Active Disturbance Rejection Control
Also known as: ADRC, Disturbance Rejection Control
Active Disturbance Rejection Control (ADRC) is a control method that estimates and cancels disturbances and model uncertainties in real-time using an extended state observer (ESO), treating them as additional 'disturbance states'. Developed by Han and popularized by Gao, ADRC achieves remarkable robustness without requiring precise plant models, making it practical for real-world systems with significant uncertainty and disturbances.
Key highlights
- Robust to model uncertainty; treats uncertainty as estimated disturbance rather than designing for worst-case.
- Simple control law (often PD-like); minimal tuning compared to PID or H-infinity.
- Fast disturbance rejection; real-time estimation enables rapid response.
- Extends to MIMO and nonlinear systems naturally.
- Practical implementation; no need for detailed model identification.
Intuition
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How it works
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When to use it
Use ADRC when the plant model is inaccurate, disturbances are substantial, and you want simple control law without detailed model. Ideal for industrial applications (motors, pumps, heating), robotics with uncertain payloads, and systems with time-varying parameters. Avoid ADRC if the disturbance is too fast for the observer to track or if very low steady-state ripple is required.
Strengths & limitations
- Robust to model uncertainty; treats uncertainty as estimated disturbance rather than designing for worst-case.
- Simple control law (often PD-like); minimal tuning compared to PID or H-infinity.
- Fast disturbance rejection; real-time estimation enables rapid response.
- Extends to MIMO and nonlinear systems naturally.
- Practical implementation; no need for detailed model identification.
- Requires accurate output measurement; observer sensitivity to noise can limit performance.
- Observer bandwidth limited by measurement noise; cannot estimate arbitrarily fast disturbances.
- High observer gain can amplify measurement noise; trade-off between disturbance estimation and noise rejection.
- Tuning ESO parameters (observer gains) requires experience; less systematic than classical control methods.
- Theoretical analysis more complex; stability and convergence guarantees less mature than classical methods.
Common pitfalls
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Applications
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Frequently asked
How do I tune the extended state observer (ESO) gains?
ESO gains control observer bandwidth and robustness to noise. Higher gains estimate disturbance faster but amplify measurement noise. Common tuning: start with observer bandwidth 5-10x controller bandwidth, adjust empirically based on sensitivity to measurement noise. Parameter space is large; use frequency response analysis or pole placement for systematic design.
Sources
- 1.Han, J. (2009). From PID to active disturbance rejection control. IEEE Transactions on Industrial Electronics, 56(3), 900-906.
- 2.Gao, Z. (2006). Active disturbance rejection control: a paradigm shift in feedback control system design. Proceedings of the 2006 American Control Conference, 2652-2661.
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Cite this page
ScholarGate. (2026, June 3). Active Disturbance Rejection Control. ScholarGate. https://scholargate.app/control-theory/active-disturbance-rejection-control