scholarly journals A Multistate Friction Model for the Compensation of the Asymmetric Hysteresis in the Mechanical Response of Pneumatic Artificial Muscles

Actuators ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 49 ◽  
Author(s):  
Alessia Capace ◽  
Carlo Cosentino ◽  
Francesco Amato ◽  
Alessio Merola
Keyword(s):  
Tracking Control ◽  
Mechanical Response ◽  
Control Strategies ◽  
Friction Model ◽  
Assistive Robotics ◽  
Surgical Instruments ◽  
Artificial Muscles ◽  
Soft Robots ◽  
Pneumatic Artificial Muscles ◽  
Compliant Actuators

These days, biomimetic and compliant actuators have been made available to the main applications of rehabilitation and assistive robotics. In this context, the interaction control of soft robots, mechatronic surgical instruments and robotic prostheses can be improved through the adoption of pneumatic artificial muscles (PAMs), a class of compliant actuators that exhibit some similarities with the structure and function of biological muscles. Together with the advantage of implementing adaptive compliance control laws, the nonlinear and hysteretic force/length characteristics of PAMs pose some challenges in the design and implementation of tracking control strategies. This paper presents a parsimonious and accurate model of the asymmetric hysteresis observed in the force response of PAMs. The model has been validated through the experimental identification of the mechanical response of a small-sized PAM where the asymmetric effects of hysteresis are more evident. Both the experimental results and a comparison with other dynamic friction models show that the proposed model could be useful to implement efficient compensation strategies for the tracking control of soft robots.

Actuation of untethered pneumatic artificial muscles and soft robots using magnetically induced liquid-to-gas phase transitions

2020 ◽  
Vol 5 (41) ◽  
pp. eaaz4239 ◽  
Author(s):  
Seyed M. Mirvakili ◽  
Douglas Sim ◽  
Ian W. Hunter ◽  
Robert Langer
Keyword(s):  
Phase Transition ◽  
Gas Phase ◽  
High Performance ◽  
Artificial Muscle ◽  
Artificial Muscles ◽  
Peak Strain ◽  
Soft Robots ◽  
Robotic Arms ◽  
Actuation Mechanism ◽  
Pneumatic Artificial Muscles

Pneumatic artificial muscles have been widely used in industry because of their simple and relatively high-performance design. The emerging field of soft robotics has also been using pneumatic actuation mechanisms since its formation. However, these actuators/soft robots often require bulky peripheral components to operate. Here, we report a simple mechanism and design for actuating pneumatic artificial muscles and soft robotic grippers without the use of compressors, valves, or pressurized gas tanks. The actuation mechanism involves a magnetically induced liquid-to-gas phase transition of a liquid that assists the formation of pressure inside the artificial muscle. The volumetric expansion in the liquid-to-gas phase transition develops sufficient pressure inside the muscle for mechanical operations. We integrated this actuation mechanism into a McKibben-type artificial muscle and soft robotic arms. The untethered McKibben artificial muscle generated actuation strains of up to 20% (in 10 seconds) with associated work density of 40 kilojoules/meter3, which favorably compares with the peak strain and peak energy density of skeletal muscle. The untethered soft robotic arms demonstrated lifting objects with an input energy supply from only two Li-ion batteries.

Passive and Active Control Strategies of a Leg Rehabilitation Exoskeleton Powered by Pneumatic Artificial Muscles

2017 ◽  
Vol 31 (10) ◽  
pp. 1759021 ◽  
Author(s):  
Chen Su ◽  
Ao Chai ◽  
Xikai Tu ◽  
Hongyu Zhou ◽  
Haiqiang Wang ◽  
...  
Keyword(s):  
Lower Limb ◽  
Sliding Mode ◽  
Control Strategies ◽  
Low Cost ◽  
Gait Training ◽  
Interaction Force ◽  
Gait Rehabilitation ◽  
Artificial Muscles ◽  
Model Free ◽  
Pneumatic Artificial Muscles

Nerve injury can cause lower limb paralysis and gait disorder. Currently lower limb rehabilitation exoskeleton robots used in the hospitals need more power to correct abnormal motor patterns of stroke patients’ legs. These gait rehabilitation robots are powered by cumbersome and bulky electric motors, which provides a poor user experience. A newly developed gait rehabilitation exoskeleton robot actuated by low-cost and lightweight pneumatic artificial muscles (PAMs) is presented in this research. A model-free proxy-based sliding mode control (PSMC) strategy and a model-based chattering mitigation robust variable control (CRVC) strategy were developed and first applied in rehabilitation trainings, respectively. As the dynamic response of PAM due to the compressed air is low, an innovative intention identification control strategy was taken in active trainings by the use of the subject’s intention indirectly through the estimation of the interaction force between the subject’s leg and the exoskeleton. The proposed intention identification strategy was verified by treadmill-based gait training experiments.

scholarly journals Force-Free Control for Direct Teaching of a Surgical Assistant Robot End Effector with Wire-Driven Bidirectional Telescopic Mechanism

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3498
Author(s):  
Youqiang Zhang ◽  
Cheol-Su Jeong ◽  
Minhyo Kim ◽  
Sangrok Jin
Keyword(s):  
Control Algorithm ◽  
Position Control ◽  
Friction Model ◽  
Surgical Instruments ◽  
Control Input ◽  
End Effector ◽  
Motor Current ◽  
Direct Teaching ◽  
End Effectors ◽  
Teaching Operation

This paper shows the design and modeling of an end effector with a bidirectional telescopic mechanism to allow a surgical assistant robot to hold and handle surgical instruments. It also presents a force-free control algorithm for the direct teaching of end effectors. The bidirectional telescopic mechanism can actively transmit force both upwards and downwards by staggering the wires on both sides. In order to estimate and control torque via motor current without a force/torque sensor, the gravity model and friction model of the device are derived through repeated experiments. The LuGre model is applied to the friction model, and the static and dynamic parameters are obtained using a curve fitting function and a genetic algorithm. Direct teaching control is designed using a force-free control algorithm that compensates for the estimated torque from the motor current for gravity and friction, and then converts it into a position control input. Direct teaching operation sensitivity is verified through hand-guiding experiments.

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