Design of a Hybrid Adaptive CMAC Tracking Control for a Class of Uncertain Chaotic Systems with only Output Measurement

Abstract:

This paper presents an observer-based hybrid adaptive cerebellar model articulation controller (CMAC) with a supervisory controller for uncertain chaotic systems, in which the hybrid adaptive control composed of a direct adaptive CMAC and an indirect adaptive CMAC control is performed as the sliding mode control (SMC). The total states of the chaotic system are not assumed to be available for measurement. A state observer is used to estimate unmeasured states of the systems. The supervised control is appended to assure that the hybrid adaptive CMAC controller achieve a stable closed-loop system through Lyapunov stability theory. Finally, simulation results show that the effect of the approximation error on the tracking error can be attenuated efficiently.

• Periodical: Advanced Materials Research (Volumes 383-390)
• Pages: 5363-5368
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.383-390.5363
• Online since: November 2011
• Authors: Chun Sheng Chen
• Keywords: Chaotic System, CMAC, Direct Adaptive Controller, Indirect Adaptive Controller, Observer, Sliding Mode Control (SMC), Supervisory Controller

References

[1] J. J. Yan, K. K. Shyu and J. S. Lin, Chaos, Solitons & Fractals, Vol. 35 (2005), p.347.

[2] C. M. Lin and C. H. Chen, Chaos, Solitons & Fractals, Vol. 35 (2008), p.40.

[3] J. Wang, G. D. Qiao and B. Deng, Chaos, Solitons & Fractals, Vol. 24 (2005), p.1075.

[4] C. Hua and X. Guan, Chaos, Solitons & Fractals, Vol. 22 (2004), p.55.

[5] Y. J. Cao, Physics Letters A, Vol. 270 (2000), p.171.

[6] J. S. Albus, Trans. ASME J. Dyn. Syst., Meas., Contr., Vol. 97 (1975), p.220.

[7] J. S. Albus, Trans. ASME J. Dyn. Syst., Meas., Contr., Vol. 97 (1975), p.228.

[8] K. S. Hwang and C. S. Lin, IEEE Trans. Syst., Man, Cybern. B, Vol. 28 (1998), p.680.

[9] H. Shiraishi, S. L. Ipri and D. D. Cho, IEEE Trans. Contr. Sys. Technology, Vol. 3 (1995), p.32.

[10] U. Itkis, Control Systems of Variable Structure, (Wiley Publications, New York, 1976).

[11] J. J. E. Slotine and J. A. Coetsee, Int. J. Control, Vol. 43 (1986), p.1631.

[12] C. M. Lin and T. -Y. Chen, IEEE Trans. Neural Networks, Vol. 20 (2008), p.1377.

[13] Y. G. Leu, T. T. Lee and W. Y. Wang, IEEE Trans. Syst., Man, Cybern. B, Vol. 29 (1999), p.583.

[14] J. H. Park and S. H. Kim, IEE Proc. Control Theory Application, Vol. 151 (2004), p.65.

[15] L. X. Wang, IEEE Trans. Fuzzy Systems, Vol. 1 (1993), p.146.