Adaptive Inverse Filter Design for Linear Minimum Phase Systems
(International Journal of Engineering Works)
Vol. 4, Issue 1, PP. 1-4, January 2017
Adaptive Tracking, Least Mean Square (LMS), Linear Minimum Phase System
Adaptive Inverse Filter (AIF) is the standard, tracking,control technique or method which has provided an extensive range of uses and applications for the last several years. This research paper deals with the adaptive inverse Filter(AIF) structure which is being utilized for the stabilized or stable linear systems. Also closed loop features of the AIF are similar as that of the low pass adaptive filtering. Hence, it reduces the consequences of disturbance and the noise. The simulation outcomes for the Linear Minimum phase system or plants are presented to validate the worth of the proposed scheme. AIF has displayed enhanced results in terms of the tracking output.
- H. Ahmad: Electrical Engineering UET, Peshawar. Email: email@example.com
- W. Shah: Electrical Engineering UET, Peshawar. Email: firstname.lastname@example.org
H. Ahmad, W. Shah, "Adaptive Inverse Filter Design for Linear Minimum Phase Systems" International Journal of Engineering Works, Vol. 4, Issue 1, PP. 1-4, January 2017.
-  G. L. Marconi and C.Melchiorri, “A solution technique for almost perfect tracking of minimum-phase, discrete-time linear systems,” Int. J. Control, vol. 74, no. 5, pp. 496–506, 2001.
-  R. Galindo, “Low order dynamic robust control for linear siso systems,”IEEE International Conference on Control Applications, Glasgow, Scotland,U.K., September 2002.
-  S. E. W. Bai, “A minimal k-step delay controller for robust tracking of non-minimum phase systems,” IEEE Conference on Decision and Control, no. 1, pp. 12–17, December 1994.
-  Z. W. Z. S. D. Gang, Z. Xingqun, “Improved filtered adaptive inverse control and its application on nonlinear ship maneuvering,” Journal of Systems Engineering and Electronics, December 2006.
-  F. M. A.-S. M. Shafiq and S. O. Farooq, “Adaptive control of non linear hammerstein model using nlms filter,” 10th IEEE ICECS, vol. 1-3, 2003.
-  B. W. K.J. Astrom, Adaptive control, ser. Addison-Wesley Longman Publishing Co. Inc. Boston. Addison-Wesley Longman Publishing, 1994.
-  Z. O. Jerzy Moscinski, Advance Control with Matlab and Simulink. Ellis Horwood Limited Publishing, 1995.
-  G. L. Plett, Adaptive inverse control of plants with disturbances. Phd, Stanford University, 1998.
-  G.L.Plett, “Adaptive inverse control of linear and nonlinear systems using dynamic neural networks,” IEEE Transactions on Neural Networks, March 2003.
-  M. A. S. M. Shafiq, “Direct adative inverse control,” IEICE Electronics Express, vol. 6, no. 5, pp. 223–229, 2009.’
-  E. W. B. Widrow, Adaptive Inverse Control: A Signal Processin Approach. Prentice Hall PTR, 1995.Express, vol. 6, no. 5, pp. 223–229, 2009.
-  B. W. K.J. Astrom, Adaptive control. Addison-Wesley Longman Publishing Co. Inc. Boston,MA, USA, 1994.
-  Advanced Digital Signal Processing and Noise Reduction. John Wiley and Sons Ltd,2006.
-  G. D.Ye, “Adaptive fault-tolerant tracking control against actuator faults with application to flight control,” IEEE Transactions on Control Systems Technology, November 2006.
-  T. B. L.B.Chouh, T. Marwala, “Using inverse neural control for hivadaptive control,” International Journal of computational Intelligence research, vol. 3, no. 1, 2007.