Trajectory tracking for mobile manipulator based on nonlinear active disturbance rejection control

Author(s):  
Abdelkarim Brahmi ◽  
Mhmed Algrnaodi ◽  
Maarouf Saad ◽  
Raouf Fareh ◽  
Mohamad Saad
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Chuang Cheng ◽  
Hui Zhang ◽  
Hui Peng ◽  
Zhiqian Zhou ◽  
Bailiang Chen ◽  
...  

Purpose When the mobile manipulator is traveling on an unconstructed terrain, the external disturbance is generated. The load on the end of the mobile manipulator will be affected strictly by the disturbance. The purpose of this paper is to reject the disturbance and keep the end effector in a stable pose all the time, a control method is proposed for the onboard manipulator. Design/methodology/approach In this paper, the kinematics and dynamics models of the end pose stability control system for the tracked robot are built. Through the guidance of this model information, the control framework based on active disturbance rejection control (ADRC) is designed, which keeps the attitude of the end of the manipulator stable in the pitch, roll and yaw direction. Meanwhile, the control algorithm is operated with cloud computing because the research object, the rescue robot, aims to be lightweight and execute work with remote manipulation. Findings The challenging simulation experiments demonstrate that the methodology can achieve valid stability control performance in the challenging terrain road in terms of robustness and real-time. Originality/value This research facilitates the stable posture control of the end-effector of the mobile manipulator and maintains it in a suitable stable operating environment. The entire system can normally work even in dynamic disturbance scenarios and uncertain nonlinear modeling. Furthermore, an example is given to guide the parameter tuning of ADRC by using model information and estimate the unknown internal modeling uncertainty, which is difficult to be modeled or identified.


Author(s):  
Sumit Aole ◽  
Irraivan Elamvazuthi ◽  
Laxman Waghmare ◽  
Balasaheb Patre ◽  
Fabrice Meriaudeau

Trajectory tracking in upper limb rehabilitation exercises is utilized for repeatability of joint movement to improve the patient’s recovery in the early stages of rehabilitation. In this article, non-linear active disturbance rejection control as a combination of non-linear extended-state observer and non-linear state error feedback is used for the sinusoidal trajectory tracking control of the two-link model of an upper limb rehabilitation exoskeleton. The two links represent movements like flexion/extension for both the shoulder joint and the elbow joint in the sagittal plane. The Euler–Lagrange method was employed to acquire a dynamic model of an upper limb rehabilitation exoskeleton. To examine the efficacy and robustness of the proposed method, four disturbances cases in simulation studies with 20% parameter variation were applied. It was found that the non-linear active disturbance rejection control is robust against disturbances and achieves better tracking as compared to proportional–integral–derivative and existing conventional active disturbance rejection control method.


Author(s):  
Mario Ramírez-Neria ◽  
Hebertt Sira-Ramírez ◽  
Rubén Garrido-Moctezuma ◽  
Alberto Luviano-Juárez

In this paper, a systematic procedure for controller design is proposed for a class of nonlinear underactuated systems (UAS), which are non-feedback linearizable but exhibit a controllable (flat) tangent linearization around an equilibrium point. Linear extended state observer (LESO)-based active disturbance rejection control (ADRC) is shown to allow for trajectory tracking tasks involving significantly far excursions from the equilibrium point. This is due to local approximate estimation and compensation of the nonlinearities neglected by the linearization process. The approach is typically robust with respect to other endogenous and exogenous uncertainties and disturbances. The flatness of the tangent model provides a unique structural property that results in an advantageous low-order cascade decomposition of the LESO design, vastly improving the attenuation of noisy and peaking components found in the traditional full order, high gain, observer design. The popular ball and beam system (BBS) is taken as an application example. Experimental results show the effectiveness of the proposed approach in stabilization, as well as in perturbed trajectory tracking tasks.


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