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Xinpeng Geng1, Shoulin Hao1, Tao Liu1

  • 1Institute of Advanced Control Technology, Dalian University of Technology, Dalian, 116024, PR China.

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|December 4, 2018
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Summary
This summary is machine-generated.

A new control scheme enhances set-point tracking and disturbance rejection for non-minimum phase (NMP) systems. It uses a generalized predictor and model-based extended state observer (MESO) for improved system performance and stability.

Keywords:
Active disturbance rejection control (ADRC)Extended state observerGeneralized predictorInput delayNon-minimum phaseSampled systems

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Area of Science:

  • Control Systems Engineering
  • Non-linear Dynamics
  • Robust Control Theory

Background:

  • Non-minimum phase (NMP) systems present significant challenges in control design due to inherent performance limitations.
  • Traditional control methods often struggle with simultaneous set-point tracking and disturbance rejection in NMP systems.
  • Accurate state and disturbance estimation is crucial for effective control of complex dynamic systems.

Purpose of the Study:

  • To propose a generalized predictor-based control scheme for enhanced performance in NMP systems.
  • To develop a robust control strategy that addresses both set-point tracking and disturbance rejection.
  • To ensure closed-loop stability in the presence of system uncertainties.

Main Methods:

  • A generalized predictor is employed to estimate the system output, effectively compensating for time delays.
  • A model-based extended state observer (MESO) is designed for simultaneous estimation of system states and external disturbances.
  • An active disturbance rejection control (ADRC) strategy is formulated, integrating state feedback and feedforward control.
  • Controller parameters are analytically derived by pole placement for the MESO and closed-loop system.
  • A pre-filter is designed using a desired closed-loop transfer function to optimize set-point tracking.
  • Robust stability against time-varying uncertainties is analyzed using linear matrix inequalities (LMIs).

Main Results:

  • The proposed control scheme demonstrates significant improvements in set-point tracking accuracy.
  • Effective rejection of external disturbances is achieved, maintaining system performance.
  • The controller exhibits robust stability under time-varying system uncertainties, as confirmed by LMI analysis.
  • Validation through three literature examples confirms the effectiveness and advantages of the proposed method.

Conclusions:

  • The generalized predictor-based control scheme offers a robust and effective solution for controlling non-minimum phase systems.
  • The integration of MESO and ADRC provides superior performance in both tracking and disturbance rejection tasks.
  • The analytical design and stability analysis ensure reliable operation in practical applications.