MODIFIED-PID CONTROL WITH FEEDFORWARD IMPROVEMENT FOR 1-DEGREE-OF-FREEDOM PNEUMATIC MUSCLE ACTUATED SYSTEM
DOI:
https://doi.org/10.11113/jt.v79.11283Keywords:
Pneumatic muscle actuator, linearizer, modified-PID control, feedforward, point-to-pointAbstract
attention due to the favorable advantages that PMA has to offer such as inherent compliant safety, compactness, dust-resistant and powerful, especially for rehabilitation application. However, the highly non-linear phenomenon exhibited by PMA poses a challenge in positioning control of the mechanism. Due to the highly nonlinear properties of the PMA system, it is difficult and challengeable to model the system accurately. Many advanced controls have been proposed, however, majority of them requires accurate model parameters for the design and/ or deep understanding of control theory. Therefore, this research aims to highlight a practical and simple control framework capable of providing ameliorated compensation towards the non-linearities in a PMA positioning system. The proposed controller is a combination of a modified PID control incorporated with a model-based feed-forward element. The modified PID control is cascaded with a modeled-nonlinear function and a linearizer that works to compensate the influence of the nonlinearities. The design procedure of the proposed control remains simple and none of the known parameter is required. The proposed controller is verified experimentally using the constructed testbed – 1DOF PMA system; in point-to-point motion that driving in several step heights (5 mm, 10 mm, 20 mm, and 30 mm). At the step height of 30 mm, the proposed control has demonstrated three times smaller of overshoot and the reduction of 39% of settling time as compared with the conventional PID control. Overall, the experimental results show that the proposed controller is capable of demonstrating a satisfactory transient, with better overshoot reduction characteristic and faster settling time; and robust performance under default and in the presence of the change of load, in comparison with the conventional PID control.Â
References
Redlarski, G., Blecharz, K., DÄ…bkowski, M., Palkowski, A. and Tojza, P.M. 2012. Comparative Analysis of Exoskeletal Actuators. Pomiary Autom. Robot. 16(12): 133-138.
Repperger, D. W., Phillips, C. A., Neidhard-doll, A., Reynolds, D. B., and Berlin, J. 2006. Actuator Design Using Biomimicry Methods and A Pneumatic Muscle System. Control Eng. Pract. 14: 999-1009.
Repperger, D. W., Phillips, C. A., Neidhard-Doll, A., Reynolds, D. B., and Berlin, J. 2005. Power/Energy Metrics for Controller Evaluation of Actuators Similar to Biological Systems. Mechatronics. 15(4): 459-469.
Tsagarakis, N., and Caldwell, D. G. 2003. Development and Control of a ‘Soft-Actuated’ Exoskeleton for Use in Physiotherapy and Training. Auton. Robots. 15(1): 21-33.
Yeh, T., Wu, M., Lu, T., Wu, F., and Huang, C. 2010. Control of McKibben Pneumatic Muscles for a Power-Assist, Lower-Limb Orthosis. Mechatronics. 20(6): 686-697.
Balasubramanian, S., Ward, J., Sugar, T., and He, J. 2007. Characterization of The Dynamic Properties of Pneumatic Muscle Actuators. IEEE 10th Int. Conf. Rehabil. Robotics (ICORR). Nertherlands. 13-15 June 2007. 764-770.
T. V. Minh, B. Kamers, H. Ramon, and H. Van Brussel. 2012. Mechatronics 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. 22(7): 923-933.
D. G. Caldwell, G. a. Medrano-Cerda, and M. Goodwin. 1995. Control of Pneumatic Muscle Actuators. IEEE Control Systems Magazine. 15(1): 40-48.
M. Iskarous and K. Kawamura. 1995. Intelligent Control Using a Neuro-Fuzzy Network. Intelligent Robots and Systems 95.’Human Robot Interaction and Cooperative Robots’, IEEE/RSJ International Conference. Pennsylvania, USA. 5-9 August 1995. 350-355.
P. Carbonell, Z. P. Jiang, and D. W. Repperger. 2001. A Fuzzy Backstepping Controller for A Pneumatic Muscle Actuator System. The IEEE International Symposium on Intelligent Control (ISIC ’01). Mexico. 5-7 September 2001. 353-358.
K. Balasubramanian and K. Rattan. 2003. Fuzzy Logic Control of A Pneumatic Muscle System Using a Linearing Control Scheme. The 22nd International Conference of the North American Fuzzy Information Processing Society (NAFIPS), Chicago, USA. 24-26 July 2003. 432-436.
K. Ahn and T. Thanh. 2004. Improvement of The Control Performance of Pneumatic Artificial Muscle Manipulators Using an Intelligent Switching Control Method. KSME Int. J. 18(8): 1388-1400.
Lilly, J. and Yang. L. 2005. Sliding Mode Tracking for Pneumatic Muscle Actuators in Opposing Pair Configuration. Control System Technology. 13(4): 550-558.
J. Sárosi, S. Csikós, I. Asztalos, J. Gyeviki, and A. Véha. 2011. Accurate Positioning of Spring Returned Pneumatic Artificial Muscle Using Sliding-mode Control. 1st REgional Conference- Mechatronics in Practice and Education (MECH-CONF). Subotica, Serbia. 8 December 2011. 350-356.
X. Zhu, G. Tao, B. Yao, and J. Cao. 2008. Adaptive Robust Posture Control of Parallel Manipulator Driven by Pneumatic Muscles With Redundancy. IEEE/ASME Trans. Mechatronics. 13(4): 441-450.
D. Schindele and H. Aschemann. 2008. Nonlinear Model Predictive Control of a High-Speed Linear Axis Driven by Pneumatic Muscles. American Control Conference (ACC), 2008. Seatle, Washington, USA. 11-13 June 2008. 3017-3022.
M. K. Chang, J. J. Liou, and M. L. Chen. 2011. T-S Fuzzy Model-Based Tracking Control of A One-Dimensional Manipulator Actuated by Pneumatic Artificial Muscles. Control Eng. Pract. 19(12): 1442-1449.
A. Hosovsky, J. Novak-Marcincin, J. Pitel, J. Borzikova, and K. Zidek. 2012. Model-Based Evolution of A Fast Hybrid Fuzzy Adaptive Controller for a Pneumatic Muscle Actuator. International Journal of Advanced Robotic System. 9(40): 1-11.
G. L. Shi and W. Shen. 2013. Hybrid Control of A Parallel Platform Based on Pneumatic Artificial Muscles Combining Sliding Mode Controller and Adaptive Fuzzy CMAC. Control Engineering Practice. 21(1): 76-86.
A. Hošovský, P. Michal, M. Tóthová, and O. Biroš. 2014. Fuzzy Adaptive Control for Pneumatic Muscle Actuator with Simulated Annealing Tuning. IEEE 12th Symposium on Applied Machine Intelligence and Informatics (SAMI). Herl'any, Slovakia. 23-25 January 2014. 205-209.
H. Pham, H. Anh, and K. K. Ahn. 2011. Hybrid Control of A Pneumatic Artificial Muscle (PAM) Robot Arm Using an Inverse NARX Fuzzy Model. Engineering Application of Artificial Intelligence. 24(4): 697-716.
T. D. C. Thanh and K. K. Ahn. 2006. Nonlinear PID Control to Improve The Control Performance of 2 Axes Pneumatic Artificial Muscle Manipulator using Neural Network. Mechatronics. 16(9): 577-587.
H. Anh and N. Nam. 2011. A New Approach of the Online Tuning Gain Scheduling Nonlinear PID Controller Using Neural Network. PID Control, Implementation and Tuning. InTech.
E. Kelasidi, G. Andrikopoulos, G. Nikolakopoulos, and S. Manesis. 2011. A Survey on Pneumatic Muscle Actuators Modeling. The 20th IEEE Int. Symp. Industrial Electronics (ISIE). Gdansk, Poland. 27-30 June 2011. 1263-1269.
D. B. Reynolds, D. W. Repperger, C. A. Phillips, and G. Bandry. 2003. Modeling The Dynamic Dharacteristics of Pneumatic Muscle. Ann. Biomed. Eng. 31(3): 310-317.
J. L. Serres, D. B. Reynolds, C. a Phillips, M. J. Gerschutz, and D. W. Repperger. 2009. Characterisation of A Phenomenological Model for Commercial Pneumatic Muscle Actuators. Computer Methods Biomech. Biomed. Engineering. 12(4): 423-30.
V. Sakthivelu, S. Chong, M. H. Tan, and M. Ghazaly. 2016. Phenomenological Modeling and Classic Control of A Pneumatic Muscle Actuator System. International Journal of Control Automation. 9(4): 301-312.
Downloads
Published
Issue
Section
License
Copyright of articles that appear in Jurnal Teknologi belongs exclusively to Penerbit Universiti Teknologi Malaysia (Penerbit UTM Press). This copyright covers the rights to reproduce the article, including reprints, electronic reproductions, or any other reproductions of similar nature.