Home   >   CSC-OpenAccess Library   >    Manuscript Information
Full Text Available

(411.55KB)
This is an Open Access publication published under CSC-OpenAccess Policy.
Publications from CSC-OpenAccess Library are being accessed from over 74 countries worldwide.
Design of Model Free Adaptive Fuzzy Computed Torque Controller for a Nonlinear Second Order System
Farzin Piltan, N. Sulaiman, Amin Jalali, Fereshteh Danesh Narouei
Pages - 232 - 244     |    Revised - 01-09-2011     |    Published - 05-10-2011
Volume - 2   Issue - 4    |    Publication Date - September / October 2011  Table of Contents
MORE INFORMATION
KEYWORDS
Adaptive Fuzzy Computed Torque Controller, Robot Manipulator, Classical Control, Non-classical Control, Computed Torque Controller
ABSTRACT
In this study, a model free adaptive fuzzy computed torque controller (AFCTC) is designed for a two-degree-of freedom robot manipulator to rich the best performance. Computed torque controller is studied because of its high performance. AFCTC has been also included in this study because of its robust character and high performance. Besides, this control method can be applied to non-linear systems easily. Today, robot manipulators are used in unknown and unstructured environment and caused to provide sophisticated systems, therefore strong mathematical tools are used in new control methodologies to design adaptive nonlinear robust controller with acceptable performance (e.g., minimum error, good trajectory, disturbance rejection). The strategies of control robot manipulator are classified into two main groups: classical and non-classical methods, however both classical and non-classical theories have been applied successfully in many applications, but they also have some limitation. One of the most important nonlinear robust controller that can used in uncertainty nonlinear systems, are computed torque controller. This paper is focuses on applied non-classical method in robust classical method to reduce the limitations. Therefore adaptive fuzzy computed torque controller will be presented in this paper.
CITED BY (59)  
1 Ajwad, S. A., Iqbal, J., Ullah, M. I., & Mehmood, A. (2015). A systematic review of current and emergent manipulator control approaches. Frontiers of Mechanical Engineering, 1-13.
2 Bazregar, M., Piltan, F., Nabaee, A., & Ebrahimi, M. (2014). Design Modified Fuzzy PD Gravity Controller with Application to Continuum Robot. International Journal of Information Technology and Computer Science (IJITCS), 6(3), 82.
3 Mozafari, N. G., Piltan, F., Shamsodini, M., Yazdanpanah, A., & Roshanzamir, A. (2014). On Line Tuning Premise and Consequence FIS Based on Lyaponuv Theory with Application to Continuum Robot. International Journal of Intelligent Systems and Applications (IJISA), 6(3), 96.
4 Nazari, I., Hosainpour, A., Piltan, F., Emamzadeh, S., & Mirzaie, M. (2014). Design Sliding Mode Controller with Parallel Fuzzy Inference System Compensator to Control of Robot Manipulator. International Journal of Intelligent Systems and Applications (IJISA), 6(4), 63.
5 Piran, M., Piltan, F., Akbari, M., Garg, R., & Bazregar, M. (2014). Quality Model and Artificial Intelligence Base Fuel Ratio Management with Applications to Automotive Engine. International Journal of Intelligent Systems and Applications (IJISA), 6(2), 76.
6 Ajwad, S., Ullah, M., Baizid, K., & Iqbal, J. (2014). A comprehensive state-of-the-art on control of industrial articulated robots. Journal of the Balkan Tribological Association, 20, 499-521.
7 Piltan, F., Bazregar, M., Piran, M., & Akbari, M. (2014). Quality Model and Artificial Intelligence Base Fuel Ratio Management with Applications to Automotive Engine. IAES International Journal of Artificial Intelligence (IJ-AI), 3(1), 36-48.
8 Piltan, F., Piran, M., Bazregar, M., & Akbari, M. (2013). Design High Impact Fuzzy Baseline Variable Structure Methodology to Artificial Adjust Fuel Ratio. International Journal of Intelligent Systems and Applications (IJISA), 5(2), 59.
9 Piltan, F., Yarmahmoudi, M., Mirzaie, M., Emamzadeh, S., & Hivand, Z. (2013). Design Novel Fuzzy Robust Feedback Linearization Control with Application to Robot Manipulator. International Journal of Intelligent Systems and Applications (IJISA), 5(5), 1.
10 Jalali, A., Piltan, F., Gavahian, A., & Jalali, M. (2013). Model-free adaptive fuzzy sliding mode controller optimized by particle swarm for robot manipulator. International Journal of Information Engineering and Electronic Business (IJIEEB), 5(1), 68.
11 Piltan, F., Nabaee, A., Ebrahimi, M., & Bazregar, M. (2013). Design robust fuzzy sliding mode control technique for robot manipulator systems with modeling uncertainties. International Journal of Information Technology and Computer Science (IJITCS), 5(8), 123.
12 Jalali, A., Piltan, F., Keshtgar, M., & Jalali, M. (2013). Colonial Competitive Optimization Sliding Mode Controller with Application to Robot Manipulator. International Journal of Intelligent Systems and Applications (IJISA), 5(7), 50.
13 Salehi, A., Piltan, F., Mousavi, M., Khajeh, A., & Rashidian, M. R. (2013). Intelligent Robust Feed-forward Fuzzy Feedback Linearization Estimation of PID Control with Application to Continuum Robot. International Journal of Information Engineering and Electronic Business (IJIEEB), 5(1), 1.
14 Piltan, F., Rafaati, M. J., Khazaeni, F., Hosainpour, A., & Soltani, S. (2013). A Design High Impact Lyapunov Fuzzy PD-Plus-Gravity Controller with Application to Rigid Manipulator. International Journal of Information Engineering and Electronic Business (IJIEEB), 5(1), 17.
15 Piltan, F., Eram, M., Taghavi, M., Sadrnia, O. R., & Jafari, M. (2013). Nonlinear Fuzzy Model-base Technique to Compensate Highly Nonlinear Continuum Robot Manipulator. International Journal of Intelligent Systems and Applications (IJISA), 5(12), 135.
16 Piltan, F., Bazregar, M., Akbari, M., & Piran, M. (2013). Adjust the fuel ratio by high impact chattering free sliding methodology with application to automotive engine. International Journal of Hybrid Information Technology, 6(1), 13-24.
17 Piltan, F., Mansoorzadeh, M., Zare, S., Shahryarzadeh, F., & Akbari, M. (2013). Artificial tune of fuel ratio: Design a novel siso fuzzy backstepping adaptive variable structure control. International Journal of Electrical and Computer Engineering (IJECE), 3(2), 171-185.
18 Jahed, A., Piltan, F., Rezaie, H., & Boroomand, B. (2013). Design Computed Torque Controller with Parallel Fuzzy Inference System Compensator to Control of Robot Manipulator. International Journal of Information Engineering & Electronic Business, 5(3).
19 Mirshekaran, M., Piltan, F., Esmaeili, Z., Khajeaian, T., & Kazeminasab, M. (2013). Design Sliding Mode Modified Fuzzy Linear Controller with Application to Flexible Robot Manipulator. International Journal of Modern Education and Computer Science (IJMECS), 5(10), 53.
20 Ebrahimi, M. M., Piltan, F., Bazregar, M., & Nabaee, A. (2013). Artificial Chattering Free on-line Modified Sliding Mode Algorithm: Applied in Continuum Robot Manipulator. International Journal of Information Engineering and Electronic Business (IJIEEB), 5(5), 57.
21 Piltan, F., Emamzadeh, S., Heidari, S., Zahmatkesh, S., & Heidari, K. (2013). Design Artificial Intelligent Parallel Feedback Linearization of PID Control with Application to Continuum Robot. International Journal of Engineering and Manufacturing, 3(2), 51-72.
22 Piltan, F., Hosainpour, A., Emamzadeh, S., Nazari, I., & Mirzaie, M. (2013). Design Sliding Mode Controller of with Parallel Fuzzy Inference System Compensator to Control of Robot Manipulator. IAES International Journal of Robotics and Automation (IJRA), 2(4), 149-162.
23 Moosavi, M., Eram, M., Khajeh, A., Mahmoudi, O., & Piltan, F. (2013). Design New Artificial Intelligence Base Modified PID Hybrid Controller for Highly Nonlinear System. International Journal of Advanced Science and Technology, 57.
24 Piltan, F., Jafari, M., Eram, M., Mahmoudi, O., & Sadrnia, O. R. (2013). Design Artificial Intelligence-Based Switching PD plus Gravity for Highly Nonlinear Second Order System. International Journal of Engineering and Manufacturing (IJEM), 3(1), 38.
25 Piltan, F., Zare, S., ShahryarZadeh, F., & Mansoorzadeh, M. (2013). Supervised Optimization of Fuel Ratio in IC Engine Based on Design Baseline Computed Fuel Methodology. International Journal of Information Technology and Computer Science (IJITCS), 5(4), 76.
26 Shamsodini, M., Piltan, F., Jafari, M., reza Sadrnia, O., & Mahmoudi, O. (2013). Design Modified Fuzzy Hybrid Technique: Tuning By GDO. International Journal of Modern Education and Computer Science (IJMECS), 5(8), 58.
27 Piltan, F., Bairami, M. A., Aghayari, F., & Rashidian, M. R. (2013). Stable Fuzzy PD Control with Parallel Sliding Mode Compensation with Application to Rigid Manipulator. International Journal of Information Technology and Computer Science (IJITCS), 5(7), 103.
28 Bazregar, M., Piltan, F., Akbari, M., & Piran, M. (2013). Management of Automotive Engine Based on Stable Fuzzy Technique with Parallel Sliding Mode Optimization. International Journal of Information Technology and Computer Science (IJITCS), 6(1), 101.
29 Imani, B., Ghanbari, A., & Noorani, S. M. R. S. (2013, February). Modeling, path planning and control of a planar five-link bipedal robot by an adaptive fuzzy computed torque controller (AFCTC). In Robotics and Mechatronics (ICRoM), 2013 First RSI/ISM International Conference on (pp. 49-54). IEEE.
30 Piltan, F., Mehrara, S., Meigolinedjad, J., & Bayat, R. (2013). Design Serial Fuzzy Variable Structure Compensator for Linear PD Controller: Applied to Rigid Robot. International Journal of Information Technology and Computer Science (IJITCS), 5(11), 111.
31 Piltan, F., Badri, A., Meigolinedjad, J., & Keshavarz, M. (2013). Adaptive Artificial Intelligence Based Model Base Controller: Applied to Surgical Endoscopy Telemanipulator. International Journal of Intelligent Systems and Applications (IJISA), 5(9), 103.
32 Piltan, F., Bazregar, M., Akbari, M., & Piran, M. (2013). Management of Automotive Engine Based on Stable Fuzzy Technique with Parallel Sliding Mode Optimization. International Journal of Advances in Applied Sciences, 2(4), 171-184.
33 Piltan, F., Yarmahmoudi, M. H., Shamsodini, M., Mazlomian, E., & Hosainpour, A. (2012). PUMA-560 Robot Manipulator Position Computed Torque Control Methods Using MATLAB/SIMULINK and Their Integration into Graduate Nonlinear Control and MATLAB Courses. International Journal of Robotics and Automation, (3), 167-191.
34 Piltan, F., Emamzadeh, S., Hivand, Z., Shahriyari, F., & Mirazaei, M. (2012). PUMA-560 Robot Manipulator Position Sliding Mode Control Methods Using MATLAB/SIMULINK and Their Integration into Graduate/Undergraduate Nonlinear Control, Robotics and MATLAB Courses. International Journal of Robotics and Automation, 3(3), 106-150.
35 Piltan, F., Hosainpour, A., Mazlomian, E., Shamsodini, M., & Yarmahmoudi, M. H. (2012). Online Tuning Chattering Free Sliding Mode Fuzzy Control Design: Lyapunov Approach. International Journal of Robotics and Automation, 3(3), 77-105.
36 Piltan, F., Nazari, I., Siamak, S., & Ferdosali, P. (2012). Methodology of FPGA-based mathematical error-based tuning sliding mode controller. International Journal of Control and Automation, 5(1), 89-118.
37 Piltan, F., Boroomand, B., Jahed, A., & Rezaie, H. (2012). Methodology of Mathematical Error-Based Tuning Sliding Mode Controller. International Journal of Engineering, 6(2), 96-117.
38 Piltan, F., Dialame, M., Zare, A., & Badri, A. (2012). Design Novel Lookup Table Changed Auto Tuning FSMC: Applied to Robot Manipulator. International Journal of Engineering, 6(1), 25-41.
39 Piltan, F., Keshavarz, M., Badri, A., & Zargari, A. (2012). Design Novel Nonlinear Controller Applied to RobotManipulator: Design New Feedback Linearization Fuzzy Controller with Minimum Rule Base Tuning Method. International Journal of Robotics and Automation, 3(1), 1-12.
40 Piltan, F., Mirzaei, M., Shahriari, F., Nazari, I., & Emamzadeh, S. (2012). Design Baseline Computed Torque Controller. International Journal of Engineering, 6(3), 129-141.
41 Piltan, F., Boroomand, B., Jahed, A., & Rezaie, H. (2012). Performance-Based Adaptive Gradient Descent Optimal Coefficient Fuzzy Sliding Mode Methodology. International Journal of Intelligent Systems and Applications (IJISA), 4(11), 40.
42 Piltan, F., Meigolinedjad, J., Mehrara, S., & Rahmdel, S. (2012). Evaluation Performance of 2nd Order Nonlinear System: Baseline Control Tunable Gain Sliding Mode Methodology. International Journal of Robotics and Automation, 3(3), 192-211.
43 Piltan, F., Aghayari, F., Rashidian, M. R., & Shamsodini, M. (2012). A New Estimate Sliding Mode Fuzzy Controller for Robotic Manipulator. International Journal of Robotics and Automation, 3(1), 45-58.
44 Piltan, F., Jahed, A., Rezaie, H., & Boroomand, B. (2012). Methodology of Robust Linear On-line High Speed Tuning for Stable Sliding Mode Controller: Applied to Nonlinear System. International Journal of Control and Automation, 5(3), 217-236.
45 Piltan, F., Akbari, M., Piran, M., & Bazregar, M. (2012). Design Model Free Switching Gain Scheduling Baseline Controller with Application to Automotive Engine. International Journal of Information Technology and Computer Science (IJITCS), 5(1), 65.
46 Piltan, F., Bayat, R., Aghayari, F., & Boroomand, B. (2012). Design Error-Based Linear Model-Free Evaluation Performance Computed Torque Controller. International Journal of Robotics and Automation, 3(3), 151-166.
47 Piltan, F., Siamak, S., Bairami, M. A., & Nazari, I. (2012). Gradient descent optimal chattering free sliding mode fuzzy control design: LYAPUNOV approach. International Journal of Advanced Science and Technology, 43, 73-90.
48 Piltan, F., Bayat, R., Mehara, S., & Meigolinedjad, J. (2012). GDO Artificial Intelligence-Based Switching PID Baseline Feedback Linearization Method: Controlled PUMA Workspace. International Journal of Information Engineering and Electronic Business (IJIEEB), 4(5), 17.
49 Piltan, F., & Haghighi, S. T. (2012). Design Gradient Descent Optimal Sliding Mode Control of Continuum Robots. IAES International Journal of Robotics and Automation (IJRA), 1(4), 175-189.
50 Piltan, F., Mehrara, S., Bayat, R., & Rahmdel, S. (2012). Design New Control Methodology of Industrial Robot Manipulator: Sliding Mode Baseline Methodology.
51 Piltan, F., Piran, M., Akbari, M., & Barzegar, M. (2012). Baseline Tuning Methodology Supervisory Sliding Mode Methodology: Applied to IC Engine. International Journal of Advances in Applied Sciences, 1(3), 116-124.
52 Seven Tir Ave, S. Design New Control Methodology of Industrial Robot Manipulator: Sliding Mode Baseline Methodology.
53 Seven Tir Ave, S. Effect of Rule Base on the Fuzzy-Based Tuning Fuzzy Sliding Mode Controller: Applied to 2 nd Order Nonlinear System.
54 Piltan, F., Sulaiman, N., Zargari, A., Keshavarz, M., & Badri, A. (2011). Design PID-Like Fuzzy Controller With Minimum Rule Base and Mathematical Proposed On-line Tunable Gain: Applied to Robot Manipulator. International Journal of Artificial intelligence and expert system, 2(4), 184-195.
55 Piltan, F., Sulaiman, N., Nasiri, H., Allahdadi, S., & Bairami, M. A. (2011). Novel Robot Manipulator Adaptive Artificial Control: Design a Novel SISO Adaptive Fuzzy Sliding Algorithm Inverse Dynamic Like Method. International Journal of Engineering, 5(5), 399-418.
56 Piltan, F., Bairami, M. A., Aghayari, F., & Allahdadi, S. (2011). Design adaptive artificial inverse dynamic controller: Design sliding mode fuzzy adaptive new inverse dynamic fuzzy controller. International Journal of Robotics and Automation (IJRA), 3(1), 13.
57 Piltan, F., Allahdadi, S., Mohammad, A. B., & Nasiri, H. (2011). Design Auto Adjust Sliding Surface Slope: Applied to Robot Manipulator. International Journal of Robotics and Automation, 3(1), 27-44.
58 TAHIR, D. N. International journal of artificial intelligence and expert systems (IJAE).
59 Orozco-Soto, S. M., & Ramos-Fernández, J. C. Control par calculado difuso basado en pasividad para seguimiento de trayectorias de robots manipuladores.
1 Google Scholar 
2 CiteSeerX 
3 refSeek 
4 Scribd 
5 SlideShare 
6 PdfSR 
1 Thomas R. Kurfess, Robotics and Automation Handbook: CRC press, 2005.
2 Bruno Siciliano and Oussama Khatib, Handbook of Robotics: Springer, 2007.
3 Slotine J. J. E., and W. Li., Applied nonlinear control: Prentice-Hall Inc, 1991. [
4 Boiko I, L. Fridman, A. Pisano, and E. Usai, “Analysis of chattering in systems with second-order sliding modes”, IEEE transactions on Automatic control, 52(11): 2085-2102, 2007.
5 L.X.Wang, “stable adaptive fuzzy control of nonlinear systems”, IEEE transactions on fuzzy systems, 1(2): 146-154, 1993.
6 Frank L.Lewis, Robot dynamics and control, in robot Handbook: CRC press, 1999.
7 A.Vivas, V.Mosquera, “predictive functional control of puma robot”, ACSE05 conference, 2005.
8 D.Tuong, M.Seeger, J.peters,” Computed torque control with nonparametric regressions models”, American control conference, pp: 212-217, 2008.
9 Farzin Piltan, A. R. Salehi and Nasri B Sulaiman.,” Design artificial robust control of second order system based on adaptive fuzzy gain scheduling,” world applied science journal (WASJ), 13 (5): 1085-1092, 2011.
10 Lotfi A. Zadeh” Toward a theory of fuzzy information granulation and its centrality in human easoning and fuzzy logic” Fuzzy Sets and Systems 90 (1997) 111-127
11 Reznik L., Fuzzy Controllers, First edition: BH NewNes, 1997.
12 Zhou, J., Coiffet, P,” Fuzzy Control of Robots,” Proceedings IEEE International Conference on Fuzzy Systems, pp: 1357 – 1364, 1992.
13 Banerjee, S., Peng Yung Woo, “Fuzzy logic control of robot manipulator,” Proceedings Second IEEE Conference on Control Applications, pp: 87 – 88, 1993.
14 Akbarzadeh-T A. R., K.Kumbla, E. Tunstel, M. Jamshidi. ,”Soft Computing for autonomous Robotic Systems,” IEEE International Conference on Systems, Man and Cybernatics, pp: 5252- 5258, 2000.
15 Lee C.C.,” Fuzzy logic in control systems: Fuzzy logic controller-Part 1,” IEEE International Conference on Systems, Man and Cybernetics, 20(2), P.P: 404-418, 1990.
16 F. Piltan, et al., "Artificial Control of Nonlinear Second Order Systems Based on AFGSMC," Australian Journal of Basic and Applied Sciences, 5(6), pp. 509-522, 2011.
17 Piltan, F., et al., “Design sliding mode controller for robot manipulator with artificial tunable gain,” Canaidian Journal of pure and applied science, 5 (2): 1573-1579, 2011.
18 Piltan, F., et al., “Design Artificial Nonlinear Robust Controller Based on CTLC and FSMC with Tunable Gain,” International Journal of Robotic and Automation, 2 (3): 205-220, 2011.
19 Piltan, F., et al., “Design Mathematical Tunable Gain PID-Like Sliding Mode Fuzzy Controller with Minimum Rule Base,” International Journal of Robotic and Automation, 2 (3): 146-156, 2011.
20 Piltan, F., et al., “Design of FPGA based sliding mode controller for robot manipulator,” International Journal of Robotic and Automation, 2 (3): 183-204, 2011.
21 Piltan, F., et al., “A Model Free Robust Sliding Surface Slope Adjustment in Sliding Mode Control for Robot Manipulator,” World Applied Science Journal, 12 (12): 2330-2336, 2011.
22 Piltan, F., et al., “Design Adaptive Fuzzy Robust Controllers for Robot Manipulator,” World Applied Science Journal, 12 (12): 2317-2329, 2011.
Mr. Farzin Piltan
UPM - Malaysia
SSP.ROBOTIC@yahoo.com
Mr. N. Sulaiman
- Malaysia
Amin Jalali
- Iran
Dr. Fereshteh Danesh Narouei
- Iran