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Direct adaptive fuzzy backstepping control of uncertain nonlinear systems in the presence of input saturation

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Abstract

In this paper, a novel direct adaptive fuzzy control approach is presented for uncertain nonlinear systems in the presence of input saturation. Fuzzy logic systems are directly used to tackle unknown nonlinear functions, and the adaptive fuzzy tracking controller is constructed by using the backstepping recursive design techniques. To overcome the problem of input saturation, a new auxiliary design system and Nussbaum gain functions are incorporated into the control scheme, respectively. It is proved that the proposed control approach can guarantee that all the signals of the resulting closed-loop system are semi-globally uniformly ultimately bounded (SGUUB), and the tracking error converges to a small neighborhood of the origin. A simulation example is included to illustrate the effectiveness of the proposed approach. Two key advantages of the scheme are that (i) the direct adaptive fuzzy control method is proposed for uncertain nonlinear system with input saturation by using Nussbaum function technique and (ii) The number of the online adaptive learning parameters is reduced.

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Acknowledgments

This work was supported in part by the National Natural Science Foundation of China (Nos. 61074014, 51179019, 60874056), the Outstanding Youth Funds of Liaoning Province (No. 2005219001), the Natural Science Foundation of Liaoning Province (No. 20102012) and China Postdoctoral Special Science Foundation (No. 200902241).

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Authors and Affiliations

  1. Navigation College, Dalian Maritime University, Dalian, 116026, Liaoning, People’s Republic of China

    Yongming Li & Tieshan Li

  2. Department of Basic Mathematics, Liaoning University of Technology, Jinzhou, 121001, Liaoning, People’s Republic of China

    Yongming Li & Shaocheng Tong

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  1. Yongming Li
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  2. Shaocheng Tong
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  3. Tieshan Li
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Correspondence to Yongming Li.

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Li, Y., Tong, S. & Li, T. Direct adaptive fuzzy backstepping control of uncertain nonlinear systems in the presence of input saturation. Neural Comput & Applic 23, 1207–1216 (2013). https://doi.org/10.1007/s00521-012-0993-3

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  • DOI: https://doi.org/10.1007/s00521-012-0993-3

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