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In this chapter, the tracking control and fault detection problems are discussed for a class of uncertain nonlinear systems with known higher input powers. Firstly, by using the function approximation capability of neural networks and combining backstepping control technique and the properties of Nussbaum function, an observer-based adaptive control designing is constructed. In the sense of Lyapunov theory, theoretical analysis shows that all closed-loop signals are semi-globally uniformly ultimately bounded and converge to a small neighborhood of the origin, which is adjusted by appropriately choosing designed parameters. Then, fault detection mechanism is given. Finally, the effectiveness of the control scheme proposed in this chapter has been verified by an example.

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Adaptive Observer-Based Tracking Control and Fault Detection with Known Higher Input Powers

  • 章节

  • 发表日期：

    2025年

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  • Qikun Shen,
  • Dezhi Xu

摘要

In this chapter, the tracking control and fault detection problems are discussed for a class of uncertain nonlinear systems with known higher input powers. Firstly, by using the function approximation capability of neural networks and combining backstepping control technique and the properties of Nussbaum function, an observer-based adaptive control designing is constructed. In the sense of Lyapunov theory, theoretical analysis shows that all closed-loop signals are semi-globally uniformly ultimately bounded and converge to a small neighborhood of the origin, which is adjusted by appropriately choosing designed parameters. Then, fault detection mechanism is given. Finally, the effectiveness of the control scheme proposed in this chapter has been verified by an example.