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. & 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., & 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
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, 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).
