###### Abstract
In contrast, disturbance observers (DOBs) have been proposed to deal with not only model uncertainties, but also external disturbances based on the assumption that their derivatives are bounded. Recent developments can be considered as the nonlinear disturbance observer (NDOB) [24; 25] and time delay estimation (TDE) [26; 27; 28] which require states and their derivatives information to achieve high accuracy disturbance estimation performance. Overcoming this requirement, the extended-state observer (ESO) was developed to estimate both lumped disturbances and system states based on the augmented state mechanism [4; 29]. However, the order of this observer was quite high, which may cause computational burdens and slow down the transient responses. A potential solution to deal with these difficulties is the sliding mode observer (SMO) which considers a similar problem, i.e., state estimation, based on the switching mechanism of the estimation errors [30]. Therefore, fast responses in the estimates can be guaranteed with robustness to changes in system dynamics. However, to the best of the authors' knowledge, the SMO has not been applied for states and disturbances estimation in general robotic applications, especially excavator control design. Beyond that, for further improvement of excavator control accuracy, i.e., guarantee pre-defined control criteria, many techniques which have been widely applied in robotic fields can be investigated as prescribed performance function (PPF) [31; 32], barrier Lyapunov function (BLF) [29; 33], and their variations [34; 35]. However, until now, the application of these advanced techniques in the control design of robotic excavators was quite limited. In the authors' previous work [4; 36], the BLF is adopted to guarantee high accuracy contouring control performance and only PID is applied for the remaining performance indices, which does not fully cover the operation of the whole system. Therefore, to entirely specify the task quality, it is necessary to apply constraint techniques for all the criteria, i.e., contouring error, tangential error, and orientation error when synthesizing the control signal. Based on the above-mentioned analysis, in this paper, an active disturbance rejection contouring control is proposed for robotic excavators. The main contribution relies on the development and implementation of an SMO, which is firstly designed to effectively estimate both system states and lumped disturbances and uncertainties during the operation of robotic excavators. These estimates are fed back into the main controller, which is designed based on the TCF approach to separate the tracking error into contouring error and the other error components. Finally, the prescribed performance is guaranteed for all system criteria based on the BLF. Simulation with a high-reliability excavator model is conducted to verify the proposed control performance. The paper is organized as follows: In Section 2, the problem formulation is described. Section 3 explains the proposed SMO design. In Section 4, the design of the proposed control algorithm is presented. Numerical simulation is discussed in Section 5. Finally, Section 6 concludes this work.