A Precise Robust Fuzzy Control of Robots Using Voltage Control Strategy

Mohammad Mehdi Fateh; Sara Fateh

doi:10.1007/s11633-013-0697-x

A Precise Robust Fuzzy Control of Robots Using Voltage Control Strategy

doi: 10.1007/s11633-013-0697-x

1.
Department of Electrical and Robotic Engineering, Shahrood University of Technology, Shahrood 3619995161, Iran

A Precise Robust Fuzzy Control of Robots Using Voltage Control Strategy

1.
Department of Electrical and Robotic Engineering, Shahrood University of Technology, Shahrood 3619995161, Iran

More Information

Author Bio:
Sara Fateh received her B. Sc. degree in robotic engineering from Shahrood Univer-sity of Technology, Iran in 2010. She re-ceived her M. Sc. degree in control engineer-ing at Shahrood University of Technology, Iran in 2012. Her thesis titled as "adaptive fuzzy control of robot manipulators using voltage control strategy" was supervised by Professor Mohammad Mehdi Fateh. Her research interests include modeling and control of robotic systems, nonlinear and fuzzy control. E-mail: ms.s.fateh@gmail.com

Corresponding author: Mohammad Mehdi Fateh

摘要: Fuzzy control of robot manipulators with a decentralized structure is facing a serious challenge. The state-space model of a robotic system including the robot manipulator and motors is in non-companion form, multivariable, highly nonlinear, and heavily coupled with a variable input gain matrix. Considering the problem, causes and solutions, we use voltage control strategy and convergence analysis to design a novel precise robust fuzzy control (PRFC) approach for electrically driven robot manipulators. The proposed fuzzy controller is Mamdani type and has a decentralized structure with guaranteed stability. In order to obtain a precise response, we regulate a fuzzy rule which governs the origin of the tracking space. The proposed design is verified by stability analysis. Simulations illustrate the superiority of the PRFC over a proprotional derivative like (PD-like) fuzzy controller applied on a selective compliant assembly robot arm (SCARA) driven by permanent magnet DC motors.
- Precise performance /
- fuzzy control /
- robot manipulator /
- voltage control strategy /
- convergence analysis /
- stability analysis
Abstract: Fuzzy control of robot manipulators with a decentralized structure is facing a serious challenge. The state-space model of a robotic system including the robot manipulator and motors is in non-companion form, multivariable, highly nonlinear, and heavily coupled with a variable input gain matrix. Considering the problem, causes and solutions, we use voltage control strategy and convergence analysis to design a novel precise robust fuzzy control (PRFC) approach for electrically driven robot manipulators. The proposed fuzzy controller is Mamdani type and has a decentralized structure with guaranteed stability. In order to obtain a precise response, we regulate a fuzzy rule which governs the origin of the tracking space. The proposed design is verified by stability analysis. Simulations illustrate the superiority of the PRFC over a proprotional derivative like (PD-like) fuzzy controller applied on a selective compliant assembly robot arm (SCARA) driven by permanent magnet DC motors.
- Precise performance /
- fuzzy control /
- robot manipulator /
- voltage control strategy /
- convergence analysis /
- stability analysis

[1]	Y. Shen.[J].W. J. Cai, S. Li. Multivariable processcontrol: decentralized, decoupling, or sparse.Industrial & Engineering Chemistry Research,vol. 49, no. 2, pp. 761-77.2010,:-
[2]	S. H. Hsua, L. C. Fua. A fully adaptivedecentralized control of robot manipulators.Automatica, vol. 42, no. 10, pp. 1761-1767,2006.
[3]	B. K. Yoo.[J].W. C. Ham. Adaptive control of robotmanipulator using fuzzy compensator. IEEETransactions on Fuzzy Systems, vol 8, no. 2, pp.186-19.2000,:-
[4]	K. C. Chiou.[J].S. J. Huang. An adaptive fuzzycontroller for robot manipulators. Mechatronics,vol. 15, no. 2, pp. 151-17.2005,:-
[5]	E. Kim. Output feedback tracking control of robotmanipulator with model uncertainty via adaptivefuzzy logic. IEEE Transactions on Fuzzy Systems.[J].vol. 12, no. 3, pp. 368-37.2004,:-
[6]	R. J. Wai.[J].P. C. Chen. Intelligent tracking controlfor robot manipulator including actuatordynamics via TSK-type fuzzy neural network,IEEE Transactions on Fuzzy Systems, vol. 12,no. 4, pp. 552-56.2004,:-
[7]	L. Cheng.[J].Z.-G. Hou, and M. Tan, Adaptiveneural network tracking control for manipulatorswith uncertain kinematics, dynamics and actuatormodel, Automatica, vol. 45, no. 10, pp. 2312-231.2009,:-
[8]	Z.-G. Hou, A.-M. Zou, L. Cheng, M. Tan,“Adaptive control of an electrically drivennonholonomic mobile robot via backstepping andfuzzy approach”, IEEE Transactions on ControlSystems Technology, vol. 17, no. 4, pp. 803-815,2009.
[9]	M.M. Fateh.[J].On the voltage-based control ofrobot manipulators, International Journal ofControl, Automation, and Systems, vol. 6, no. 5,pp. 702-71.2008,:-
[10]	M.M. Fateh.[J].Nonlinear control of electricalflexible-joint robots, Nonlinear Dynamics, vol.67, no. 4, pp. 2549-255.2012,:-
[11]	M. W. Spong.[J].S. Hutchinson, M. Vidyasagar.Robot modelling and control. John Wiley & Sons,Hoboken, NJ.2006,:-
[12]	L. X. Wang. A course in fuzzy systems andcontrol.[J].Prentice Hall, Englewood Cliffs.1996,:-

[1]	Mohammad Al-Fetyani, Mohammad Hayajneh, Adham Alsharkawi. Design of an Executable ANFIS-based Control System to Improve the Attitude and Altitude Performances of a Quadcopter Drone . International Journal of Automation and Computing, 2021, 18(1): 124-140. doi: 10.1007/s11633-020-1251-2
[2]	Satyam Paul, Ajay Arunachalam, Davood Khodadad, Henrik Andreasson, Olena Rubanenko. Fuzzy tuned PID controller for envisioned agricultural manipulator . International Journal of Automation and Computing, 2021, (): 1-13. doi: 10.1007/s11633-021-1280-5
[3]	Atlas Khan, Yan-Peng Qu, Zheng-Xue Li. Convergence Analysis of a New MaxMin-SOMO Algorithm . International Journal of Automation and Computing, 2019, 16(4): 534-542. doi: 10.1007/s11633-016-0996-0
[4]	Hanane Zermane, Hayet Mouss. Development of an Internet and Fuzzy Based Control System of Manufacturing Process . International Journal of Automation and Computing, 2017, 14(6): 706-718. doi: 10.1007/s11633-016-1027-x
[5]	Mourad Elloumi, Samira Kamoun. Parametric Estimation of Interconnected Nonlinear Systems Described by Input-output Mathematical Models . International Journal of Automation and Computing, 2016, 13(4): 364-381. doi: 10.1007/s11633-016-0956-8
[6]	Mohamadreza Homayounzade, Mehdi Keshmiri, Mostafa Ghobadi. A Robust Tracking Controller for Electrically Driven Robot Manipulators: Stability Analysis and Experiment . International Journal of Automation and Computing, 2015, 12(1): 83-92. doi: 10.1007/s11633-014-0850-1
[7]	Imen Manaa, Nabil Barhoumi, Faouzi Msahli. Global Stability Analysis of Switched Nonlinear Observers . International Journal of Automation and Computing, 2015, 12(4): 432-439. doi: 10.1007/s11633-014-0855-9
[8]	Xi-Sheng Dai, Sen-Ping Tian, Ya-Jun Guo. Iterative Learning Control for Discrete Parabolic Distributed Parameter Systems . International Journal of Automation and Computing, 2015, 12(3): 316-322. doi: 10.1007/s11633-015-0892-z
[9]	Fu-Cai Liu, Li-Huan Liang, Juan-Juan Gao. Fuzzy PID Control of Space Manipulator for Both Ground Alignment and Space Applications . International Journal of Automation and Computing, 2014, 11(4): 353-360. doi: 10.1007/s11633-014-0800-y
[10]	Lal Bahadur Prasad, Barjeev Tyagi, Hari Om Gupta. Optimal Control of Nonlinear Inverted Pendulum System Using PID Controller and LQR: Performance Analysis Without and With Disturbance Input . International Journal of Automation and Computing, 2014, 11(6): 661-670. doi: 10.1007/s11633-014-0818-1
[11]	Zhi-Qiang Pu, Ru-Yi Yuan, Xiang-Min Tan, Jian-Qiang Yi. An Integrated Approach to Hypersonic Entry Attitude Control . International Journal of Automation and Computing, 2014, 11(1): 39-50. doi: 10.1007/s11633-014-0764-y
[12]	. State Observer Based Dynamic Fuzzy Logic System for a Class of SISO Nonlinear Systems . International Journal of Automation and Computing, 2013, 10(2): 118-124. doi: 10.1007/s11633-013-0704-2
[13]	Vineet Kumar, A. P. Mittal, R. Singh. Stability Analysis of Parallel Fuzzy P + Fuzzy I + Fuzzy D Control Systems . International Journal of Automation and Computing, 2013, 10(2): 91-98. doi: 10.1007/s11633-013-0701-5
[14]	Majid Moradi Zirkohi, Mohammad Mehdi Fateh, Mahdi Aliyari Shoorehdeli. Type-2 Fuzzy Control for a Flexible-joint Robot Using Voltage Control Strategy . International Journal of Automation and Computing, 2013, 10(3): 242-255. doi: 10.1007/s11633-013-0717-x
[15]	Qing Zhu, Ai-Guo Song, Tian-Ping Zhang, Yue-Quan Yang. Fuzzy Adaptive Control of Delayed High Order Nonlinear Systems . International Journal of Automation and Computing, 2012, 9(2): 191-199. doi: 10.1007/s11633-012-0633-5
[16]	. Indirect Adaptive Fuzzy and Impulsive Control of Nonlinear Systems . International Journal of Automation and Computing, 2010, 7(4): 484-491. doi: 10.1007/s11633-010-0531-7
[17]	Shao-Cheng Tong, Ning Sheng. Adaptive Fuzzy Observer Backstepping Control for a Class of Uncertain Nonlinear Systems with Unknown Time-delay . International Journal of Automation and Computing, 2010, 7(2): 236-246. doi: 10.1007/s11633-010-0236-y
[18]	Xin Li, Xue-Ping Zhao, Jie Chen. Controller Design for Electric Power Steering System Using T-S Fuzzy Model Approach . International Journal of Automation and Computing, 2009, 6(2): 198-203. doi: 10.1007/s11633-009-0198-0
[19]	. Some Remarks on the Boundedness and Convergence Properties of Smooth Sliding Mode Controllers . International Journal of Automation and Computing, 2009, 6(2): 154-158. doi: 10.1007/s11633-009-0154-z
[20]	Jie Chen, Feng Pan, Tao Cai. Acceleration Factor Harmonious Particle Swarm Optimizer . International Journal of Automation and Computing, 2006, 3(1): 41-46. doi: 10.1007/s11633-006-0041-9

点击查看大图

计量

文章访问数: 5567
HTML全文浏览量: 40
PDF下载量: 2689
被引次数: 0

A Precise Robust Fuzzy Control of Robots Using Voltage Control Strategy

doi: 10.1007/s11633-013-0697-x

A Precise Robust Fuzzy Control of Robots Using Voltage Control Strategy

Corresponding author: Mohammad Mehdi Fateh

计量

A Precise Robust Fuzzy Control of Robots Using Voltage Control Strategy

doi: 10.1007/s11633-013-0697-x

1. Department of Electrical and Robotic Engineering, Shahrood University of Technology, Shahrood 3619995161, Iran

English Abstract

A Precise Robust Fuzzy Control of Robots Using Voltage Control Strategy

1. Department of Electrical and Robotic Engineering, Shahrood University of Technology, Shahrood 3619995161, Iran

Corresponding author: Mohammad Mehdi Fateh

全文HTML

目录

A Precise Robust Fuzzy Control of Robots Using Voltage Control Strategy

doi: 10.1007/s11633-013-0697-x

A Precise Robust Fuzzy Control of Robots Using Voltage Control Strategy

Corresponding author: Mohammad Mehdi Fateh

计量

出版历程

A Precise Robust Fuzzy Control of Robots Using Voltage Control Strategy

doi: 10.1007/s11633-013-0697-x

1. Department of Electrical and Robotic Engineering, Shahrood University of Technology, Shahrood 3619995161, Iran

English Abstract

A Precise Robust Fuzzy Control of Robots Using Voltage Control Strategy

1. Department of Electrical and Robotic Engineering, Shahrood University of Technology, Shahrood 3619995161, Iran

Corresponding author: Mohammad Mehdi Fateh

全文HTML

目录