کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
688923 | 889581 | 2014 | 12 صفحه PDF | دانلود رایگان |
• A novel weighting method is proposed for multimodel predictive control of MIMO nonlinear systems.
• The gap metric is employed to formulate weighting functions for local controller combination.
• There is only one tuning parameter, making the proposed weighting method simpler.
• The weights can be calculated off-line and stored in a look-up table, reducing computation load.
A novel weighting method is proposed for multimodel predictive control of nonlinear systems with multiple scheduling variables (MIMO nonlinear systems), in which the gap metric is employed to formulate weighting functions for local controller combination. Compared to existent weighting functions, the proposed weighting method has two major advantages: firstly, there is only one tuning parameter, which makes it simpler. Secondly, the weights depend only on the scheduling vector and can be calculated off-line and stored in a look-up table. Therefore, the computational load can be reduced, especially for nonlinear systems with multiple scheduling variables. A MIMO CSTR system is studied to demonstrate the effectiveness of the proposed weighting method.
Journal: Journal of Process Control - Volume 24, Issue 9, September 2014, Pages 1346–1357