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Artificial Chattering Free on-line Fuzzy Sliding Mode Algorithm for Uncertain System: Applied in Robot Manipulator
Farzin Piltan, N. Sulaiman, Samira Soltani, Samaneh Roosta, Atefeh Gavahian
Pages - 360 - 379     |    Revised - 01-11-2011     |    Published - 15-12-2011
Volume - 5   Issue - 5    |    Publication Date - November / December 2011  Table of Contents
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KEYWORDS
chattering phenomenon , , chattering free adaptive sliding mode fuzzy cont, nonliner controller part
ABSTRACT
In this research, an artificial chattering free adaptive fuzzy sliding mode control design and application to uncertain robotic manipulator has proposed in order to design high performance nonlinear controller in the presence of uncertainties. Regarding to the positive points in sliding mode controller, fuzzy logic controller and adaptive method, the output has improved. Each method by adding to the previous controller has covered negative points. The main target in this research is design of model free estimator on-line sliding mode fuzzy algorithm for robot manipulator to reach an acceptable performance. Robot manipulators are highly nonlinear, and a number of parameters are uncertain, therefore design model free controller using both analytical and empirical paradigms are the main goal. Although classical sliding mode methodology has acceptable performance with known dynamic parameters such as stability and robustness but there are two important disadvantages as below: chattering phenomenon and mathematical nonlinear dynamic equivalent controller part. To solve the chattering fuzzy logic inference applied instead of dead zone function. To solve the equivalent problems in classical sliding mode controller this paper focuses on applied fuzzy logic method in classical controller. This algorithm works very well in certain environment but in uncertain or various dynamic parameters, it has slight chattering phenomenon. The system performance in sliding mode controller and fuzzy sliding mode controller are sensitive to the sliding function. Therefore, compute the optimum value of sliding function for a system is the next challenge. This problem has solved by adjusting sliding function of the adaptive method continuously in real-time. In this way, the overall system performance has improved with respect to the classical sliding mode controller. This controller solved chattering phenomenon as well as mathematical nonlinear equivalent part by applied fuzzy supervisory method in sliding mode fuzzy controller and tuning the sliding function.
CITED BY (52)  
1 Tayyab, K., Malik, F. M., & Sheikh, S. A. (2015). SAMPLED DATA CONTROL OF BLDC MOTOR USING SMC AND FUZZY CONTROLLER AND COMPARING THEIR PERFORMANCE. Science International, 27(3).
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 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.
7 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.
8 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.
9 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.
10 Ebrahimi, M. M., Piltan, F., Bazregar, M., & Nabaee, A. (2013). Intelligent Robust Fuzzy-Parallel Optimization Control of a Continuum Robot Manipulator. International Journal of Control and Automation, 6(3), 15-34.
11 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.
12 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.
13 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.
14 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).
15 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.
16 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.
17 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.
18 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.
19 Jalali, A., Piltan, F., Hashemzadeh, M., BibakVaravi, F., & Hashemzadeh, H. (2013). Design Parallel Linear PD Compensation by Fuzzy Sliding Compensator for Continuum Robot. International Journal of Information Technology and Computer Science (IJITCS), 5(12), 97.
20 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.
21 Sadrnia, O. R., Piltan, F., Jafari, M., Eram, M., & Shamsodini, M. (2013). Design PID Estimator Fuzzy plus Backstepping to Control of Uncertain Continuum Robot. International Journal of Hybrid Information Technology, 6(4), 31-48.
22 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.
23 Jalali, A., Piltan, F., Hashemzadeh, H., Hasiri, A., & Hashemzadeh, M. (2013). Design Novel Soft Computing Backstepping Controller with Application to Nonlinear Dynamic Uncertain System. International Journal of Intelligent Systems and Applications (IJISA), 5(10), 93.
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 Zahmatkesh, S., Piltan, F., Heidari, K., Shamsodini, M., & Heidari, S. (2013). Artificial Error Tuning Based on Design a Novel SISO Fuzzy Backstepping Adaptive Variable Structure Control. International Journal of Intelligent Systems and Applications (IJISA), 5(11), 34.
26 Kazeminasab, M., Piltan, F., Esmaeili, Z., Mirshekaran, M., & Salehi, A. (2013). Design Parallel Fuzzy Partly Inverse Dynamic Method plus Gravity Control for Highly Nonlinear Continuum Robot. International Journal of Intelligent Systems and Applications (IJISA), 6(1), 112.
27 Heidari, S., Piltan, F., Shamsodini, M., Heidari, K., & Zahmatkesh, S. (2013). Design New Nonlinear Controller with Parallel Fuzzy Inference System Compensator to Control of Continuum Robot Manipulator. International Journal of Control and Automation, 6(4).
28 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.
29 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.
30 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.
31 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.
32 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.
33 Shamsodini, M., Manei, R., Bekter, A., Ranjbar, B., & Soltani, S. (2013). Design a New Fuzzy Optimize Robust Sliding Surface Gain in Nonlinear Controller. International Journal of Intelligent Systems and Applications (IJISA), 5(12), 91.
34 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.
35 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.
36 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.
37 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.
38 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.
39 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.
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., 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.
44 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.
45 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.
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., Rahmdel, S., Mehrara, S., & Bayat, R. (2012). Sliding mode methodology vs. Computed torque methodology using matlab/simulink and their integration into graduate nonlinear control courses. International Journal of Engineering, 6(3), 142-177.
48 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.
49 Piltan, F., Mehrara, S., Bayat, R., & Rahmdel, S. (2012). Design New Control Methodology of Industrial Robot Manipulator: Sliding Mode Baseline Methodology.
50 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.
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. Effect of Rule Base on the Fuzzy-Based Tuning Fuzzy Sliding Mode Controller: Applied to 2 nd Order Nonlinear System.
1 Google Scholar
2 CiteSeerX
3 refSeek
4 Scribd
5 SlideShare
6 PdfSR
1 T. R. Kurfess, Robotics and automation handbook: CRC, 2005.
2 J. J. E. Slotine and W. Li, Applied nonlinear control vol. 461: Prentice hall Englewood Cliffs, NJ,1991.
3 K. Ogata, Modern control engineering: Prentice Hall, 2009.
4 L. Cheng, et al., "Multi-agent based adaptive consensus control for multiple manipulators with kinematic uncertainties," 2008, pp. 189-194.
5 J. J. D'Azzo, et al., Linear control system analysis and design with MATLAB: CRC, 2003.
6 B. Siciliano and O. Khatib, Springer handbook of robotics: Springer-Verlag New York Inc, 2008.
7 I. Boiko, et al., "Analysis of chattering in systems with second-order sliding modes," IEEE Transactions on Automatic Control, vol. 52, pp. 2085-2102, 2007.
8 J. Wang, et al., "Indirect adaptive fuzzy sliding mode control: Part I: fuzzy switching," Fuzzy Sets and Systems, vol. 122, pp. 21-30, 2001.
9 C. Wu, "Robot accuracy analysis based on kinematics," IEEE Journal of Robotics and Automation,vol. 2, pp. 171-179, 1986.
10 H. Zhang and R. P. Paul, "A parallel solution to robot inverse kinematics," 2002, pp. 1140-1145.
11 J. Kieffer, "A path following algorithm for manipulator inverse kinematics," 2002, pp. 475-480.
12 Z. Ahmad and A. Guez, "On the solution to the inverse kinematic problem(of robot)," 1990, pp.1692-1697.
13 F. T. Cheng, et al., "Study and resolution of singularities for a 6-DOF PUMA manipulator,"Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on, vol. 27, pp. 332-343,2002.
14 M. W. Spong and M. Vidyasagar, Robot dynamics and control: Wiley-India, 2009.
15 A. Vivas and V. Mosquera, "Predictive functional control of a PUMA robot," 2005.
16 D. Nguyen-Tuong, et al., "Computed torque control with nonparametric regression models," 2008,pp. 212-217.
17 V. Utkin, "Variable structure systems with sliding modes," Automatic Control, IEEE Transactions on, vol. 22, pp. 212-222, 2002.
18 R. A. DeCarlo, et al., "Variable structure control of nonlinear multivariable systems: a tutorial,"Proceedings of the IEEE, vol. 76, pp. 212-232, 2002.
19 K. D. Young, et al., "A control engineer's guide to sliding mode control," 2002, pp. 1-14.
20 O. Kaynak, "Guest editorial special section on computationally intelligent methodologies and sliding-mode control," IEEE Transactions on Industrial Electronics, vol. 48, pp. 2-3, 2001.
21 J. J. Slotine and S. Sastry, "Tracking control of non-linear systems using sliding surfaces, with application to robot manipulators†," International Journal of Control, vol. 38, pp. 465-492, 1983.
22 J. J. E. Slotine, "Sliding controller design for non-linear systems," International Journal of Control,vol. 40, pp. 421-434, 1984.
23 R. Palm, "Sliding mode fuzzy control," 2002, pp. 519-526.
24 C. C. Weng and W. S. Yu, "Adaptive fuzzy sliding mode control for linear time-varying uncertain systems," 2008, pp. 1483-1490.
25 M. Ertugrul and O. Kaynak, "Neuro sliding mode control of robotic manipulators," Mechatronics,vol. 10, pp. 239-263, 2000.
26 P. Kachroo and M. Tomizuka, "Chattering reduction and error convergence in the sliding-mode control of a class of nonlinear systems," Automatic Control, IEEE Transactions on, vol. 41, pp.1063-1068, 2002.
27 H. Elmali and N. Olgac, "Implementation of sliding mode control with perturbation estimation(SMCPE)," Control Systems Technology, IEEE Transactions on, vol. 4, pp. 79-85, 2002.
28 J. Moura and N. Olgac, "A comparative study on simulations vs. experiments of SMCPE," 2002,pp. 996-1000.
29 Y. Li and Q. Xu, "Adaptive Sliding Mode Control With Perturbation Estimation and PID Sliding Surface for Motion Tracking of a Piezo-Driven Micromanipulator," Control Systems Technology,IEEE Transactions on, vol. 18, pp. 798-810, 2010.
30 B. Wu, et al., "An integral variable structure controller with fuzzy tuning design for electro-hydraulic driving Stewart platform," 2006, pp. 5-945.
31 L. A. Zadeh, "Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic," Fuzzy Sets and Systems, vol. 90, pp. 111-127, 1997.
32 L. Reznik, Fuzzy controllers: Butterworth-Heinemann, 1997.
33 J. Zhou and P. Coiffet, "Fuzzy control of robots," 2002, pp. 1357-1364.
34 S. Banerjee and P. Y. Woo, "Fuzzy logic control of robot manipulator," 2002, pp. 87-88.
35 K. Kumbla, et al., "Soft computing for autonomous robotic systems," Computers and Electrical Engineering, vol. 26, pp. 5-32, 2000.
36 C. C. Lee, "Fuzzy logic in control systems: fuzzy logic controller. I," IEEE Transactions on systems, man and cybernetics, vol. 20, pp. 404-418, 1990.
37 R. J. Wai, et al., "Implementation of artificial intelligent control in single-link flexible robot arm,"2003, pp. 1270-1275.
38 R. J. Wai and M. C. Lee, "Intelligent optimal control of single-link flexible robot arm," Industrial Electronics, IEEE Transactions on, vol. 51, pp. 201-220, 2004.
39 M. B. Menhaj and M. Rouhani, "A novel neuro-based model reference adaptive control for a two link robot arm," 2002, pp. 47-52.
40 S. Mohan and S. Bhanot, "Comparative study of some adaptive fuzzy algorithms for manipulator control," International Journal of Computational Intelligence, vol. 3, pp. 303–311, 2006.
41 F. Barrero, et al., "Speed control of induction motors using a novel fuzzy sliding-mode structure,"Fuzzy Systems, IEEE Transactions on, vol. 10, pp. 375-383, 2002.
42 Y. C. Hsu and H. A. Malki, "Fuzzy variable structure control for MIMO systems," 2002, pp. 280-285.
43 Y. C. Hsueh, et al., "Self-tuning sliding mode controller design for a class of nonlinear control systems," 2009, pp. 2337-2342.
44 R. Shahnazi, et al., "Position control of induction and DC servomotors: a novel adaptive fuzzy PI sliding mode control," Energy Conversion, IEEE Transactions on, vol. 23, pp. 138-147, 2008.
45 C. C. Chiang and C. H. Wu, "Observer-Based Adaptive Fuzzy Sliding Mode Control of Uncertain Multiple-Input Multiple-Output Nonlinear Systems," 2007, pp. 1-6.
46 H. Temeltas, "A fuzzy adaptation technique for sliding mode controllers," 2002, pp. 110-115.
47 C. L. Hwang and S. F. Chao, "A fuzzy-model-based variable structure control for robot arms:theory and experiments," 2005, pp. 5252-5258.
48 C. G. Lhee, et al., "Sliding mode-like fuzzy logic control with self-tuning the dead zone parameters," Fuzzy Systems, IEEE Transactions on, vol. 9, pp. 343-348, 2002.
49 "Sliding-Like Fuzzy Logic Control with Self-tuning the Dead Zone Parameters," 1999.
50 X. Zhang, et al., "Adaptive sliding mode-like fuzzy logic control for high order nonlinear systems,"pp. 788-792.
51 M. R. Emami, et al., "Development of a systematic methodology of fuzzy logic modeling," IEEE Transactions on Fuzzy Systems, vol. 6, 1998.
52 1994, vol. 4, pp. 212-218, 1994.
53 Z. Kovacic and S. Bogdan, Fuzzy controller design: theory and applications: CRC/Taylor & Francis, 2006.
54 F. Y. Hsu and L. C. Fu, "Nonlinear control of robot manipulators using adaptive fuzzy sliding mode control," 2002, pp. 156-161.
55 R. G. Berstecher, et al., "An adaptive fuzzy sliding-mode controller," Industrial Electronics, IEEE Transactions on, vol. 48, pp. 18-31, 2002.
56 V. Kim, "Independent joint adaptive fuzzy control of robot manipulator," 2002, pp. 645-652.
57 Y. Wang and T. Chai, "Robust adaptive fuzzy observer design in robot arms," 2005, pp. 857-862.
58 B. K. Yoo and W. C. Ham, "Adaptive control of robot manipulator using fuzzy compensator," Fuzzy Systems, IEEE Transactions on, vol. 8, pp. 186-199, 2002.
59 H. Medhaffar, et al., "A decoupled fuzzy indirect adaptive sliding mode controller with application to robot manipulator," International Journal of Modelling, Identification and Control, vol. 1, pp. 23-29, 2006.
60 Y. Guo and P. Y. Woo, "An adaptive fuzzy sliding mode controller for robotic manipulators,"Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on, vol. 33, pp.149-159, 2003.
61 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.
62 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
63 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.
64 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.
65 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.
66 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.
67 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.
68 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
Mr. Samira Soltani
- Iran
Mr. Samaneh Roosta
- Iran
Mr. Atefeh Gavahian
- India