CONTROL OF A SINGLE LINK ROBOT ARM ACTUATED BY PNEUMATIC ARTIFICIAL MUSCLES EMPLOYING ACTIVE FORCE CONTROL AND FUZZY LOGIC VIA HARDWARE-IN-THE-LOOP-SIMULATION

Authors

  • A. Enzevaee A. Enzevaee Department of Applied Mechanics and Design Faculty of Mechanical Engineering Universiti Teknologi Malaysia 81310 UTM Johor Bahru, Johor, Malaysia
  • M. Mailah M. Mailah Department of Applied Mechanics and Design Faculty of Mechanical Engineering Universiti Teknologi Malaysia 81310 UTM Johor Bahru, Johor, Malaysia
  • S. Kazi S. Kazi Department of Applied Mechanics and Design Faculty of Mechanical Engineering Universiti Teknologi Malaysia 81310 UTM Johor Bahru, Malaysia

Keywords:

Pneumatic artificial muscle, single link robot arm, active force control, fuzzy logic, hardware-in-the-loop simulation

Abstract

Among the many types of actuation for robotic systems, Pneumatic Artificial Muscle (PAM) is one of the most credible and efficient classes providing high tension forces, high power density, rapid response and high power-to-weight ratio, as well as features like cleanliness and low cost. However, drawbacks such as high level of nonlinearity and time varying characteristics make this class of actuators difficult to control. In this paper, an intelligent Active Force Control(AFC) of a single-link PAM actuated robot arm employing Fuzzy Logic(FL) element has been applied and tested through simulation as well as experimental studies. The robot arm is desired to move along a one radian (about 60 degrees) circular trajectory as a joint angle tracking control in the wake of the introduced disturbances. To demonstrate the robot arm more industrially practical, a radial gripper has been physically developed and attached to the robot arm. The experiment was conducted using Hardware-in-the-Loop-Simulation (HILS) strategy, taking into account variations in the payload masses. The results clearly show the capability of the proposed controller to handle and eliminate the disturbances in the system effectively and robustly.

References

Klute, G.K., Czerniecki, J.M., and Hannaford,B.,1999. McKibben artificial muscles: pneumatic actuators with biomechanical intelligence. Proceedings of IEEE/ASME International Conference on Advanced Intelligent Mechatronics.

Zhu, X.C., et al., 2008.Adaptive robust posture control of a parallel manipulator driven by pneumatic muscles.Automatica, 44(9), 2248-2257.

Tondu, B. and Lopez,P. 2000. Modeling and control of McKibben artificial muscle robot actuators.Control Systems, IEEE,. 20(2),15-38.

Chou, C.P. and Hannaford, B., 1996. Measurement and Modeling of McKibbenPneumatic Artificial Muscles, IEEE Transactions on Robotics and Automation, 12(1), 90-102.

Repperger, D.W., Johnso, K.R. n, and Philips, C.A.,1999.Nonlinear feedback controller design of a pneumatic muscle actuator system. Proceedings of the American Control Conference, 1999. 1999.

Repperger, D.W., et al., 2005. Power/energy metrics for controller evaluation of actuators similar to biological systems.Mechatronics, 15(4), 459-469.

Thanh, T.U.D.C. and Ahn,K.K., Nonlinear PID control to improve the control performance of 2 axes pneumatic artificial muscle manipulator using neural network.Mechatronics, 2006. 16(9), 577-587.

Ahn, K. and Anh,H., 2008. Comparative study of modeling and identification of the pneumatic artificial muscle (PAM) manipulator using recurrent neural networks.Journal of Mechanical Science and Technology,22(7), 1287-1298.

Chan, S.W., et al. 2003. Fuzzy PD+I learning control for a pneumatic muscle. FUZZ '03. The 12thIEEE International Conference onFuzzy Systems.

Lilly, J.H., 2003. Adaptive tracking for pneumatic muscle actuators in bicep and tricep configurations.IEEE Transactions onNeural Systems and Rehabilitation Engineering,. 11(3), 333-339.

Lilly, J.H. and Liang,Y., 2005. Sliding mode tracking for pneumatic muscle actuators in opposing pair configuration.IEEE Transactions onControl Systems Technology, 2005. 13(4), 550-558.

Lilly, J.H. and Quesada,P.M., 2004. A two-input sliding-mode controller for a planararm actuated by four pneumatic muscle groups.IEEE Transactions onNeural Systems and Rehabilitation Engineering, 12(3), 349-359.

Hewit, J.R. and Bouazza-Marouf,K., 1996. Practical control enhancement via mechatronics design.IEEE Transactions onIndustrial Electronics,43(1),16-22.

Hewit, J.R. and J.S. 1981. Burdess, Fast dynamic decoupled control for robotics, using active force control.Mechanism and Machine Theory, 16(5),535-542.

Jahanabadi, H., Mailah, M., and Zain, M.Z.M.,2009. Active Force Control of a fluidic muscle system using Fuzzy Logic. IEEE/ASME International Conference onAdvanced Intelligent Mechatronics, AIM

Jahanabadi, H., Mailah, M., and Zain, M.Z.M,2009.Control of a fluidic muscle system using Neuro Active Force Control. IEEE Symposium onComputational Intelligence in Control and Automation, 2009. CICA

Jahanabadi, H., et al., 2011. Active Force with Fuzzy Logic Control of a Two-Link Arm Driven by Pneumatic Artificial Muscles.Journal of Bionic Engineering, 8(4),474-484.

Mailah, M., Control of a robot arm using iterative learning algorithm with a stopping criterion, ed. J.W.S. Chong.

Mailah, M., 1998. Intelligent active force control of a rigid robot arm using neural network and iterative learning algorithms. PhD thesis,University of Dundee.

Mailah, M., et al., 2009.Modelling and control of a human-like arm incorporating muscle models.Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 223(7), 1569-1577.

Mailah, M. and Rahim, N.I.A.. 2000.Intelligent active force control of a robot arm using fuzzy logic. in TENCON. Proceedings.

Klute, G.K., 1999. Artificial Muscles: Actuators for Biorobotic Systems.: University of Washington.

Klute, G.K., Czerniecki,J.M., and Hannaford, B.,2000. Artificial tendons: biomechanical design properties for prosthetic lower limbs. Proceedings of the 22ndAnnual International Conference of the IEEEin Engineering in Medicine and Biology Society,.

Xiaocong, Z., et al., 2008. Adaptive Robust Posture Control of Parallel Manipulator Driven by Pneumatic Muscles With Redundancy,IEEE/ASME Transactions on Mechatronics, 13(4),441-450.

Reynolds, D.B., et al., 2003. Modeling the Dynamic Characteristics of Pneumatic Muscle, Annals of Biomedical Engineering, 31(3), 310-317.

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Published

2018-04-01

How to Cite

A. Enzevaee, A. E., M. Mailah, M. M., & S. Kazi, S. K. (2018). CONTROL OF A SINGLE LINK ROBOT ARM ACTUATED BY PNEUMATIC ARTIFICIAL MUSCLES EMPLOYING ACTIVE FORCE CONTROL AND FUZZY LOGIC VIA HARDWARE-IN-THE-LOOP-SIMULATION. Jurnal Mekanikal, 36(2). Retrieved from https://jurnalmekanikal.utm.my/index.php/jurnalmekanikal/article/view/57

Issue

Section

Mechanical

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