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Generalized predictor based active disturbance rejection control for non-minimum phase systems
Xinpeng Geng1, Shoulin Hao1, Tao Liu1
1Institute of Advanced Control Technology, Dalian University of Technology, Dalian, 116024, PR China.
ISA Transactions
|December 4, 2018
Summary
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.
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.
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