Improved fuzzy sliding mode control in flexible manipulator actuated by PMAs

Li, Fang; Zhang, Zheng; Wu, Yang; Liu, Kai; Yao, Jiafeng

doi:10.1017/s0263574721001909

Cited by 17 publications

(8 citation statements)

References 13 publications

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“…Once the update values of the PD feedback gains are determined, the PD feedback gains for the controller can be obtained from the following equations [ 35 ]:

…”

Section: Neural Feedback Controllermentioning

confidence: 99%

Neuromechanics-Based Neural Feedback Controller for Planar Arm Reaching Movements

Zhao

Zhang

et al. 2023

Bioengineering

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Based on the principles of neuromechanics, human arm movements result from the dynamic interaction between the nervous, muscular, and skeletal systems. To develop an effective neural feedback controller for neuro-rehabilitation training, it is important to consider both the effects of muscles and skeletons. In this study, we designed a neuromechanics-based neural feedback controller for arm reaching movements. To achieve this, we first constructed a musculoskeletal arm model based on the actual biomechanical structure of the human arm. Subsequently, a hybrid neural feedback controller was developed that mimics the multifunctional areas of the human arm. The performance of this controller was then validated through numerical simulation experiments. The simulation results demonstrated a bell-shaped movement trajectory, consistent with the natural motion of human arm movements. Furthermore, the experiment testing the tracking ability of the controller revealed real-time errors within one millimeter, with the tensile force generated by the controller’s muscles being stable and maintained at a low value, thereby avoiding the issue of muscle strain that can occur due to excessive excitation during the neurorehabilitation process.

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“…Once the update values of the PD feedback gains are determined, the PD feedback gains for the controller can be obtained from the following equations [ 35 ]:

…”

Section: Neural Feedback Controllermentioning

confidence: 99%

Neuromechanics-Based Neural Feedback Controller for Planar Arm Reaching Movements

Zhao

Zhang

et al. 2023

Bioengineering

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“…Dong et al 12 developed a flexible manipulator with a streamlined structure and swallowing function for fruit and vegetable picking, which solved the problem of easily damaging the surface of the fruit skin. Jin and Lin 13 developed a flexible manipulator by the underdrive principle, which can smoothly grasp the target pieces not exceeding 300 g. Li et al 14 established a bionic flexible manipulator based on PMAs by simulating the motion characteristics of the human upper arm and proposed a sliding mode control based on saturation function to improve the tracking accuracy of the manipulator. Geng et al 15 proposed a novel pneumatic-driven multifinger flexible manipulator, which can achieve smooth target grasping.…”

Section: Introductionmentioning

confidence: 99%

Research on the grasping characteristics of composite-driven double-finger flexible manipulator

Li,

Chen

2024

Science Progress

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Aiming at the flexible manipulator grasping complex target parts of different shapes, a double-finger flexible manipulator model is proposed. The manipulator is composed of a flexible mechanical finger, a driving component and a position compensation mechanism. It imitates the motion characteristics of human finger joints and follows the principle of double-fingered grasping. According to the structural characteristics of the target contour, the grasping features of the target contour are extracted. Through the motion principle of the flexible manipulator, the kinematic model of the envelope clamping process of the manipulator target is carried out. Finally, the flexible manipulator experimental platform is built to verify the grasping characteristics of the flexible manipulator target. The results show that the manipulator can realize the adaptive grasping of cylinder and cuboid parts, which have high grasping reliability and stability.

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“…Sliding mode control (SMC) [7][8][9][10][11][12][13][14][15][16][17][18], a robust control approach, is known to be effective in controlling manipulators. While possessing strong robustness against uncertainties and disturbances, SMC is, on the other hand, subject to some drawbacks, for instance, highly switching gains, long convergence time, and chattering in the response.…”

Section: Introductionmentioning

confidence: 99%

Adaptive fractional-order integral fast terminal sliding mode and fault-tolerant control of dual-arm robots

Tuan,

2024

Robotica

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Closed-loop kinematics of a dual-arm robot (DAR) often induces motion conflict. Control formulation is increasingly difficult in face of actuator failures. This article presents a new approach for fault-tolerant control of DARs based on advanced sliding mode control. A comprehensive fractional-order model is proposed taking nonlinear viscous and viscoelastic friction at the joints into account. Using integral fast terminal sliding mode control and fractional calculus, we develop two robust controllers for robots subject to motor faults, parametric uncertainties, and disturbances. Their merits rest with their strong robustness, speedy finite-time convergence, shortened reaching phase, and flexible selection of derivative orders. To avoid the need for full knowledge of faults, robot parameters, and disturbances, two versions of the proposed approach, namely adaptive integral fractional-order fast terminal sliding mode control, are developed. Here, an adaptation mechanism is equipped for estimating a common representative of individual uncertainties. Simulation and experiment are provided along with an extensive comparison with existing approaches. The results demonstrate the superiority of the proposed control technique. The robot performs well the tasks with better responses (e.g., with settling time reduced by at least 16%).

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Improved fuzzy sliding mode control in flexible manipulator actuated by PMAs

Cited by 17 publications

References 13 publications

Neuromechanics-Based Neural Feedback Controller for Planar Arm Reaching Movements

Neuromechanics-Based Neural Feedback Controller for Planar Arm Reaching Movements

Research on the grasping characteristics of composite-driven double-finger flexible manipulator

Adaptive fractional-order integral fast terminal sliding mode and fault-tolerant control of dual-arm robots

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