Dynamic model identification and state variables estimation from the corrupted measurement data have been attracted much research efforts during the recent years. In this way, Kalman and H-infinity filters have been increasingly used to estimate the parameters individually. In this paper, a mixed kalman-H_∞ filter is designed in an innovative approach using a multi-objective optimization method. It is desired to simultaneously employ the advantages of both filters to minimize both the root-mean squared errors and the upper bounds limit of estimation errors associated with Kalman and H-infinity filters, respectively. Some Pareto optimum design points are presented for two case studies from which trade-off optimum design points can be simply selected.
Masoumnezhad,M , Moafi,A , Jamali,A and Nariman-zadeh,N . (2014). Optimal Design of Mixed Kalman-H infinity Filter Using Multi-objective Optimization Method. Modares Mechanical Engineering, 14(2), 128-132.
MLA
Masoumnezhad,M , , Moafi,A , , Jamali,A , and Nariman-zadeh,N . "Optimal Design of Mixed Kalman-H infinity Filter Using Multi-objective Optimization Method", Modares Mechanical Engineering, 14, 2, 2014, 128-132.
HARVARD
Masoumnezhad M, Moafi A, Jamali A, Nariman-zadeh N. (2014). 'Optimal Design of Mixed Kalman-H infinity Filter Using Multi-objective Optimization Method', Modares Mechanical Engineering, 14(2), pp. 128-132.
CHICAGO
M Masoumnezhad, A Moafi, A Jamali and N Nariman-zadeh, "Optimal Design of Mixed Kalman-H infinity Filter Using Multi-objective Optimization Method," Modares Mechanical Engineering, 14 2 (2014): 128-132,
VANCOUVER
Masoumnezhad M, Moafi A, Jamali A, Nariman-zadeh N. Optimal Design of Mixed Kalman-H infinity Filter Using Multi-objective Optimization Method. Modares Mechanical Engineering. 2014;14(2):128-132 (In Persian).
