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

Abstract

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.

Handheld Active Add-On Control Unit for a Cable-Driven Flexible Endoscope

“…This means that the iPPROM risk could be lowered if this instrument was used in a real TTTS procedure. However, the current basic hysteresis modeling approach should be improved by e.g., using hysteresis compensation (Mei et al, 2017;Capace et al, 2019) or deep learning algorithms (Li et al, 2019). This would probably encourage the operator to use the flexible feature of the instrument even more, since it would be more responsive to the user input.…”

“…In order to solve this problem, both friction and muscles hysteresis could be characterized in greater detail, by e.g., characterizing the hysteresis over different bending angle ranges. Another solution could make use of hysteresis compensation algorithms for the muscles, like suggested by Mei et al (2017) or Capace et al (2019). Even though this 10 • error is important, one should realize that this is a human-in-the-loop system.…”

An Adaptive Fast Terminal Sliding Mode Controller of Exercise-Assisted Robotic Arm for Elbow Joint Rehabilitation Featuring Pneumatic Artificial Muscle Actuator

“…Indeed, a PAM actuator is one of the most promising actuators for industrial application and devices because it can offer many merits, such as compliant behavior, soft and flexible structure, high power to weight ratio, lightweight, etc. However, there still exists significant drawbacks that are time-varying nonlinear dynamics and hysteresis characteristics [19,20] which may cause difficulties for applying traditional control algorithms such as Proportional Integral (PI), PID, linear control techniques or model-based controllers to manage the operation of PAM actuators. In recent years, the nonlinear control algorithms for PAM actuators have been proposed based on neural network [21,22], backstepping control [23].…”

Integrated Capacitance Sensing for Miniature Artificial Muscle Actuators

“…This model is used in feed forward, allowing an open-loop control of the muscle. Capace et al [9] introduced a multistate friction model in order to compensate for the muscle hysteresis. These methods do not require extra sensors and thus provides a compact system.…”