Qiang Sun

Mr. Qiang Sun


Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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14 January 2022 in Micromachines
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Journal Article
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Yinglong ChenYinglong Chen
Yinglong Chen
QSQiang Sun
Qiang Sun
QGQiang Guo
Qiang Guo
YGYongjun Gong
Yongjun Gong
Compared with rigid robots, soft robots have better adaptability to the environment because of their pliability. However, due to the lower structural stiffness of the soft manipulator, the posture of the manipulator is usually decided by the weight and the external load under operating conditions. Therefore, it is necessary to conduct dynamics modeling and movement analysis of the soft manipulator. In this paper, a fabric reinforced soft manipulator driven by a water hydraulic system is firstly proposed, and the dynamics of both the soft manipulator and hydraulic system are considered. Specifically, a dynamic model of the soft manipulator is established based on an improved Newton–Euler iterative method, which comprehensively considers the influence of inertial force, elastic force, damping force, as well as combined bending and torsion moments. The dynamics of the water hydraulic system consider the effects of cylinder inertia, friction, and water response. Finally, the accuracy of the proposed dynamic model is verified by comparing the simulation results with the experimental data about the steady and dynamic characteristics of the soft manipulator under various conditions. The results show that the maximum sectional error is about 0.0245 m and that the maximum cumulative error is 0.042 m, which validate the effectiveness of the proposed model.

Verified
Journal Article
Open access
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Yinglong ChenYinglong Chen
Yinglong Chen
QSQiang Sun
Qiang Sun
JWJia Wang
Jia Wang
JZJunhao Zhang
Junhao Zhang
PZPengyu Zhao
Pengyu Zhao
YGYongjun Gong
Yongjun Gong
Soft manipulators have desirable environmental compatibility because of their pliability. However, this pliability also brings challenges to modeling and control when considering contact or collision with the environment. In previous work, we established several mathematical models for describing fluidic soft manipulators under environmental effects and verified their accuracy. However, the controller design for a soft manipulator is still a significant challenge, especially under the conditions of environmental contact. In this paper, we build upon our previously established work by conducting feedforward compensation for a soft manipulator under contact constraints and designing a sliding mode controller based on an operational space dynamics model. Then, we combine the feedforward compensation model with the sliding mode controller to realize accurate position control of the soft manipulator. Finally, simulation and experimental results show that this controller can accurately and effectively control the position of the soft manipulator.

5 December 2024 in Biomimetics
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Journal Article
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BYBo Yan
Bo Yan
Yinglong ChenYinglong Chen
Yinglong Chen
CZCheng Zhou
Cheng Zhou
QSQiang Sun
Qiang Sun
FGFei Gao
Fei Gao
XXXingtian Xiao
Xingtian Xiao
The inherent passive impedance characteristics of soft robotic arms provide excellent environmental adaptability. When a soft robotic arm interacts with its surroundings, its passive impedance responds swiftly, preventing rigid collisions that could damage the arm and ensuring high safety. However, during the movement of the soft robotic arm, these passive impedance properties are uncontrollable, making it impossible to achieve precise impedance control in constrained environments by relying solely on passive mechanisms. Therefore, this paper integrated active impedance control with the passive impedance characteristics of soft robotic arms, proposing an active–passive composite impedance controller. Additionally, a position-based impedance controller was designed for comparative analysis. Finally, this article developed both control systems and conducted simulations and experiments, demonstrating that the composite active–passive impedance controller offers superior control performance and environmental adaptability.