Model-free Adaptive Predictive Control Of Permanent Magnet Synchronous Motor System

Permanent magnet synchronous motor(PMSM)has been widely used inmachinery manufacturing,vehicle parts production,chemical industry and other fields because of its superior mechanical performance,strong load carrying capacity,simple operation,low loss and high efficiency.In motor control,control accuracy is an important index to measure the advantages and disadvantages of motor control methods,and it is also an important index to reflect the control performance of various equipment driven by motor.Therefore,in order to improve the motor control accuracy,this paper designs the control scheme suitable for PMSM systems and PMSM systems under network communication transmission.The main research contents and innovations are summarized as follows:1.This paper investigates the model-free adaptive predictive control(MFAPC)problem for a class of PMSM systems with strong coupling,load uncertainty and external disturbance,and a novel MFAPC scheme is proposed to achieve the speed tracking objective of PMSM systems with external disturbance.The main advantage of the proposed control scheme is that only the input/output(I/O)data of the controlled system are used and has strong robustness to external disturbance.In addition,the convergence of tracking error and the stability of bounded input and bounded output are discussed.Finally,the simulation results illustrate the effectiveness and advantage of the proposed MFAPC scheme by compared with the traditional PI control scheme and the prototype model-free adaptive control(MFAC)scheme.2.The problem of event-triggered model-free adaptive predictive control(ETMFAPC)for general nonlinear networked control systems(NCSs)with communication constraints such as data dropouts is studied,and a new ET-MFAPC scheme with data dropouts compensation is proposed to complete the task of tracking the desired output signal.The main advantage of the proposed control scheme is that it not only has the prediction function,saves communication resources and simple event triggering conditions,but also its 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.