Abstract
This paper investigates the problems of state/fault estimation and active fault-tolerant control (AFTC) design for time-delay descriptor fuzzy systems subject to external disturbances and actuator faults. Using Takagi–Sugeno fuzzy models, an adaptive fuzzy observer is proposed to achieve system state and actuator fault estimation simultaneously. According to Lyapunov functional method, design and analysis conditions of the resulting closed-loop delayed descriptor system are formulated in terms of linear matrices inequalities (LMIs). Observer and controller gains are computed by solving a set of LMIs in only one step and then used to both estimate the unmeasured states and actuator faults in AFTC context. Numerical examples are provided to show the merit and the conservativeness of the proposed approach in comparison with the existing methods by considering various types of actuator faults.
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Appendices
Appendix A: Proof of Theorem 1
Consider the following Lyapunov–Krasovskii functional:
The time derivative of V(t) is given by:
By using Lemma 1, we have:
where
By using (23) and substituting (22), (17) and (39) into Eq. (38), one can obtain:
Applying Jessen’s inequality [9] to deal with the cross product items, we obtain
Noting the extended state vector as follows:
Then, we can write :
where
Denote
where
By using Schur complement, inequality (25) is equivalent to \(\xi ^ T \phi _{i}^{11} \xi (t) + h^2[(E\dot{x}(t))^\mathrm{T} Z_1 (E\dot{x}(s))] + h^2 [\dot{e}_{x}^\mathrm{T}(s) Z_2 \dot{e}_x(s)] < 0\).
If condition (25) holds, it follows from (41) that
where \(\zeta =\lambda _\mathrm{min}(-\phi _i)\)
It follows that \(\dot{V}(t) \leqslant 0\) for \( \zeta \Vert \xi (t) \Vert ^2 > \delta \), and according to Lyapunov stability theory, \(\xi (t)\) will converge to a small set \(\Psi = \{ \xi (t) / \Vert \xi (t) \Vert ^2 \le \frac{\delta }{\zeta } \}\) ; thus, \(\xi (t)\) is uniformly bounded.
The proof is completed.
Appendix B: Proof of Theorem 2
We can write inequality (26) in this form
where
Consider the following symmetric matrix:
where \( \mathbb {Z}_{11} =\hbox {diag}(P_1^{-T},P_1^{-T}), \mathbb {Z}_{22} = \hbox {diag}(P_1^{-T},I,I,I)\) and \(\mathbb {Z}_{33} =P_1^{-T} \)
We can transform inequality (50) by pre- and post-multiplying it by \(\mathbb {Z}\), and we obtain this form:
By using Lemma 2, we obtain the following inequalities:
By applying Schur complement, we obtain the following inequality:
By posing \(X_1=P_1^{-1}, X_2=P_2, \widetilde{Z}_1=P_1^{-1}Z_1 P_1^{-T}, \widetilde{Q}_1=P_1^{-T}Q_1 P_1^{-1}, Y_{1i}=P_2 L_{1i}, Y_{2i}=P_2 L_{2i}\) and \(W_i=K_{i} P^{-1}_1\), we obtain inequality (30).
The proof is completed.
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Kharrat, D., Gassara, H., El Hajjaji, A. et al. Adaptive Fuzzy Observer-Based Fault-Tolerant Control for Takagi–Sugeno Descriptor Nonlinear Systems with Time Delay. Circuits Syst Signal Process 37, 1542–1561 (2018). https://doi.org/10.1007/s00034-017-0624-4
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DOI: https://doi.org/10.1007/s00034-017-0624-4