Parameter independent model order reduction |
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| Affiliation: | 1. ASIC & System State Key Laboratory, Microelectronics Department, Fudan University, HanDan Road 220, Shanghai 200433, China;2. IMTEK-Institute for Microsystem Technology, University of Freiburg, D-79110 Freiburg, Germany;1. Center for Educational Technology, Gannan Normal University, Ganzhou 341000, China;2. Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China;3. School of Information Engineering, Jiangxi University of Science and Technology, Ganzhou 341000, China;1. KTH Royal Institute of Technology, The Marcus Wallenberg Laboratory for Sound and Vibration Research, Teknikringen 8, SE-100 44 Stockholm, Sweden;2. Eindhoven University of Technology, Department of Mechanical Engineering, 5600 MB Eindhoven, The Netherlands;1. Mechanical Engineering Department, Dogus University, Istanbul, Turkey;2. Mechanical Engineering and Mechanics, Lehigh University, Bethlehem, PA 18015-3085, United States;1. Department of Mechanical Engineering, Federal University of Santa Catarina, Florianópolis, SC 88040-900, Brazil;2. Federal University of Santa Catarina, Ararangua, SC 88906-072, Brazil |
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| Abstract: | Several recently developed model order reduction methods for fast simulation of large-scale dynamical systems with two or more parameters are reviewed. Besides, an alternative approach for linear parameter system model reduction as well as a more efficient method for nonlinear parameter system model reduction are proposed in this paper. Comparison between different methods from theoretical elegancy to complexity of implementation are given. By these methods, a large dimensional system with parameters can be reduced to a smaller dimensional parameter system that can approximate the original large sized system to a certain degree for all the parameters. |
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