T–S fuzzy model-based tracking control of a one-dimensional manipulator actuated by pneumatic artificial muscles

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.

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Analysis and Design of Interval Type-2 Polynomial-Fuzzy-Model-Based Networked Tracking Control Systems

IEEE Transactions on Fuzzy Systems ◽

10.1109/tfuzz.2020.3006587 ◽

2020 ◽

pp. 1-1

Author(s):

Bo Xiao ◽

Hak-Keung Lam ◽

Hongying Zhou ◽

Jianli Gao

Keyword(s):

Control Systems ◽

Tracking Control ◽

Fuzzy Model ◽

Analysis And Design ◽

Model Based ◽

Interval Type

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Model-Based Feedforward Control of a Robotic Manipulator With Pneumatic Artificial Muscles

Volume 1: Development and Characterization of Multifunctional Materials; Modeling, Simulation and Control of Adaptive Systems; Structural Health Monitoring ◽

10.1115/smasis2012-8084 ◽

2012 ◽

Author(s):

Ryan M. Robinson ◽

Norman M. Wereley ◽

Curt S. Kothera

Keyword(s):

Control Algorithm ◽

Controller Design ◽

Feedforward Control ◽

Artificial Muscles ◽

Specific Work ◽

Pneumatic Actuators ◽

Precise Control ◽

Model Based ◽

Pneumatic Artificial Muscles ◽

Dynamics Simulations

Pneumatic artificial muscles (PAMs) are lightweight, flexible actuators capable of higher specific work than comparably-sized hydraulic actuators at the same pressure and electric motors. PAMs are composed of an elastomeric bladder surrounded by a helically braided sleeve. Lightweight, compliant actuators are particularly desirable in portable, heavy-lift robotic systems intended for interaction with humans, such as those envisioned for patient assistance in hospitals and battlefield casualty extraction. However, smooth and precise control remains difficult because of nonlinearities in the dynamic response. The objective of this paper is to develop a control algorithm that satisfies accuracy and smooth motion requirements for a two degree-of-freedom manipulator actuated by pneumatic artificial muscles and intended for interaction with humans, such as lifting a human. This control strategy must be capable of responding to large, abrupt variations in payload weight over a high range of motion. In previous work, the authors detailed the design and construction of a proof-of-concept PAM-based manipulator. The present work investigates the feasibility of combining output feedback using proportional-integral-derivative control or fuzzy logic control with model-based feedforward compensation to achieve improved closed-loop performance. The model upon which the controller is based incorporates the internal airflow dynamics, the geometric parameters of the pneumatic actuators, and the arm dynamics. Simulations were performed in order to validate the control algorithm, guide controller design, and predict optimal gains. Using real-time interface software and hardware, the controller was implemented and experimentally tested on the manipulator. Performance was evaluated for several trajectories, and different payload weights. The effect of varying the feedforward gain was also analyzed. Model refinement further improved performance.

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