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   Experimental Evaluation of Cascaded Continuous and Finite Set Model Predictive Speed Control for Electrical Drives   [View] 
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 Author(s)   Sebastian WENDEL 
 Abstract   The proposed paper describes and experimentally validates a cascaded continuous and finite set model predictive control (CCF-MPC) algorithm for a mechatronic drive system. This approach is advantageous for the speed control of electrical drives in mechatronic systems with high requirements on the electrical and mechanical controlled system equally. CCF-MPC enables, on the one hand, the optimization of the steady-state current performance, as indicated by a reduced total harmonic distortion, and a highly dynamic current behavior by using the advantages and direct control nature of finite control set MPC. On the other hand, due to the integration of a continuous control set MPC concept, CCF-MPC allows a foresighted and active damping of mechanical oscillations in the load speed. This is beneficial for the overall predictive optimization of mechatronic systems (e.g., two-mass systems), which are present, e.g., for electrical drives in machine tools. 
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Filename:0030-epe2019-full-14503620.pdf
Filesize:1.555 MB
 Type   Members Only 
 Date   Last modified 2020-08-14 by System