Neural Adaptive Funnel Dynamic Surface Control with Disturbance-Observer for the PMSM with Time Delays |
| |
Authors: | Menghan Li Shaobo Li Junxing Zhang Fengbin Wu Tao Zhang |
| |
Affiliation: | 1.School of Mechanical Engineering, Guizhou University, Guiyang 550025, China; (M.L.); (T.Z.);2.State Key Laboratory of Public Big Data, Guizhou University, Guiyang 550025, China;3.School of Computer Science and Technology, Guizhou University, Guiyang 550025, China; |
| |
Abstract: | This paper suggests an adaptive funnel dynamic surface control method with a disturbance observer for the permanent magnet synchronous motor with time delays. An improved prescribed performance function is integrated with a modified funnel variable at the beginning of the controller design to coordinate the permanent magnet synchronous motor with the output constrained into an unconstrained one, which has a faster convergence rate than ordinary barrier Lyapunov functions. Then, the specific controller is devised by the dynamic surface control technique with first-order filters to the unconstrained system. Therein, a disturbance-observer and the radial basis function neural networks are introduced to estimate unmatched disturbances and multiple unknown nonlinearities, respectively. Several Lyapunov-Krasovskii functionals are constructed to make up for time delays, enhancing control performance. The first-order filters are implemented to overcome the “complexity explosion” caused by general backstepping methods. Additionally, the boundedness and binding ranges of all the signals are ensured through the detailed stability analysis. Ultimately, simulation results and comparison experiments confirm the superiority of the controller designed in this paper. |
| |
Keywords: | disturbance observer dynamic surface control permanent magnetic synchronous motor funnel control radial basis function neural networks |
|
|