In this paper, a problem of influence of an input-gain uncertainty on the tracking performance of a control structure designed according to the Active Disturbance Rejection Control (ADRC) paradigm is investigated. This problem is exemplified using the second-order plant. It is presented that conscious choice of the input-gain parameter different to that of the real plant may lead to a significant improvement of the control precision if the controller is designed in an error domain. Obtained results indicate that the closed-loop system remains stable, and the tracking errors decrease if the value of this parameter follows from multiplying the plant gain input by a positive factor smaller than a certain threshold value. The upper limit for this factor is investigated in the paper and outcomes are presented for various implementation variants. Results of numerical computations, simulations and experiments are presented to consider this bounding value in individual cases.

In this letter, a new kind of adaptive controller for the problem of output feedback tracking is proposed on the basis of the Active Disturbance Rejection Control (ADRC) paradigm. The controller is synthesized for the systems linear in parameters by combining the classic ADRC algorithm with a recent Parameter Identifying Extended State Observer (PIESO) which employs a gradient adaptation law to actively identify the parameters of the plant. By means of the Lyapunov analysis, the asymptotic convergence of tracking, estimation, and identification errors is proved in the nominal case and the stability conditions of the closed-loop system are formulated. The theoretical analysis is complemented by simulation and experimental results of the proposed controller.

In this paper, a novel method of parameter identification of linear in parameter dynamic systems is presented. The proposed scheme employs an Extended State Observer to online estimate a state of the plant and momentary value of total disturbance present in the system. A notion is made that for properly redefined dynamics of the system, this estimate can be interpreted as a measure of modeling error caused by the parameter uncertainty. Under this notion, a disturbance estimate is used as a basis for classic gradient identification. A global convergence of both state and parameter estimates to their true values is proved using the Lyapunov approach under an assumption of a persistent excitation. Finally, results of simulation and experiments are presented to support the theoretical analysis. The experiments were conducted using a compliant manipulator joint and obtained results show the usefulness of the proposed method in drive control systems and robotics.

This paper is focused on a distributed control of fully actuated manipulators under operating conditions when dynamic couplings between their joints are insignificant. The main research aspect was to examine the influence of the inertia parameter on the tracking quality for control systems based on the active rejection paradigm. The theoretical description and preliminary hypothesis were supported by extensive simulation and experimental results. In particular, it is demonstrated that choosing the inertia parameter according to the real dynamics properties does not guarantee the best performance of the considered control structures.

In this paper the novel control and communication scheme designed to ease the development and maintenance of the robotic astronomical telescope device is presented. The proposed solution allows the user to remotely access any signal in the controller of the telescope without imposing any additional overhead during telescope operation. The implemented scheme can be used by both an automated control system and human operators for easy supervision, control, and maintenance of the device.