Event-triggered Model-free Adaptive Predictive Control for Nonlinear NCSs with Data Dropout and Application in PMSM Control System

For a class of nonlinear networked control systems (NCSs) subject to data dropouts, this paper studies the problem of the event-triggered model-free adaptive predictive control (ET-MFAPC), and a new ET-MFAPC scheme with data dropouts compensation is proposed to track the desired output. The main advantage of the proposed control scheme is that it has the pre-diction function, its the event triggering conditions of this scheme are complex, which reduces the calculation requirements, and pseudo partial derivative estimation algorithm is a real-time online estimation algorithm. In addition, the uniform boundedness of the tracking error of the closed-loop system in the mean square sense is also discussed. Finally, it is applied to PMSM speed control system to verify the effectiveness of the proposed ET-MFAPC algorithm.