Full‐Order Sliding‐Mode Control of Rigid Robotic Manipulators

Feng, Yong; Zhou, Minghao; Yu, Xinghuo; Han, Fengling

doi:10.1002/asjc.1813

Cited by 20 publications

(13 citation statements)

References 35 publications

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“…Robotic manipulation is an emerging topic for robot systems [1][2][3][4][5][6]. Due to the advantages involved compared with typical grippers, for complex grasping tasks, the end-effector of the robot manipulator is envisaged to attain the flexibility of the human hand, especially in industrial production lines with frequently changing end-effectors [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

A two‐step method for 4‐pin form‐closure gripper with grasping force optimization

2021

Asian Journal of Control

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Grasp planning and the grasping force optimization are challenging issues associated with the dexterous robotic hand grasping problem. To ensure a safe, fast, and stable grasp for robots, careful determination of the grasping points and the grasping forces is required. The former creates an open question because of the availability of multiple solutions. The latter is formulated as a problem for minimizing an objective function subject to form-closure constraints and balance constraints of external forces. In this work, we propose a novel approach for the grasping force optimization of the 4-pin environmental constraint-based form-closure grasp using dynamic neural networks. To find a form-closure grasp, we propose an environmental constraint-based algorithm and convert it to a problem of finding the local minima of a constraint region, resulting in an easy determination of the grasping points with the guarantee of grasping safety. To satisfy the grasping force limit of the contact points, we solve the grasping force optimization problem with friction constraint, which maximize the efficiency of the applied force and power of the dexterous hand. The proposed approach is evaluated with 4-pin gripper, and the result demonstrates that we can plan a safe, fast, and stable grasp from any initial state to a form-closure grasping state.

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Section: Introductionmentioning

confidence: 99%

A two‐step method for 4‐pin form‐closure gripper with grasping force optimization

2021

Asian Journal of Control

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“…Feng et al 28 have proposed a full-order sliding-mode controller for rigid robotic manipulators. The work suggested a time-varying gain to adjust the gain of the signum function.…”

Section: Introductionmentioning

confidence: 99%

Optimal super-twisting sliding mode control design of robot manipulator: Design and comparison study

Al-Dujaili

Falah

Humaidi

et al. 2020

International Journal of Advanced Robotic Systems

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This article presents a tracking control design for two-link robot manipulators. To achieve robust tracking control performance, a super-twisting sliding mode control (STSMC) is derived. The stability of the system based on the proposed approach is proved based on the Lyapunov theorem. However, one problem with the designed STSMC is to properly set its parameters during the design. Therefore, it is proposed a social spider optimization (SSO) to tune these design parameters to improve the dynamic performance of the robot manipulator controlled considering STSMC. The performance of the STSMC approach based on SSO is compared to that based on particle swarming optimization (PSO) in terms of dynamic performance and robustness characteristics. The effectiveness of the proposed optimal controllers is verified by simulations within the MATLAB software. It is verified that the performance given by SSO-based STSMC outperforms that resulting from PSO-based STSMC. The experimental results are conducted based on LabVIEW 2019 software to validate the numerical simulation.

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“…In order to deal with system uncertainties, and to enhance the robustness of the system, they combined the sliding mode control (SMC) with backstepping controller. Owing to its robustness against uncertainties and its simple design, SMC has become very popular as a robust controller for uncertain systems [23][24][25][26][27][28]. The main goal of using an SMC is to control a system which is subjected to uncertainties and disturbances.…”

Section: Introductionmentioning

confidence: 99%

Trajectory tracking control of a wheeled mobile robot in the presence of matched uncertainties via a composite control approach

Shafei

Bahrami

2020

Asian Journal of Control

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In the present work, a novel method is devised for controlling an uncertain wheeled mobile robot (WMR) in a desired path. To achieve this objective, an optimal and robust control system with adaptive gains is combined to benefit from the advantages of both methods. In fact, applying this controller not only controls a nonlinear system robustly against uncertainties and external disturbances, but also optimizes a quadratic cost function. Also, since the upper bound of uncertainty is determined by an adaptive law, it does not need to be adjusted manually. To ensure the designed controller's finite time stability, Lyapunov theory is used. Finally, to illustrate the effectiveness of the proposed control method, a case study involving a WMR is presented. By comparing the results of this approach with those of an adaptive sliding mode control (ASMC), it is shown that the proposed controller uses less control effort, relative to the ASMC controller, to stabilize the uncertain WMR in the presence of external disturbances.

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Full‐Order Sliding‐Mode Control of Rigid Robotic Manipulators

Cited by 20 publications

References 35 publications

A two‐step method for 4‐pin form‐closure gripper with grasping force optimization

A two‐step method for 4‐pin form‐closure gripper with grasping force optimization

Optimal super-twisting sliding mode control design of robot manipulator: Design and comparison study

Trajectory tracking control of a wheeled mobile robot in the presence of matched uncertainties via a composite control approach

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