Conventional model predictive control (MPC) of power converter has been widely applied to power inverters achieving high performance, fast dynamic response, and accurate transient control of power converter. However, the MPC strategy is highly reliant on the accuracy of the inverter model used for the controlled system. Consequently, a parameter or model mismatch between the plant and the controller leads to a sub-optimal performance of MPC. In this paper, a new strategy called model-free predictive control (MF-PC) is proposed to improve such problems. The presented approach is based on a recursive least squares algorithm to identify the parameters of an auto-regressive with exogenous input (ARX) model. The proposed method provides an accurate prediction of the controlled variables without requiring detailed knowledge of the physical system. This new approach and is realized by employing a novel state space identification algorithm into the predictive control structure.
Fig. 1 Proposed Model-Free Predictive Control Scheme.
Fig. 2. Performance comparison of conventional FCS-MPC and the proposed MF-PC of a voltage source inverter considering model mismatch. (a) Experimental validation of the conventional FCS-MPC. (c) Experimental validation of the proposed MF-PC.