The extended model predictive-sliding mode control of three-level AC/DC power converters with output voltage and load resistance variations

Abstract

In the proposed approach, an Extended Model Predictive Sliding Mode Controller (EMPSMC) is designed to control Three-Level Ac/Dc Power Converters to achieve improved dynamic performance and better. Steady-state stability. The traditional proportional-integral (PI) controller is used in the Model Predictive PI controller (MPPIC) technique to produce active power reference. However, this technique results in a significant overshoot/undershoot and steady-state error. Instead of PI, sliding mode control (SMC) is used to overcome these shortcomings. The performances of EMPSMC and MPPIC are compared and analyzed with and without disturbance. The results show that the system's settling time is minimized by introducing SMC, and the overshoot is also reduced. Moreover, it also provided better steady-state stability. Similarly, dynamic improvements are achieved with EMPSMC for tracking the desired dc reference voltage demand. The simulation results validate the performance of the designed model.

Model Predictive Sliding Mode Control of Direct Current Motors

“…Ma et al [23] presented a new reaching law-based control approach combining a sliding-mode disturbance observer and an enhanced two-vector model predictive current control enhances the dynamic performance and robustness of the permanent magnet synchronous motor to system disturbances. Jamshed Abbas et al [24] proposed an extended MPSMC for controlling Three-Level AC/DC Power Converters to enhance dynamic performance and steady-state stability. Comparisons between extended MPSMC and Model Predictive proportional integral controller show that SMC reduces settling time, overshoot, and steady-state error, providing better performance in tracking DC reference voltage demand.…”

“…) Referring to the equations(22) and(23), we can conclude: 𝐼(𝑘 + 1) = 𝑎𝐼(𝑘) + 𝑇 𝑠 𝑢(𝑘)(24) The tracking error of the reference current in the proposed MPC controller is defined as follows:𝑒 𝐼 (𝑘) = 𝐼 𝑟 (𝑘) − 𝐼(𝑘)(25) where 𝑒 𝐼 (𝑘) is the tracking error of the MPC controller. Considering the equations (24) and (25), we can predict the flow tracking error in the upcoming moments: { 𝑒 𝐼 (𝑘) = 𝐼 𝑟 (𝑘) − 𝐼(𝑘) 𝑒 𝐼 (𝑘 + 1) = 𝐼 𝑟 (𝑘 + 1) − 𝐼(𝑘 + 1) = 𝐼 𝑟 (𝑘 + 1) − 𝑎𝐼(𝑘) + 𝑇 𝑠 𝑢(𝑘) 𝑒 𝐼 (𝑘 + 2) = 𝐼 𝑟 (𝑘 + 2) − 𝑎 2 𝐼(𝑘) − 𝑎𝑇 𝑠 𝑢(𝑘) − 𝑇 𝑠 𝑢(𝑘 + 1) ⋮ 𝑒 𝐼 (𝑘 + 𝑁) = 𝐼 𝑟 (𝑘 + 𝑁) − 𝑎 𝑁 𝐼(𝑘) − 𝑇 𝑠 ∑ 𝑎 𝑁−1−𝑖 𝑁−1 𝑖=0𝑢(𝑘 + 𝑖)…”