Cover page and Table of Contents: PDF (size: 513KB)
Full Text (PDF, 513KB), PP.19-25
Views: 0 Downloads: 0
Wavelet neural networks, reduced order observer, adaptive control, delayed systems, actuator saturation, Lyapunov- Krasovskii functional
This Paper investigates the mean to design the reduced order observer and observer based controllers for a class of delayed uncertain nonlinear system subjected to actuator saturation. A new design approach of wavelet based adaptive reduced order observer is proposed. The proposed wavelet adaptive reduced order observer performs the task of identification of unknown system dynamics in addition to the reconstruction of states of the system. Wavelet neural network (WNN) is used to approximate the uncertainties present in the system as well as to identify and compensate the nonlinearities introduced in the system due to actuator saturation. Using the feedback control, based on reconstructed states, the behavior of closed loop system is investigated. In addition robust control terms are also designed to attenuate the approximation error due to WNN. Adaptation laws are developed for the online tuning of the wavelet parameters and the stability of the overall systems is assured by using the Lyapunov- Krasovskii functional. A numerical example is provided to verify the effectiveness of theoretical development.
Manish Sharma, Ajay Verma, "Wavelet Adaptive Reduced Order Observer Based Tracking Control for a Class of Uncertain Time Delay Nonlinear Systems Subjected to Actuator Saturation", International Journal of Intelligent Systems and Applications(IJISA), vol.4, no.12, pp.19-25, 2012. DOI:10.5815/ijisa.2012.12.03
H. Lens and J. Adamy, “Observer based controller design for linear systems with input constraints”, Proceedings of 17th World Congress, The international federation of automatic control, Seoul Korea, pp.9916-9921, July 2008.
F. Abdollahi, H.A Talebi and R.V. Patel, “A stable neural network-based observer with application to flexible-joint manipulators”, IEEE Transactions on Neural Networks, Vol. 17, Issue 1, pp.118-129 Jan. 2006.
M. Sharma, A. Kulkarni and A. Verma, “Wavelet Adaptive Observer Based Control for a Class of Uncertain Time Delay Nonlinear Systems with Input Constraints”, IEEE International Conference on Advances in Recent Technologies in Communication and Computing, ARTCOM, pp.863-86, 2009.
V. Sundarapandian, “Reduced order observer design for nonlinear systems” Applied Mathematics Letters 19, pp. 936–941, 2006.
Z. F. Lai and D. X. Hao, “The Design of Reduced-order Observer for Systems with Monotone Nonlinearities”, ACTA Automatica Sinica, Vol. 33, no.2, pp. 1290-1293, 2007.
Y. G. Liu and J. F. Zhang, “Reduced-order observer-based control design for nonlinear stochastic systems”, Systems & Control Letters 52, pp. 123 – 135, 2004.
G. Bartolini, E. Punta and T. Zolezzi, “Reduced-Order Observer for Sliding Mode Control of Nonlinear Non-Affine Systems”, Proceedings of the 47th IEEE Conference on Decision and Control, Mexico, 2008.
J.P. Richard, “Time delay systems: an overview of some recent advances and open problems”, Automatica, vol. 39, pp. 1667-1694, 2003.
E. Fridman and U. Shaked, “An improved stabilization method for linear time delay systems”, IEEE Transactions on Automatic Control, vol. 47, pp. 1931–1937, 2002.
V.L. Khantonov and A.P. Zhabko, “Lyapunov-Krasovskii approach to robust stability analysis of time delay systems”, Automatica, vol. 39, pp. 15-20, 2003.
F. Morabito, A. R. Teel, and L. Zaccarian, “Nonlinear antiwindup applied to Euler–Lagrange systems,” IEEE Transactions on Robotics and Automation, Vol. 20, no. 3, pp. 526-537, June 2004.
P. He and S. Jagannathan, “Reinforcement learning neural-network-based controller for nonlinear discrete-time systems with input constraints,” IEEE Transactions on Systems, Man, and Cybernetics—Part B: Cybernetics, Vol. 37, no. 2, pp.425-436, April 2007.
J. Zhou, M. Joo and Y. Zhou, “Adaptive neural network control of uncertain nonlinear system in presence of input saturation”, Proceedings of the ICARCV, pp.895-899, 2006.
Q. Zhang and A. Benveniste, “Wavelet networks,” IEEE Transactions on Neural Networks, Vol. 3, no. 6, pp.889-898, November 1992.
J. Zhang, G. G. Walter, Y. Miao, and. W. Lee, “Wavelet neural networks for function learning,” IEEE Transactions on Signal Processing, Vol. 43, no. 6, pp.1485-1497, June 1995.
B. Delyon, A. Juditsky, and A. Benveniste, “Accuracy analysis for wavelet approximations,” IEEE Transactions on Neural Networks, Vol. 6, no. 2, pp.332-348 March 1995.