An adaptive neural controller is proposed for nonlinear systems with a nonlinear dead-zone and multiple time-delays. The often used inverse model compensation approach is avoided by representing the dead-zone as a time-varying system. The “explosion of complexity” in the backstepping synthesis is eliminated in terms of the dynamic surface control (DSC) technique. A novel high-order neural network (HONN) with only a scalar weight parameter is developed to account for unknown nonlinearities. The control singularity and some restrictive requirements on the system are circumvented. Simulations and experiments for a turntable servo system with permanent-magnet synchronous motor (PMSM) are provided to verify the reliability and effectiveness.
|Translated title of the contribution||Adaptive neural dynamic surface control for servo systems with unknown dead-zone|
|Pages (from-to)||1328 - 1343|
|Number of pages||16|
|Journal||Control Engineering Practice|
|Publication status||Published - Aug 2011|