The performance of active disturbance rejection control (ADRC) algorithms can be limited in practice by high-frequency measurement noise. In this article, this problem is addressed by transforming the high-gain extended state observer (ESO), which is the inherent element of ADRC, into a new cascade observer structure. Set of experiments, performed on a dc–dc buck power converter system, show that the new cascade ESO design, compared to the conventional approach, effectively suppresses the detrimental effect of sensor noise overamplification while increasing the estimation/control performance. The proposed design is also analyzed with a low-pass filter at the converter output, which is a common technique for reducing measurement noise in industrial applications.

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.