One of the major advantages of model predictive control (MPC) is that several control targets, variables, and constraints can be included in a single cost function and simultaneously controlled. Some representative examples of MPC cost functions are classified according to the nature of their terms, in order to group types of weighting factors that could be tuned similarly. Then a set of simple guidelines is analyzed and tested to evaluate the evolution of system performance in relation to changes in the weighting factors. Several converter and drive control applications will be studied to cover a wide variety of cost functions and weighting factors.
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Model predictive control with a finite control set has emerged as a promising control tool for power converters and drives. One of the major advantages is the possibility to control several system variables with a single control law, by including them with appropriate weighting factors. However, at the present state of the art, these coefficients are determined empirically. There is no analytical or numerical method proposed yet to obtain an optimal solution. In addition, the empirical method is not always straightforward, and no procedures have been reported. This paper presents a first approach to a set of guidelines that reduce the uncertainty of this process. First a classification of different types of cost functions and weighting factors is presented. Then the different steps of the empirical process are explained. Finally, results for several power converters and drives applications are analyzed, which show the effectiveness of the proposed guidelines to reach appropriate weighting factors and control performance.
I have published an article about how to narrow down the best values of weighting factors in FCS-MPC for grid converter with LCL filter. In my opinion we should relating the largest changes of the controlled values that are possible to be achieved during one sampling period Ts.
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Article Properties of active rectifier with LCL filter in the select...
Hi Ali, there are multiple different methods (Table based, Offline calculation and online methods (adaptive)), following paper will help you about adaptive weights https://www.sciencedirect.com/science/article/abs/pii/S0019057822001987?via%3Dihub