An adaptive sliding mode backstepping control for the mobile manipulator with nonholonomic constraints

Chen, Naijian; Song, Fang; Li, Guoping; Sun, Xuan; Ai, Changsheng

doi:10.1016/j.cnsns.2013.02.002

Cited by 111 publications

(58 citation statements)

References 21 publications

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“…A mobile manipulator [9,10] in this study is a redundant 2-DOF manipulator mounted on a wheeled mobile platform, its schematic picture is shown in Figure 1. The mobile manipulator online detects the moving object grasping in the working space by the camera system.…”

Section: System Working Principlementioning

confidence: 99%

Machine Vision Based Information Collection of Mobile Manipulator for Moving Object Grasping

Chen¹,

Song²,

Li³

et al. 2013

Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)

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Abstract-To solve the problem of reliability and real time in visual perception of the mobile manipulator, a visual based information collection system integrated edge detection algorithm and tracking algorithm is proposed. In the vision system, an adaptable threshold edge detection algorithm based on the small world network is presented to improve the reliability and accuracy of edge detection and image segmentation, and the Meanshift algorithm is used to track the mobile objective in real time. Firstly, the edge detection algorithm based on small world phenomenon can adapt the threshold from the global to the local and it improves the ability of the mobile manipulator to find the moving object. Secondly, the edge detection results are used to initialize the target area of Meanshift algorithm, which then tracks the moving objective and extracts parameters' information automatically and real time. The proposed vision system not only meets the need of a mobile manipulator operating on moving objectives but also provides an effective method to find and track objectives automatically.

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Section: System Working Principlementioning

confidence: 99%

Machine Vision Based Information Collection of Mobile Manipulator for Moving Object Grasping

Chen¹,

Song²,

Li³

et al. 2013

Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)

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“…3.3 Backstepping sliding mode controller (BSMC) [15,16] WT is an autonomous nonlinear system and its mathematical model is expressed as Backstepping sliding mode control 405…”

Section: Sliding Mode Control (Smc)mentioning

confidence: 99%

Backstepping sliding mode control of a variable speed wind turbine for power optimization

Saravanakumar

Jena

2015

J. Mod. Power Syst. Clean Energy

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To optimize the energy capture from the wind, wind turbine (WT) should operate at variable speed. Based on the wind speed, the operating regions of the WT are divided into two parts: below and above the rated wind speed. The main aim at below rated wind speed is to maximize the energy capture from the wind with reduced oscillation on the drive train. At above rated wind speed, the aim is to maintain the rated power by using pitch control. This paper presents the control of WT at below rated wind speed by using backstepping sliding mode control (BSMC). In BSMC, generator torque is considered as the control input that depends on the optimal rotor speed. Usually, this optimal rotor speed is derived from effective wind speed. In this paper, effective wind speed is estimated from aerodynamic torque and rotor speed by using the modified Newton Rapshon (MNR) algorithm. Initially, a conventional sliding mode controller (SMC) is applied to the WT, but the performance of the controller was found to be less robust with respect to disturbances. Generally, WT external disturbance is not predictable. To overcome the above drawback, BSMC is proposed and both the controllers are tested with mathematical model and finally validated with the fatigue, aerodynamics, structures, and turbulence (FAST) WT simulator in the presence of disturbances. From the results, it is concluded that the proposed BSMC is more robust than conventional SMC in the presence of disturbances.

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“…To satisfy the Lyapunov stability theory and the reaching law of the controller as in [25], the derivativeṠ is defined aṡ where ℎ and are positive constants. We design the backstepping sliding mode controller as…”

Section: Controller Design For Path Followingmentioning

confidence: 99%

Dynamic Control and Disturbance Estimation of 3D Path Following for the Observation Class Underwater Remotely Operated Vehicle

Huang

Tang

et al. 2013

Advances in Mechanical Engineering

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This study addresses the question of 3D path following for the observation class underwater remotely operated vehicle. The dynamic model of the investigated remote operated vehicle is taken as a coupled multibody system composing of a flexible body and a rigid body. For precise control, the tether cable disturbance has been investigated as well via a dynamic model. Each element of the tethered cable even has been taken as an elastic body, and the waves and current disturbances have been taken into consideration. Based on the multibody system model, an adaptive backstepping sliding mode controller has been designed. To improve the controller's systematic robustness against disturbances, the sliding mode surface and adaptive control rule have been designed, too. Experiments have been performed in a tank, including the 3D path following controls of depth, heading, advance, sideway, polygon line, and spiral line. With current and wave disturbances having been taken into consideration, the tether effect has been analyzed, the efficacy and superiority of adaptive backstepping sliding mode control have been verified. It is further confirmed from the comparisons that the investigated method outperforms those S surface based controllers.

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An adaptive sliding mode backstepping control for the mobile manipulator with nonholonomic constraints

Cited by 111 publications

References 21 publications

Machine Vision Based Information Collection of Mobile Manipulator for Moving Object Grasping

Machine Vision Based Information Collection of Mobile Manipulator for Moving Object Grasping

Backstepping sliding mode control of a variable speed wind turbine for power optimization

Dynamic Control and Disturbance Estimation of 3D Path Following for the Observation Class Underwater Remotely Operated Vehicle

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