scholarly journals Nonlinear Control of a Pneumatic Muscle Actuator System

2001 ◽  
Vol 34 (6) ◽  
pp. 1129-1134
Author(s):  
Pablo Carbonell ◽  
Zhong-Ping Jiang ◽  
Daniel W. Repperger
2013 ◽  
Vol 284-287 ◽  
pp. 1936-1940
Author(s):  
Liu Hsu Lin ◽  
Jai Yush Yen ◽  
Fu Cheng Wang

This paper describes the application of system identification techniques and robust control strategies to a pneumatic muscle actuator system. Due to the inherent nonlinear and time-varying characteristics of this system, it is difficult to achieve excellent performance using conventional control methods. Therefore, we apply identification techniques to model the system as linear transfer functions and regard the un-modeled dynamics as system uncertainties. Because robust control is well-known for its capability in dealing with system uncertainties, we then apply robust control strategies to guarantee system stability and performance for the system. This work is carried out in three parts. First, the pneumatic muscle actuator system was modeled as linear transfer functions. Second, robust control theorem were utilized to design a Hinf robust controller to deal with system uncertainties and performance requirements. Finally, the designed controller was implemented for experimental verifications and compared with a conventional PID controller. From the experimental results, the proposed Hinf robust controller is deemed effective.


2014 ◽  
Vol 15 (1) ◽  
pp. 19-31 ◽  
Author(s):  
Ville T. Jouppila ◽  
S. Andrew Gadsden ◽  
Gary M. Bone ◽  
Asko U. Ellman ◽  
Saeid R. Habibi

2016 ◽  
Vol 9 (4) ◽  
pp. 301-312 ◽  
Author(s):  
Vasanthan Sakthivelu ◽  
Shin-Horng Chong ◽  
Ming Hui Tan ◽  
Mariam Md Ghazaly

2013 ◽  
Vol 37 (3) ◽  
pp. 581-590 ◽  
Author(s):  
Liu-Hsu Lin ◽  
Jia-Yush Yen ◽  
Fu-Cheng Wang

This paper presents the modeling and robust control of a pneumatic muscle actuator system. Due to the inherent nonlinear and time-varying characteristics of this system, it is difficult to achieve excellent performance using conventional control methods. Therefore, we apply identification techniques to model the system as linear transfer functions and regard the un-modeled dynamics as system uncertainties. Because H∞ robust control is well-known for its capability in dealing with system uncertainties, we then apply H∞ robust control strategies to guarantee system stability and performance for the system. From the experimental results, the proposed H∞ robust controller is deemed effective.


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