Adaptive Integral-Type Neural Sliding Mode Control for Pneumatic Muscle Actuator
Dang Xuan Ba*, Kyoung Kwan Ahn*, and Nguyen Trong Tai**
*University of Ulsan, 93 Daehak-ro, Nam-gu, Ulsan 680-749, Republic of Korea
**Faculty of Electrical and Electronic Engineering, Ho Chi Minh City University of Technology, 268 Ly Thuong Kiet Str, Dist. 10, Ho Chi Minh City, Viet Nam
This paper presents an integral-type adaptive sliding mode controller integrated into a neural network for position-tracking control of a pneumatic muscle actuator testing system. Stability of the closed-loop system is covered by the sliding mode algorithm while both control error and control energy are minimized by the neural network. With only four weight factors in the hidden layer and two weight factors in the output layer, the network provides a very high calculation speed. Then, the approach is successfully verified on a real-time system under different working conditions. By comparing it with a proportional-integraldifferential controller on the same system and under the same working conditions, the effectiveness of the designed controller is confirmed.
-  D. Sasaki, T. Noritsugu, and M. Takaiwa, “Development and application of high contractile pneumatic artificial muscle,” Int. J. of Automation Technology, Vol.4, No.4, pp. 531-537, 2011.
-  X. Li, T. Noritsugu, M. Takaiwa, and D. Sasaki, “Design of wearable power assist wear for low back support using pneumatic actuators,” Int. J. of Automation Technology, Vol.7, No.2, pp. 228-236, 2013.
-  Y. K. Lee and I. Shimoyama, “A skeletal framework artificial hand actuated by pneumatic artificial muscle,” Proc. of the 1999 IEEE Int. Conf. on Robotics and Automation, pp. 926-931, May 1999.
-  B. Tondu, S. Ippolito, J. Guiochet, and A. Daidie, “A seven-degreesof-freedom robot-arm driven by pneumatic artificial muscles for humanoid robots,” The Int. J. of Robotics Research, Vol.24, No.4, pp. 257-274, Apr. 2005.
-  X. Zhu, G. Tao, B. Yao, and J. Cao, “Adaptive robust posture control of a parallel manipulator driven by pneumatic muscles,” Automica, Vol.44, No.9, pp. 2248-2257, 2008.
-  K. Kawashima, T. Sasaki, A. Ohkubo, T. Miyata, and T. Kagawa, “Application of robot arm using fiber knitted type pneumatic artificial rubber muscles,” Proc. of the 2004 IEEE Int. Conf. on Robotics and Automation, pp. 4937-4942, Apr. 2004.
-  S. Ganguly, A. Garg, A. Pasricha, and S. K. Dwivedy, “Control of pneumatic artificial muscle system through experimental modelling,” Mechatronics, Vol.22, No.8, pp. 1135-1147, 2012.
-  T. Hesselroth, K. Sarkar, P. Patrick van der Smagt, and K. Schulten, “Neural network control of a pneumatic robot arm,” IEEE Trans. on Systems, Man, and Cybernetics, Vol.24, No.1, pp. 28-38, Jan. 1994.
-  S. W. Chan and J. H. Lilly, “Fuzzy PD+I Learning Control for a Pneumatic Muscle,” The 12th IEEE Int. Conf. on Fuzzy Systems, Vol.1, pp. 278-283, May 2003.
-  T. D. C. Thanh and K. K. Ahn, “Nonlinear PID control to improve the control performance of 2 axes pneumatic artificial muscle manipulator using neural network,” Mechatronics, Vol.16, No.9, pp. 577-587, 2006.
-  H. P. H. Anh and K. K. Ahn, “Hybrid control of a pneumatic artificial muscle (PAM) robot arm using an inverse NARX fuzzy model,” Engineering Applications of Artificial Intelligence, Vol.24, No.4, pp. 697-716, 2011.
-  K. Xing, Y. Wang, Q.Zhu, and H. Zhou, “Modeling and control of McKibben artificial muscle enhanced with echo state networks,” Control Engineering Practice, Vol.20, No.5, pp. 477-488, 2012.
-  D. G. Caldwell, G. A. Medrano-Cerda, and M. Goodwin, “Control of Pneumatic Muscle Actuators,” IEEE Control Systems, Vol.15, No.1, pp. 40-48, 1995.
-  J. H. Lilly, “Adaptive tracking for pneumatic muscle actuators in Bicep and Tricep configurations,” IEEE Trans. on Neural Systems and Rehabilitation Engineering, Vol.11, No.3, Sep. 2003.
-  X. Zhu, G. Tao, B. Yao, and J. Cao, “Integrated direct/indirect adaptive robust posture trajectory tracking control of a parallel manipulator driven by pneumatic muscles,” IEEE Trans. on Control Systems Technology, Vol.17, No.3, May 2009.
-  B. Tondu, K. Braikia, M. Chettouh, and S. Ippolito, “Second order sliding mode control for an anthropomorphic robot-arm driven with pneumatic artificial muscles,” 9th IEEE-RAS Int. Conf. on Humanoid Robots, pp. 47-54, Dec. 2009.
-  X. Shen, “Nonlinear model-based control of pneumatic artificial muscle servo systems,” Control Engineering Practice, Vol.18, No.3, pp. 311-317, 2010.
-  Y. Shtessel, M. Taleb, and F. Plestan, “A novel adaptive-gain supertwisting sliding mode controller: Methodology and application,” Automica, Vol.48, No.5, pp. 759-769, 2012.
-  M. Taleb, A. Levant, and F. Plestan, “Pneumatic actuator control: Solution based on adaptive twisting and experimentation,” Control Engineering Practice, Vol.21, No.5, pp. 727-736, 2013.
-  T. V. Minh, T. Tjahjowidodo, H. Ramon, and H. V. Brussel, “Control of a pneumatic artificial muscle (PAM) with model-based hysteresis compensation,” IEEE/ASME Int. Conf. on Advanced Intelligent Mechatronics, pp. 1082-1087, Jul. 2009.
-  T. J. Yeh, M. J. Wu, T. J. Lu, F. K. Wu, and C. R. Huang, “Control of McKibben pneumatic muscles for a power-assist, lower-limb orthosis,” Mechatronics, Vol.20, No.6, pp. 686-697, 2010.
-  T. V. Minh, B. Kamers, H. Ramon, and H. V. Brussel, “Modeling and control of a pneumatic artificial muscle manipulator joint - Part I: Modeling of a pneumatic artificial muscle manipulator joint with accounting for creep effect,” Mechatronics, Vol.22, No.7, pp. 923-933, 2012.
-  M. K. Chang, J. J. Liou, and M. L. Chen, “T-S fuzzy modelbased tracking control of a one-dimensional manipulator actuated by pneumatic artificial muscles,” Control Engineering Practice, Vol.19, No.12, pp. 1442-1449, 2011.
-  C. P. Chou and B. Hannaford, “Measurement and modeling of McKibben pneumatic artificial muscles,” IEEE Trans. on Robotics and Automation, Vol.12, No.1, pp. 90-102, Feb. 1996.
-  B. Tondu and P. Lopez, “Modeling and control of McKibben artificial muscle robot actuators,” IEEE Control Systems Magazine, Vol.20, No.2, pp. 15-38, 2000.
This article is published under a Creative Commons Attribution-NoDerivatives 4.0 International License.