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<p>In nonlinear systems with malicious faults on actuators and/or their input signals, the fault estimation error (FEE) information is difficult to obtain directly and indirectly because of unknown fault signals and system’s nonlinearities. This results in a significantly low utilization of the FEE, making it difficult to obtain more accurate fault estimation signals. Consequently, further improvements in fault compensation performance of reliable control may be hindered. Then an indirect approach for acquiring the FEE is proposed in this article by using the available data and the virtual input matrix projection technique. Furthermore, a class of fuzzy observers with a cooperative interaction structure is constructed utilizing the T-S fuzzy model. This can make full use of the FEE information to enhance the fault estimation accuracy. By integrating the proposed fault observer with the existing reliable control schemes, the compensation performance can be enhanced, thereby improving the control performance. Finally, a mass-spring-damper networked control system validates the presented methods.</p>

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A fuzzy cooperative interaction observer via indirect fault estimation error for enhanced reliable control of nonlinear systems

  • 期刊论文

  • 发表日期：

    2026年6月29日

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  • Xin Huang,
  • Qingyu Su,
  • Jian Li,
  • Jiuxiang Dong

摘要

In nonlinear systems with malicious faults on actuators and/or their input signals, the fault estimation error (FEE) information is difficult to obtain directly and indirectly because of unknown fault signals and system’s nonlinearities. This results in a significantly low utilization of the FEE, making it difficult to obtain more accurate fault estimation signals. Consequently, further improvements in fault compensation performance of reliable control may be hindered. Then an indirect approach for acquiring the FEE is proposed in this article by using the available data and the virtual input matrix projection technique. Furthermore, a class of fuzzy observers with a cooperative interaction structure is constructed utilizing the T-S fuzzy model. This can make full use of the FEE information to enhance the fault estimation accuracy. By integrating the proposed fault observer with the existing reliable control schemes, the compensation performance can be enhanced, thereby improving the control performance. Finally, a mass-spring-damper networked control system validates the presented methods.