Active disturbance rejection controller (ADRC) has achieved soaring success in motion controls featured by rapid dynamics. However, it turns obstreperous to implement it in the power plant process with considerable time-delay, largely because of the tuning difficulty. To this end, this article proposes a quantitative tuning rule for the time-delayed ADRC (TD-ADRC) structure based on the typical first order plus time delay (FOPTD) model. By compensating the FOPTD process as an integrator plus time delay in low frequencies, the gain parameter of TD-ADRC can be related to a scaled time constant which shapes the closed-loop tracking performance. Bandwidth parameter of extended state observer is scaled as a dimensionless parameter. A sufficient stability condition of TD-ADRC is theoretically derived in terms of the scaled parameter pair, the range of which falls within the practical interest. Relative delay margin is revealed as a critical robustness metric among others, a default pair of scaled parameter setting is recommended as well as an explicit retuning guideline according to the user's preference for performance or robustness. Simulation and laboratory water tank experiment validate the tuning efficacy and a coal mill temperature control test depicts a promising prospective of the proposed method in process control practice.
30 October 2017 in International Journal of Robust and Nonlinear Control
The extended state observer (ESO) is used to estimate both the unmeasurable system states and acting lumped disturbance. Generally, high gains need to be selected in ESO to achieve fast convergence, which can make it sensitive to measurement noise. To address this limitation, a governing structure with a special combination of Kalman filter (KF) and ESO is proposed. The former serves as noise filtration while the latter is responsible for on-line reconstruction of states and disturbance. The two are connected as the system model used for the KF design contains a constantly updated estimate of the lumped disturbance obtained with the ESO. Finally, the resultant estimates are used to construct a composite disturbance rejection-based controller. To verify the new method, hardware experiments are performed on an electronic throttle system. Conducted quantitative comparison with conventional solution reveals advantages of the proposed approach in noise attenuation and control performance.
5 March 2018 in Science China Information Sciences