Distributed Control for Coordinated Motion Tracking of Multiple PMAs Cluster

In this paper, a coordinated motion tracking control scheme is investigated for multiple pneumatic muscle actuators (PMAs), to implement the motion coordination for the PMAs cluster. System construction for the proposed coordinated tracking system is elaborated, including the single PMA and cluster system design, communication topology among PMAs, performance analysis of the cluster system. Based on a three-element model structure, the model parameters are identified by several groups of real-time experimental tests, and the mathematical model of PMA applied to a specific pressure range is obtained, which can be used in the design of control algorithm. Through the PID tuning of each PMA and the design of distributed coordination controller of the cluster, the motion positions of PMAs are coordinated. Experimental results demonstrate that the distributed coordinated controller with necessary information interactions between each PMA modeling by proposed experimental identification method is valid for the motion tracking of the PMAs cluster.

[1]  Jianping Yuan,et al.  Distributed Coordinated Motion Tracking of the Linear Switched Reluctance Machine-Based Group Control System , 2016, IEEE Transactions on Industrial Electronics.

[2]  C. Phillips,et al.  Modeling the Dynamic Characteristics of Pneumatic Muscle , 2003, Annals of Biomedical Engineering.

[3]  Asko Ellman,et al.  Position Control of PWM-Actuated Pneumatic Muscle Actuator System , 2011 .

[4]  Michael C. Yip,et al.  High-performance robotic muscles from conductive nylon sewing thread , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[5]  Jinghui Cao,et al.  MIMO Sliding Mode Controller for Gait Exoskeleton Driven by Pneumatic Muscles , 2018, IEEE Transactions on Control Systems Technology.

[6]  George Nikolakopoulos,et al.  Piecewise Affine Modeling and Constrained Optimal Control for a Pneumatic Artificial Muscle , 2014, IEEE Transactions on Industrial Electronics.

[7]  Blake Hannaford,et al.  Measurement and modeling of McKibben pneumatic artificial muscles , 1996, IEEE Trans. Robotics Autom..

[8]  Ching-Ping Chou,et al.  Static and dynamic characteristics of McKibben pneumatic artificial muscles , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[9]  Jun Wu,et al.  Tracking control of pneumatic artificial muscle actuators based on sliding mode and non-linear disturbance observer , 2010 .

[10]  Ziyang Meng,et al.  Leaderless and Leader-Following Consensus With Communication and Input Delays Under a Directed Network Topology , 2011, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[11]  Robert M. Sanner,et al.  Nonlinear Control of Robotic Manipulators Driven by Pneumatic Artificial Muscles , 2016, IEEE/ASME Transactions on Mechatronics.

[12]  Andrew McDaid,et al.  A Systematic Design Strategy for Antagonistic Joints Actuated by Artificial Muscles , 2017, IEEE/ASME Transactions on Mechatronics.

[13]  Jianda Han,et al.  Active modeling for pneumatic artificial muscle , 2016, 2016 IEEE 14th International Workshop on Advanced Motion Control (AMC).

[14]  Norman M. Wereley,et al.  Variable Recruitment Testing of Pneumatic Artificial Muscles for Robotic Manipulators , 2015, IEEE/ASME Transactions on Mechatronics.

[15]  Bram Vanderborght,et al.  Pleated Pneumatic Artificial Muscle-Based Actuator System as a Torque Source for Compliant Lower Limb Exoskeletons , 2014, IEEE/ASME Transactions on Mechatronics.