Abstract
When dealing with microprocessors with limited resources and networks with limited bandwidth, the research of event triggering technology becomes more and more important. In order to save communication resources, this paper is concerned with the event-triggered control problem for a class of p-normal uncertain nonlinear systems with unknown growth rate. At first, an event-triggered controller is designed for the nominal system by adding a power integrator technique. Then, a novel dynamic gain is introduced into the proposed event-triggered controller to render lower-triangular uncertain nonlinear systems globally asymptotically stable. At the same time, Zeno phenomenon is excluded. Finally, the proposed method is extended to event-triggered control of p-normal upper-triangular uncertain nonlinear systems. A practical circuit system and a numerical simulation are given to illustrate the effectiveness of the proposed method.
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This work is supported in part by National Natural Science Foundation of China (62373096) and Natural Science Foundation of Jiangsu Province (BK20211162)
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Appendix
Appendix
In this section, a generic constant c is used to represent some positive constant values. It may be different in different places.
Proof of Proposition 1:
From the construction of \(W_k\), one has
From (10) and using Young’s inequality, it can be seen that
Substituting (A2) into (A1) and using Young’s inequality, one has
with a constant \({\hat{c}}_1>0\).
Proof of Proposition 2:
By Lemma 3, one has
From (10), one has
If \(\tau >0\), then \(\frac{r_{i-1}}{r_ip_{i-1}}=\frac{r_{i-1}}{r_{i-1}+\tau }<1\). Then, we have
If \(\tau \le 0\), then \(\frac{r_{i-1}}{r_ip_{i-1}}=\frac{r_{i-1}}{r_{i-1}+\tau }\ge 1\). By Lemma 3, one has
From the above two cases, one has
where \(\alpha _i>0\) and \(g_i\) is a continuous function of \(l_{i-1}\) with \(g_2(\cdot )=0\).
Proof of Proposition 3:
From the definition of \(e_i\) and using Lemma 3, one has
where \(m_i=2^{1-\rho _i/p_{i-1}}\).
Proof of Proposition 4:
From the definitions of \(\rho _i\) and \(r_i\), one has \(r_i\rho _i/r_{i-1}>1\). By Lemma 3, from (21) one has
From the definition of \(e_i\) and (10), one has
Substituting (A11) into (A10) and using Young’s inequality, one has
where \(h_i(\cdot )\) is a continuous function of \(l_{i-1}\). It should be pointed out that \({\hat{x}}_i^{\rho _i}-\zeta _i^{r_i\rho _i/r_{i-1}}=0\) for \(i=2\).
Proof of Proposition 5:
From (22) and the definition of \(e_i\), one has
From the definition of \(e_{n-1}\), one has
If \(\tau \ge 0\), then \(\frac{r_{n-1}}{r_np_{n-1}}=\frac{r_{n-1}}{r_{n-1}+\tau }\le 1\). By Lemma 3, one has
If \(\tau < 0\), then \(\frac{r_{n-1}}{r_np_{n-1}}=\frac{r_{n-1}}{r_{n-1}+\tau }>1\). From (10) and Lemma 3, one has
Using Young’s inequality and the above inequalities, one has
where \({\bar{\alpha }}, c_1\) are constants and \(g_n\) is a continuous function of \(l_{n-1}\).
Proof of Proposition 6:
From (33), one has
where the last relation is obtained by \(\xi _n^\frac{2\mu -\tau -r_{n}}{\alpha }x_{n+1}^{*}\le 0\) and \(\frac{1+\delta _0 L^{-1}}{1+b_1(t)\delta _0 L^{-1}}-1\ge 0\).
Now, we estimate the first term of (A19).
From (10), one has \(|x_i^{{\alpha }/{r_i}}|\le c(|\xi _i|+|\xi _{i-1}|)\). By Lemma 3, we have
Substituting (A21) into (A20) yields
where \({\tilde{\alpha }}>0\) is a constant.
By using Young’s inequality, one has
where \(c_2>0\) is a constant.
Substituting (A22) and (A23) into (A19), one has
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Zhai, J. Event-triggered control for p-normal uncertain nonlinear systems. Nonlinear Dyn 112, 3661–3677 (2024). https://doi.org/10.1007/s11071-023-09220-0
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DOI: https://doi.org/10.1007/s11071-023-09220-0