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access icon free Non-linear-disturbance-observer-enhanced MPC for motion control systems with multiple disturbances

  • Author(s): Yunda Yan 1 ; Jun Yang 1 ; Zhenxing Sun 2 ; Shihua Li 1 ; Haoyong Yu 3
    • View affiliations
  • Source: Volume 14, Issue 1, 01 January 2020, p. 63 – 72
    DOI:  10.1049/iet-cta.2018.5821 , Print ISSN 1751-8644, Online ISSN 1751-8652
© The Institution of Engineering and Technology
Received 26/07/2018, Accepted 24/09/2019, Revised 10/08/2019, Published 25/09/2019

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.

Inspec keywords: motion control; servomechanisms; synchronous motors; observers; predictive control; asymptotic stability; machine control; control system synthesis; permanent magnet motors; nonlinear control systems; position control; variable structure systems

Other keywords: future tracking error; existing composite MPC methods; higher-order sliding mode disturbance observer; control input; permanent magnet synchronous motor servo system; nonlinear-disturbance-observer-enhanced MPC; disturbance estimates; nonlinear-disturbance-observer-enhanced continuous-time model; multiple disturbances; position control; optimised tracking problem; robot arm system; motion control systems; rough nominal system

Subjects: Multivariable control systems; Control system analysis and synthesis methods; Synchronous machines; Spatial variables control; Nonlinear control systems; Stability in control theory; Control of electric power systems; Optimal control

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