The main objective of the proposed method is to improve the robustness of the Finite Control Set Model Predictive Torque Control for Induction Motors
In this Project, an adaptive sliding-mode-control-based MPTC (ASMC-MPTC) method is proposed to improve the robustness of the finite control set model predictive control (FCS-MPC). First, the influence of the mismatched parameters for FCS-MPTC is introduced and the shortcoming of the PI-based MPTC (PI-MPTC) is analyzed. Then, a sliding-mode-control-based MPTC (SMC-MPTC) is studied, in which the exponential reaching law is introduced to control the trajectories of the state variables. To further improve the control performance of SMC-MPTC, the exponential reaching law is optimized to adjust the switching gain adaptively, thus the ASMC-MPTC is proposed. The PI-MPTC and ASMC-MPTC are compared with help MATLAB/SIMULINK software, and the results show that the proposed ASMC-MPTC has the best disturbance rejection ability and robustness against motor parameters variation and load torque change.
Index TermsβInduction motor (IM), model predictive torque control (MPTC), robustness, sliding-mode control (SMC), Fuzzy Logic Controller.
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Software Configuration:
Operating System : Windows 7/8/10
Application Software : Matlab/Simulink
Hardware Configuration:
RAM : 8 GB
Processor : I3 / I5(Mostly prefer)