Optimal Sector-Based Sequential Model Predictive Control for Current Source Rectifier

Conventional model predictive control (MPC) methods for current source rectifier (CSR) use either a PI controller or weight factor-based methods, which require time-consuming tuning methods to develop an efficient controller. Moreover, the limitations on the bandwidth requirements of the LC filter cause resonances and grid current distortions if a variable switching frequency-based predictive control is used. So, a new fixed switching frequency-based MPC algorithm has been developed to control the load and source current simultaneously, thereby facilitating the weight factor less operation and applying a predefined space vector sequence. Unlike the conventional single cost function methods applied to CSR, the proposed method uses separate cost function for each control variable. Simultaneously, to provide fixed frequency operation, duty ratio-based modulation of grid current control has been applied. A virtual impedance-based active damping has been embedded into the supply current control to suppress the oscillations caused by the LC filter and grid current harmonics. Simulation and experimental results have been supported to validate the improvements in terms of supply current total harmonic distortion (THD), steady state, and transient switching performance.

Automated summary

In this study, a new fixed switching frequency-based MPC algorithm for current source rectifier (CSR) is proposed, which can simultaneously control the load and source current, improving the quality of the supply current and the steady state and transient switching performance.