CLC number: TP242.3
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2021-08-24
Cited: 0
Clicked: 4650
Citations: Bibtex RefMan EndNote GB/T7714
Cong Chen, Jun Zou. Adaptive robust control of soft bending actuators: an empirical nonlinear model-based approach[J]. Journal of Zhejiang University Science A, 2021, 22(9): 681-694.
@article{title="Adaptive robust control of soft bending actuators: an empirical nonlinear model-based approach",
author="Cong Chen, Jun Zou",
journal="Journal of Zhejiang University Science A",
volume="22",
number="9",
pages="681-694",
year="2021",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.A2100076"
}
%0 Journal Article
%T Adaptive robust control of soft bending actuators: an empirical nonlinear model-based approach
%A Cong Chen
%A Jun Zou
%J Journal of Zhejiang University SCIENCE A
%V 22
%N 9
%P 681-694
%@ 1673-565X
%D 2021
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A2100076
TY - JOUR
T1 - Adaptive robust control of soft bending actuators: an empirical nonlinear model-based approach
A1 - Cong Chen
A1 - Jun Zou
J0 - Journal of Zhejiang University Science A
VL - 22
IS - 9
SP - 681
EP - 694
%@ 1673-565X
Y1 - 2021
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.A2100076
Abstract: Soft robotics, compared with their rigid counterparts, are able to adapt to uncharted environments, are superior in safe human-robot interactions, and have low cost, owing to the native compliance of the soft materials. However, customized complex structures, as well as the nonlinear and viscoelastic soft materials, pose a great challenge to accurate modeling and control of soft robotics, and impose restrictions on further applications. In this study, a unified modeling strategy is proposed to establish a complete dynamic model of the most widely used pneumatic soft bending actuator. First, a novel empirical nonlinear model with parametric and nonlinear uncertainties is identified to describe the nonlinear behaviors of pneumatic soft bending actuators. Second, an inner pressure dynamic model of a pneumatic soft bending actuator is established by introducing a modified valve flow rate model of the unbalanced pneumatic proportional valves. Third, an adaptive robust controller is designed using a backstepping method to handle and update the nonlinear and uncertain system. Finally, the experimental results of comparative trajectory tracking control indicate the validity of the proposed modeling and control method.
[1]Abbasi P, Nekoui MA, Zareinejad M, et al., 2020. Position and force control of a soft pneumatic actuator. Soft Robotics, 7(5):550-563.
[2]Al-Ibadi A, Nefti-Meziani S, Davis S, 2018. Active soft end effectors for efficient grasping and safe handling. IEEE Access, 6:23591-23601.
[3]Bieze TM, Largilliere F, Kruszewski A, et al., 2018. Finite element method-based kinematics and closed-loop control of soft, continuum manipulators. Soft Robotics, 5(3):348-364.
[4]Blumenschein LH, Gan LT, Fan JA, et al., 2018. A tip-extending soft robot enables reconfigurable and deployable antennas. IEEE Robotics and Automation Letters, 3(2):949-956.
[5]Boyraz P, Runge G, Raatz A, 2018. An overview of novel actuators for soft robotics. Actuators, 7(3):48.
[6]Bruder D, Gillespie B, Remy CD, et al., 2019. Modeling and control of soft robots using the Koopman operator and model predictive control. Proceedings of Robotics: Science and Systems.
[7]Chen C, Tang W, Hu Y, et al., 2020. Fiber-reinforced soft bending actuator control utilizing on/off valves. IEEE Robotics and Automation Letters, 5(4):6732-6739.
[8]Chen WB, Xiong CH, Liu CL, et al., 2019. Fabrication and dynamic modeling of bidirectional bending soft actuator integrated with optical waveguide curvature sensor. Soft Robotics, 6(4):495-506.
[9]Deimel R, Brock O, 2013. A compliant hand based on a novel pneumatic actuator. Proceedings of the IEEE International Conference on Robotics and Automation, p.2047-2053.
[10]Deimel R, Radke M, Brock O, 2016. Mass control of pneumatic soft continuum actuators with commodity components. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, p.774-779.
[11]Falkenhahn V, Hildebrandt A, Neumann R, et al., 2017. Dynamic control of the bionic handling assistant. IEEE/ ASME Transactions on Mechatronics, 22(1):6-17.
[12]Fan JZ, Du QL, Yu QG, et al., 2020. Biologically inspired swimming robotic frog based on pneumatic soft actuators. Bioinspiration & Biomimetics, 15(4):046006.
[13]Fang G, Wang XM, Wang K, et al., 2019. Vision-based online learning kinematic control for soft robots using local Gaussian process regression. IEEE Robotics and Automation Letters, 4(2):1194-1201.
[14]Finnemore EJ, Franzini JB, 2002. Fluid Mechanics with Engineering Applications. McGraw-Hill, New York, USA, p.597.
[15]Franco E, Garriga-Casanovas A, 2021. Energy-shaping control of soft continuum manipulators with in-plane disturbances. The International Journal of Robotics Research, 40(1):236-255.
[16]Gerboni G, Diodato A, Ciuti G, et al., 2017. Feedback control of soft robot actuators via commercial flex bend sensors. IEEE/ASME Transactions on Mechatronics, 22(4):1881-1888.
[17]Hamidi A, Almubarak Y, Tadesse Y, 2019. Multidirectional 3D-printed functionally graded modular joint actuated by TCP FL muscles for soft robots. Bio-Design and Manufacturing, 2(4):256-268.
[18]Hyatt P, Kraus D, Sherrod V, et al., 2019a. Configuration estimation for accurate position control of large-scale soft robots. IEEE/ASME Transactions on Mechatronics, 24(1):88-99.
[19]Hyatt P, Wingate D, Killpack MD, 2019b. Model-based control of soft actuators using learned non-linear discrete-time models. Frontiers in Robotics and AI, 6:22.
[20]Ibrahim S, Krause JC, Raatz A, 2019. Linear and nonlinear low level control of a soft pneumatic actuator. Proceedings of the 2nd IEEE International Conference on Soft Robotics, p.434-440.
[21]Jung J, Park M, Kim D, et al., 2020. Optically sensorized elastomer air chamber for proprioceptive sensing of soft pneumatic actuators. IEEE Robotics and Automation Letters, 5(2):2333-2340.
[22]Katzschmann RK, 2018. Building and Controlling Fluidically Actuated Soft Robots: from Open Loop to Model-based Control. PhD Thesis, Massachusetts Institute of Technology, Massachusetts, USA.
[23]Khan AH, Li S, 2020. Sliding mode control with PID sliding surface for active vibration damping of pneumatically actuated soft robots. IEEE Access, 8:88793-88800.
[24]Khan AH, Shao ZL, Li S, et al., 2020. Which is the best PID variant for pneumatic soft robots? An experimental study. IEEE/CAA Journal of Automatica Sinica, 7(2):451-460.
[25]Kim S, Laschi C, Trimmer B, 2013. Soft robotics: a bioinspired evolution in robotics. Trends in Biotechnology, 31(5):287-294.
[26]Kwon J, Yoon SJ, Park YL, 2020. Flat inflatable artificial muscles with large stroke and adjustable force-length relations. IEEE Transactions on Robotics, 36(3):743-756.
[27]Laschi C, Mazzolai B, Cianchetti M, 2016. Soft robotics: technologies and systems pushing the boundaries of robot abilities. Science Robotics, 1(1):eaah3690.
[28]Li MH, Kang RJ, Branson DT, et al., 2018. Model-free control for continuum robots based on an adaptive Kalman filter. IEEE/ASME Transactions on Mechatronics, 23(1):286-297.
[29]Liu S, Yao B, 2008. Coordinate control of energy saving programmable valves. IEEE Transactions on Control Systems Technology, 16(1):34-45.
[30]Luo C, Wang K, Li GY, et al., 2019. Development of active soft robotic manipulators for stable grasping under slippery conditions. IEEE Access, 7:97604-97613.
[31]Marchese AD, Tedrake R, Rus D, 2016. Dynamics and trajectory optimization for a soft spatial fluidic elastomer manipulator. The International Journal of Robotics Research, 35(8):1000-1019.
[32]Mohanty A, Yao B, 2011. Indirect adaptive robust control of hydraulic manipulators with accurate parameter estimates. IEEE Transactions on Control Systems Technology, 19(3):567-575.
[33]Müller D, Raisch A, Hildebrandt A, et al., 2020. Nonlinear model based dynamic control of pneumatic driven quasi continuum manipulators. Proceedings of the IEEE/SICE International Symposium on System Integration, p.277-282.
[34]Pang W, Wang JB, Fei YQ, 2018. The structure, design, and closed-loop motion control of a differential drive soft robot. Soft Robotics, 5(1):71-80.
[35]Polygerinos P, Wang Z, Overvelde JTB, et al., 2015. Modeling of soft fiber-reinforced bending actuators. IEEE Transactions on Robotics, 31(3):778-789.
[36]Polygerinos P, Correll N, Morin SA, et al., 2017. Soft robotics: review of fluid-driven intrinsically soft devices; manufacturing, sensing, control, and applications in human-robot interaction. Advanced Engineering Materials, 19(12):1700016.
[37]Skorina EH, Luo M, Ozel S, et al., 2015. Feedforward augmented sliding mode motion control of antagonistic soft pneumatic actuators. Proceedings of the IEEE International Conference on Robotics and Automation, p.2544-2549.
[38]Tang ZQ, Heung HL, Tong KY, et al., 2020. A probabilistic model-based online learning optimal control algorithm for soft pneumatic actuators. IEEE Robotics and Automation Letters, 5(2):1437-1444.
[39]Thuruthel TG, Ansari Y, Falotico E, et al., 2018. Control strategies for soft robotic manipulators: a survey. Soft Robotics, 5(2):149-163.
[40]Wang T, Zhang YC, Chen Z, 2018. Design and verification of model-based nonlinear controller for fluidic soft actuators. Proceedings of the IEEE/ASME International Conference on Advanced Intelligent Mechatronics, p.1178-1183.
[41]Xiang Z, 2010. Research on the Key Technologies of Pneumatic High-speed on-off Valve. PhD Thesis, Zhejiang University, Hangzhou, China (in Chinese).
[42]Yang Y, Li Y, Chen Y, 2018. Principles and methods for stiffness modulation in soft robot design and development. Bio-Design and Manufacturing, 1(1):14-25.
[43]Yao B, 1997. High performance adaptive robust control of nonlinear systems: a general framework and new schemes. Proceedings of the 36th IEEE Conference on Decision and Control, p.2489-2494.
[44]Yao B, Bu FP, Reedy J, et al., 2000. Adaptive robust motion control of single-rod hydraulic actuators: theory and experiments. IEEE/ASME Transactions on Mechatronics, 5(1):79-91.
[45]Zhang C, Zhu P, Lin Y, et al., 2021. Fluid-driven artificial muscles: bio-design, manufacturing, sensing, control, and applications. Bio-Design and Manufacturing, 4(1):123-145.
[46]Zhang J, Sheng J, ONeill CT, et al., 2019. Robotic artificial muscles: current progress and future perspectives. IEEE Transactions on Robotics, 35(3):761-781.
[47]Zhou JS, Chen XJ, Chang Y, et al., 2019. A soft-robotic approach to anthropomorphic robotic hand dexterity. IEEE Access, 7:101483-101495.
Open peer comments: Debate/Discuss/Question/Opinion
<1>