Adaptive Gain Fuzzy-projection of Permanent Magnet Linear Synchronous Motor with Dead-zone Compensation

Adaptive robust control (ARC) is widely used in linear motor systems because of its robustness and ability to deal with the uncertain parameters. However, in industrial applications, undesirable operating trajectories and uncertain nonlinear external disturbances of permanent magnet linear synchronous motors (PMLSM) can adversely affect the parameter adaptive part of the ARC controller, which can lead to undesirable performance. Therefore, this paper introduces an adaptive gain fuzzy-projection with dead-zone compensation (DAFP) strategy based on ARC, which uses the dead-zone shutdown mechanism and adaptive regulation of the parameter gains to achieve fast estimation of uncertain parameters and reduce the impact of parameter estimation errors on the system. Furthermore, in this paper, by conducting two sets of comparative experiments under different expectation trajectories, the results consistently validate that the proposed DAFP method effectively enhances accuracy and speed of parameter identification while mitigating the impact of nonlinear disturbances on the system.