Application of Self-Tuning PID Control with Feed-Forward Compensator Based on LS_SVM Inverse Model in Nonlinear System

Qing Ling Dai

doi:10.4028/www.scientific.net/AMM.401-403.1577

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 401-403Application of Self-Tuning PID Control with...

Application of Self-Tuning PID Control with Feed-Forward Compensator Based on LS_SVM Inverse Model in Nonlinear System

Abstract:

Aiming at the difficulty to building inverse model in the inverse model control system, the modeling method of inverse model based on the LS_SVM is proposed. In order to obtain better static and dynamic performance, the feed-forward compensator and self-tuning PID controller are consisted of the compound control system. As can be seen from the simulation results that the compound control system has a good ability to control nonlinear object with high tracking precision, good dynamic performance and better control effect.

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Periodical:

Applied Mechanics and Materials (Volumes 401-403)

Pages:

1577-1580

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.401-403.1577

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Online since:

September 2013

Authors:

Qing Ling Dai

Keywords:

Feed-Forward Compensator, Inverse Model Control, Least Squares Support Vector Machines (Ls-SVM), Self-Tuning PID Control

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References

[1] HUANG yin-tong，ZHANG Shao-Me，／I Min．A inverse control system based On least squares support vector machine and PID[J]．Journal of Mechanical＆Electrical Engineering，2010，27(2)：75-78.

Google Scholar

[2] LIU Bin, SU Hong-ye，CHU Jian．A method based On least squares support vector machine predictive control algorithm[J]．Control and Decision, 2004，19(20)：1439-1402.

Google Scholar

[3] Suykens J A K．Support vector machines：a nonlinear modeling and control perspective[J]．European Journal of Control，2001，7(2—3)：311-327.

Google Scholar

[4] WANG Hui，FI Dao-ying，SUN You-xian．Online SVM regression algorithm-based adaptive control[J]．Nenrocomputing, 2007．70(4／6)：952-959.

Google Scholar

[5] Shen Shu-guang Wang Guang-jun, Chen Hong. application of minimum support vector machine (SVM) in inverse dynamics and control system [J]. Proceedings of the CSEE, 2008, 28 (35) : 96-101.

Google Scholar

[6] LI L J，SU H Y and CHU J．Generalized predictive control with online least squares support vector machines[J]．Acta Automatica Sinica，2007，33(1 J)：1182-1188.

DOI: 10.1360/aas-007-1182

Google Scholar