Robust Iterative Learning Control For Permanent Magnet Synchronous Linear Motor Control

Permanent magnet linear synchronous motor(PMLSM) has been used more and more widely, because of some advantage, such as simple structure, strong thrust and less dead, high transmission efficiency. PMSLM depend on the coupling of short mover and long stator to produce thrust. Actually the air gap between mover and stator was difficult to keep constant, with the switch of winding and magnetic pole, which produces a magnetic field fluctuations and the difference of end effects; in the running of PMSLM, motor winding temperature, load condition changes and other factors, can have some impact on system parameters, which lead to parameter perturbation and the existing of uncertainty in the system; in the controlling of PMSLM, parameter will difficult to detect directly, such as speed, location and workers corner, and it will produce a measuring disturbance; in subparagraph motor winding switching would cause saturation. Therefore, drive and control of PMSLM is a nonlinear, Multivariable uncertain objects and strong coupling.Doing repetitive work of PMSLM, to restrain measurement of disturbances, saturated input, as well as to its parameter perturbation and unmodeled Dynamics uncertainties, robust iterative learning control method was designed in this paper(ILC) This research work mainly includes the following three components:First, the measurement of interference appears in the running of PMSLM, and the ILC with a filter algorithm was designed. Theory represented the convergence of the algorithm, and it is effective to suppress the measurement of interference by the ILC algorithm and simulation validation with filter.Second, it is on the concerning that the control input was not equal to actual input which caused by input saturation, and the impact because of above. ILC algorithm is designed to ensure stable operation of PMSLM and good tracking performance. And theories prove the convergence of systems, simulation proves the correctness of the theoretical analysis.Third, Adaptive iterative learning controller was designed for perturbations of parameters that appear in the system, and uncertainty.Through theoretical analysis, simulation, it proved the correctness of control me-thods, system performance and stability, high precision, have a certain robustness...