Non‐linear‐disturbance‐observer‐enhanced MPC for motion control systems with multiple disturbances

摘要

This study addresses the optimised tracking problem for motion control systems with multiple disturbances by a non‐linear‐disturbance‐observer‐enhanced continuous‐time model predictive control (MPC) method. The core is to predict the future tracking error and desired control input (including the lumped effects of disturbances/uncertainties) in the receding‐horizon by a higher‐order sliding mode disturbance observer, which is designed based upon a rough nominal system. Different from the direct compensation approach in most existing composite MPC methods, disturbance estimates are taken full advantage in the optimisation. The explicit relationship between asymptotic stability and weights in the performance index is provided. Simulations on position control of the robot arm system and experiments on speed regulation of the permanent magnet synchronous motor servo system are both presented to demonstrate the workability.