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Reseach Article
RTRL Algorithm Based Adaptive Controller for Non-linear Multivariable Systems
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 1 - Number 5 |
| Year of Publication: 2010 |
| Authors: K.C. Sindhu Thampatty, M. P. Nandakumar, Elizabeth P. Cheriyan |
10.5120/115-230
|
K.C. Sindhu Thampatty, M. P. Nandakumar, Elizabeth P. Cheriyan . RTRL Algorithm Based Adaptive Controller for Non-linear Multivariable Systems. International Journal of Computer Applications. 1, 5 ( February 2010), 94-101. DOI=10.5120/115-230
Abstract
The paper presents a new design of adaptive and dynamic neural network-based controller architecture with feedback connection for non-linear multivariable systems. The network is trained on-line at each sampling interval using the desired output trajectory and the training method used is the Real Time Recurrent Learning Algorithm (RTRL). The recurrent network is a fully connected one, with feedback from output layer to the input layer through a delay element. Since the synaptic weights to the neurons are adjusted on-line, this controller has potential applications in real time control also. Moreover, it can be used for both continuous and discrete systems. The simulation results obtained by applying the algorithm to a non-linear multivariable system demonstrate the effectiveness of the proposed method.
References
- Al-Zohary T.A, Wahdan, M. A. R. Ghonaimy and A. A. Elshamy.,2002 Adaptive Control of Nonlinear Multivariable Systems Using Neural Networks and Approximate Models,, Jounal of applied sciences
- Chang L.H., 2007. Design of nonlinear controller for bi-axial inverted pendulum, IET Control theory Applications, ,Vol 1, No.4, pp.979-986.
- Daniele Semino and Gabriele Pannocchia, 1999. Robust Multivariable Inverse-Based Controllers: Theory and Application, Ind. Eng. Chem. Res., Vol 38, pp.2375-2382.
- Duan G.R, Yu H.H., 2008. Robust pole assignment in high-order descriptor linear systems via proportional plus derivative state feedback, IET Control theory Applications, Vol 2, No.4, pp.277-287.
- Ender L , Maciel Filho R., 2000. Design of multivariable controller based on neural networks, Elsevier, Computers and Chemical Engineering, Vol 24, pp. 937-943.
- Filho. B, Cabral E, Soares A, 1998 . A new approach to artificial neural networks, IEEE Trans on Neural Networks, ,Vol.9, no. 6, pp.1167- 1179.
- Jagannathan Sarangapani, 1989. Neural Network Control of Nonlinear Discrete-Time, Taylor and Francis ,New M. Young, The Technical Writers Handbook, Mill Valley, CA: University Science,
- Jin. L, Nikiforuk. P, Gupta M., 1995. Approximation of discrete time state space trajectories using dynamic recurrent networks, IEEE Trans on Automatic Control, Vol.40, no.7, pp.1266-1270
- Linkens. D, Nyongesa Y, Learning systems in intelligent control: an appraisal of fuzzy, neural and genetic algorithm control applications, IEE Proc. Control Theory App, 134(4), pp 367-385
- Narendra K.S and Parthasarathy. K., 1990. Identification and control of dynamical system using neural networks, IEEE Trans on Neural Networks, Vol.1, no. 6, pp.4-27.
- Panos J. Antsaklis,. 1993. Neural Networks in Control Systems, IEEE Trans on Energy Conversion, Vol.8, no. 1, pp71-77.
- Paul J Webrose . An overview of Neural Networks for control, IEEE Trans on Control Systems, no. 1, pp40-42.
- Pearlmutter. B., 1995. Gradient calculations for Dynamic Recurrent Neural networks: A Survey, IEEE Trans on Neural Networks, Vol.6, no.3, pp 1212
- Simon Haykin, 1994. Neural Networks-A comprehensive Foundation , IEEE Press,
- Sindhu Thampatty K .C., M. P. Nandakumar, Elizabeth. P. Cheriyan, 2009. ANN based Adaptive Controller tuned by RTRL Algorithm for non-linear system control, Proc. of Second International workshop on nonlinear Dynamics and Synchronisation, INDS'09, July 20-21, Klagenfurt, Austria.
- Steepen W. Riche Webrose, 1994. Steepest Descent Algorithm for Neural Network controllers and Filters, IEEE Trans on Neural Networks, Vol.5, no. 2.
- Sun X.M, Zhao. J, Wang. W., 2008. State feedback control for discrete delay systems with controller failures based on average dwell-time method, IET Control theory Applications, Vol 2, No.2, pp.126-132.
- Williams R.J and Zipser D., 1989. A learning algorithm for continually Running fully Recurrent Neural Networks, Neural Computation , Vol 1, pp 552-558.
- Zhang. Y, Chen.G. P, Malik. O.P and Hope, G.S., 1992. An Artificial Neural Network Based Adaptive Power System Stabiliser, IEEE Control System Magazine, Vol.12, no. 4, pp8-10.
- Zhang .B., 2008. Parametric eigen structure assignment by state feedback in descriptor systems, IET Control theory Applications, Vol 2, No.4, pp.303-309.
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