Browse > Article
http://dx.doi.org/10.5391/IJFIS.2007.7.2.096

An Adaptive Tracking Control for Robotic Manipulators based on RBFN  

Lee, Min-Jung (RIC for Ubiquitous Appliance, Dongseo University)
Jin, Tae-Seok (Dept. of Mechatronics Eng., Dongseo University)
Publication Information
International Journal of Fuzzy Logic and Intelligent Systems / v.7, no.2, 2007 , pp. 96-101 More about this Journal
Abstract
Neural networks are known as kinds of intelligent strategies since they have learning capability. There are various their applications from intelligent control fields; however, their applications have limits from the point that the stability of the intelligent control systems is not usually guaranteed. In this paper we propose an adaptive tracking control for robot manipulators using the radial basis function network (RBFN) that is e. kind of neural networks. Adaptation laws for parameters of the RBFN are developed based on the Lyapunov stability theory to guarantee the stability of the overall control scheme. Filtered tracking errors between actual outputs and desired outputs are discussed in the sense of the uniformly ultimately boundedness(UUB). Additionally, it is also shown that parameters of the RBFN are bounded. Experimental results for a SCARA-type robot manipulator show that the proposed adaptive tracking controller is adaptable to the environment changes and is more robust than the conventional PID controller and the neuro-controller based on the multilayer perceptron.
Keywords
Neural Network; RBFN; Lyapunov stability; Robot Manipulators; Uniformly Ultimately Boundedness;
Citations & Related Records
연도 인용수 순위
  • Reference
1 S. Jagannathan, F. L. Lewis and O. Pastravanu : 'Model reference adaptive control nonlinear dynamical systems using multilayer neural networks,' in Proc. of IEEE Int. Conf. on Neural Networks, vol. 7, pp. 4766-4771, 1994
2 D.Y.Meddah and A.Benallegue : 'A stable neuro-adaptive controller for rigid robot manipulators,' Journal of Intelligent and Robotic Systems, vol. 20, pp. 181-193, 1997   DOI
3 M.A.Abido and Y.Abdel-Magid : 'On-line identification of synchronous machines using radial basis function neural networks,' IEEE Trans. on Power Systems, vol. 12, no. 4, November 1997
4 R.Carelli and E.F.Camacho : 'A neural network based feedforward adaptive controller for robots,' IEEE Trans. On Systems, Man and Cybernetics, vol. 25, no. 9, pp. 1281-1288, September 1995   DOI   ScienceOn
5 Sridhar Seshagiri and Hassan K. Khalil: 'Output feedback control of nonlinear systems using rbf neural networks,' IEEE Trans. on Neural Networks, vol. 11, no. 1, January 2000
6 Frank L. Lewis, Kai Liu, and Aydin Yesildirek : 'Neuralnet robot controller with guaranteed tracking performance,' IEEE Trans. on Neural Networks, vol. 6, no. 3, May 1995
7 Robert M. Sanner and Jean-Jacques E. Siotine : 'Gaussian networks for direct adaptive control,' IEEE Trans. on Neural Networks, vol. 3, no. 6, November 1992
8 J.-S.R.Jang, C.-T.Sun, and E.Mizutani : Neuro-Fuzzy and Soft Computing, Prentice Hall, 1997
9 R. M. Scanner and J.-J. E. Slotine : 'Gaussian networks for direct adaptive control,' IEEE Trans. on Neural Networks, vol. 3, Nov. 1992
10 M.W.Spong and M.Vidyasagar : Robot Dynamic and Control, John Wiley & Sons, 1989
11 M.Zhihong, H.R.Wu, and M.Palaniswame : 'An adaptive tracking controller using neural networks for a class of nonlinear systems,' IEEE Trans. on Neural Networks, vol. 9, no. 5, September. 1998
12 R. K.S.Fu, R.C.Gonzalez, and C.S.G.Lee : Robotics, McGraw-Hill International Editions, 1987
13 M.-J. Lee and Y.-K. Choi : 'An Adaptive Neurocontroller Using RBFN for Robot Manipulators,' IEEE Trans. on Industrial Electronics, vol. 51, no. 3, June 2004
14 J.-J.E.Slotine and W. Li : Applied Nonlinear Control, Prentice Hall, 1991
15 H. D. Patirio and Derong Liu : 'Neural network-based model reference adaptive control system,' IEEE Trans. on Systems, Man and Cybernetics, vol. 30, no. 1, February 2000
16 A.S.Morris and S.Khemaissia : 'A neural network based adaptive robot controller,' Journal of Intelligent and Robotic Systems, vol. 15, pp. 3-10, 1996   DOI
17 K.S.Narendra and K.Parthasarathy : 'Identification and control of dynamical systems using neural networks,' IEEE Trans. On Neural Networks, vol. 1, no. 1, March 1990
18 Y.-K Choi, M.-J. Lee, S. Kim, and Y.-C. Kay: 'Design and implementation of an adaptive neural-network compensator for control system,' IEEE Trans. on Industrial Electronics, vol. 48, no. ?, Apr. 2001