Wan and Rudolph Van der Merwe, “The unscented Kalman filter for nonlinear estimation,” Center for Spoken Language and Understanding, OGI School of Science and Engineering, 2006, URL: http://cslu.cse.ogi.edu/nsel/ukf/.
Eric A. Wan, Rudolph Van der Merwe and Alex T. Nelson, “Dual estimation and the unscented transformation,” Neural Inf. Proc. Syst., vol. 12, MIT Press, Massachusetts, USA, pp. 666-672, 2000.
Stefano Mariani and Aldo Ghisi, “Unscented Kalman filtering for nonlinear structural dynamics,” Nonlinear Dyn., vol. 49, pp. 131-150, 2007.
Jindrich Dunik, Ondrej Straka and Miroslav Simandl, “The Development of a Randomised Unscented Kalman Filter,” 18th IFAC World Congress, pp. 8-13, Milano, Italy, 2011.
Henry Cox, “On the estimation of state variables and parameters for noisy dynamic systems,” IEEE Trans. Auto. Cont., vol. 9, pp. 5-12, 1964.
Lawrence Nelson and Edwin Stear, “The simultaneous on-line estimation of parameters and states in linear systems,” IEEE Trans. Auto. Cont., pp. 438-442, 1967.
S. C. Stubberud and M. Owen, “Artificial neural network feedback loop with on-line training,” Proc. IEEE. Int. Symp. Intell. Cont. Dearborn, August, pp. 514-519, 1996.
Eric A. Wan and Alex T. Nelson, “Dual Kalman filtering methods for nonlinear prediction, estimation, and smoothing,” Adv. in Neural Inf. Proc. Syst. Vol. 9, Cambridge, MA: MIT Press, 1997.
Stefano Mariani and Alberto Corigliano, “Impact induced composite delamination: state a parameter identification via joint and dual extended Kalman filters,” Comput. Methods Appl. Mech. Eng., vol. 194, pp. 5242-5272, 2005.
Jacek Czeczot, “Balance-based adaptive control methodology and its application to the non-isothermal CSTR,” Chem. Eng. Proc., pp. 359-371, 2006.
William L. Luyben, “Chemical reactor design and control,” New Jersey: John Wiley & Sons, 2007.
Richard E. Kopp and Richard J. Orford, “Linear regression applied to system identification for adaptive control systems,” AIAA Journal, vol. 1, no. 10, pp. 2300-2306, 1963.
Eric A. Wan and Alex T. Nelson, “Dual extended Kalman filter methods,” Kalman filtering and neural networks, pp. 123-173, 2001.
Hossein Khodadadi and Hooshang Jazayeri-Rad, “Applying a dual extended Kalman filter for the nonlinear state and parameter estimations of a continuous stirred tank reactor,” Comput. Chem. Eng., vol. 35, no. 11, pp. 2426- 2436, 2011.
Alan Genz and John Monahan, “A Stochastic Algorithm for High Dimensional Integrals over Unbounded Regions with Gaussian Weight,” J. Comput. Appl. Math, vol. 112, no. 1, pp. 71-81, 1999.
Vinary A. Bavdekar, R. Bhushan Gopaluni and Sirish L. Shah, “Evaluation of Adaptive Extended Kalman Filter Algorithms for State Estimation in Presence of Model-Plant Mismatch”, 10th IFAC Int. Symp. Dyn. Cont. Proc. Syst., Mumbai, India, 2013.
M.F. Samadi, S.M. Alavi, and M. Saif, “Online state and parameter estimation of the Li-ion battery in a Bayesian framework,” American Control Conference (ACC), pp. 4693-4698, June 2013, Washington, DC.
Nader Meskin, Hazem Nounou, Mohamed Nounou, and A. Datta, “Parameter Estimation of Biological Phenomena: An Unscented Kalman Filter Approach,” IEEE/ACM Trans. Comput. Biol. Bioinforma., Vol. 10, No. 2, 2013.
Li Meng, Liu Li, and S.M. Veres, “Aerodynamic Parameter Estimation of an Unmanned Aerial Vehicle Based on Extended Kalman Filter and Its Higher Order Approach,” Adv. Comput. Cont. (ICACC), 2nd Int. Conf., Vol. 5, pp. 526-531, March 2010, Shenyang, China.
Ji-Hoon Seung, Deok-Jin Lee and Kil-To Chong, “Parameter Estimation Method for Coupled Tank System using Dual Extended Kalman Filter,” 13th Int. Conf. Cont., Auto. Syst., pp. 1223-1228, Gwangju, Korea, October, 2013.
Ondrej Straka, Jindrich Dunik, and Mioslav Simandl, “Randomized unscented Kalman filter in target tracking,” 15th Int. Conf. Inf. Fusion (FUSION), pp. 503-510, Singapore, July 2012.