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Adaptive neural output feedback control for stochastic nonlinear time-delay systems with unknown control directions

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Abstract

This paper first focuses on the problem of adaptive output feedback stabilization for a more general class of stochastic nonlinear time-delay systems with unknown control directions. By using a linear state transformation, the original system is transformed to a new system for which control design becomes feasible. Then a novel adaptive neural network (NN) output feedback control strategy, which only contains one adaptive parameter, is developed for such systems by combining the input-driven filter design, the backstepping technique, the NN’s parameterization, the Nussbaum gain function method and the Lyapunov–Krasovskii approach. The proposed control design guarantees that all signals in the closed-loop systems are 4-moment (or 2-moment) semi-globally uniformly bounded. Finally, two simulation examples are given to demonstrate the effectiveness and the applicability of the proposed control design.

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Correspondence to Zhaoxu Yu.

Appendix

Appendix

The Proof of Lemma 1 is given as follows

Proof

Firstly, we set

$$\begin{aligned} W(t,x)=V(t,x)e^{C_1 t}. \end{aligned}$$
(62)

It is easy to be obtained

$$\begin{aligned} \left. {EW(s,x(s))} \right| _0^t =E\int _0^t {\mathcal {L}W(s,x(s))\hbox{d}s}, \quad \forall \;\;t\in [0,t_f) \end{aligned}$$
(63)

Which is expressed, by (62), in the form

$$\begin{aligned} E\int _0^t {[C_1 V(s,x(s))e^{C_1 s}+\mathcal {L}V(s,x(s))e^{C_1 s}]\hbox{d}s} \end{aligned}$$
(64)

By the use of (4), this is bounded above by

$$\begin{aligned} E\int _0^t {(N(\zeta )\dot{\zeta }+C_2 )e^{C_1 s}\hbox{d}s} \le \frac{C_2 }{C_1 }(e^{C_1 t}-1)+\int _0^t {N(\zeta )\dot{\zeta }e^{C_1 s}\hbox{d}s}, \quad \forall \;\;t\in [0,t_f) \end{aligned}$$
(65)

From (63), we have

$$\begin{aligned} EW(t,x(t))\le EW(0,x(0))+\frac{C_2 }{C_1 }(e^{C_1 t}-1)+\int _0^t {N(\zeta )\dot{\zeta }e^{C_1 s}\hbox{d}s}, \quad \forall \;\;t\in [0,t_f ) \end{aligned}$$
(66)

By recalling that \(W(t,x)=V(t,x)e^{C_1 t}\), for any \(t\in [0,t_f)\), we obtain

$$\begin{aligned} EV(t,x(t))&\le EV(0,x(0))e^{-C_1 t}+\frac{C_2 }{C_1 }(1-e^{-C_1 t})+e^{-C_1 t}\int _0^t {N(\zeta )\dot{\zeta }e^{C_1 s}\hbox{d}s}\nonumber \\&\le EV(0,x(0))+\frac{C_2 }{C_1 }+\int _0^t {N(\zeta )\dot{\zeta }e^{-C_1 (t-s)}\hbox{d}s} \end{aligned}$$
(67)

Rewrite (67) as

$$\begin{aligned} 0 \le EV(t,x(t)) \le Const + \int _0^t {\left| {N(\zeta )\dot{\zeta }} \right| } \hbox{d}s,\;\forall t \in [0,t_f ) \end{aligned}$$
(68)

where \(Const = EV(0,x(0)) + \frac{{C_2 }}{{C_1 }}\).

Depending on the signs of \(N(\zeta )\) and \(\dot{\zeta }\), (68) can be further written as

$$\begin{aligned} 0 \le EV(t,x(t)) \le Const1 \pm \int _0^{\zeta (t)} {N(\zeta )\hbox{d}\zeta },\;\;\forall t \in [0,t_f ) \end{aligned}$$
(69)

where \(Const1 = Const + \int _{\zeta (0)}^0 {\left| {N(\zeta )} \right| \hbox{d}\zeta }\).

In the following, we first show that \(\zeta (t)\) is bounded on \([0,t_f )\). It needs to consider the following two cases: (a) \(\zeta (t)\) have upper bound, and (b) \(\zeta (t)\) have lower bound.

Cases (a): Suppose that \(\zeta (t)\) has no upper bounds on \([0,t_f )\). According to the properties of Nussbaum-type function, there must exist two monotone increasing sequences \(\{\zeta _n^{(j)} \}\) with \(\zeta _1^{(j)} > \left| {\zeta (0)} \right|\) and \(\mathop {\lim }\nolimits _{n \rightarrow \infty } \zeta _n^{(j)} = \infty\), \(j=1,2\), such that

$$\begin{aligned}& \mathop {\lim }\limits _{n \rightarrow \infty } \sup \frac{1}{{\zeta _n^{(1)} }}\int _0^{\zeta _n^{(1)} } {N(\zeta )} \hbox{d}\zeta = + \infty \end{aligned}$$
(70)
$$\begin{aligned}&\mathop {\lim }\limits _{n \rightarrow \infty } \inf \frac{1}{{\zeta _n^{(2)} }}\int _0^{\zeta _n^{(2)} } {N(\zeta )} \hbox{d}\zeta = - \infty \end{aligned}$$
(71)

Since \(\zeta (t)\) has no upper bounds on \([0,t_f )\), thus, there exist monotone increasing sequences \({t_n^{(j)}}, j=1,2\) such that

$$\begin{aligned} \left\{ {\begin{array}{l} {\zeta (t_n^{(j)} ) = \zeta _n^j ,\;\;j = 1,2,\;\;n = 1,2,...} \\ {\mathop {\lim }\limits _{n \rightarrow \infty } t_n^{(j)} = t_f ,\;j = 1,2} \\ \end{array}} \right. \end{aligned}$$
(72)

Dividing (69) by \(\zeta (t_n^{(j)} ) = \zeta _n^{(j)},\;j = 1,2\), we obtain

$$\begin{aligned}&0\le \frac{{EV(t_n^{(1)},x(t_n^{(1)}))}}{{\zeta (t_n^{(1)} )}} \le \frac{{Const1}}{{\zeta (t_n^{(1)} )}} \pm \frac{{\int _0^{\zeta _n^{(1)}} {N(\zeta )\hbox{d}\zeta } }}{{\zeta (t_n^{(1)} )}}\end{aligned}$$
(73)
$$\begin{aligned}&0 \le \frac{{EV(t_n^{(2)},x(t_n^{(2)}))}}{{\zeta (t_n^{(2)} )}} \le \frac{{Const1}}{{\zeta (t_n^{(2)} )}} \pm \frac{{\int _0^{\zeta _n^{(2)}} {N(\zeta )\hbox{d}\zeta } }}{{\zeta (t_n^{(2)} )}} \end{aligned}$$
(74)

Thus, if \(N(\zeta ) > 0\), (74) contradicts (71) and when \(N(\zeta ) < 0\), (73) contradicts (70). Therefore, \(\zeta (t)\) has upper bound on \([0,t_f )\).

Case (b): the following procedure will prove that \(\zeta (t)\) have lower bounds on \([0,t_f )\). Firstly, we assume that \(\zeta (t)\) have no lower bounds on \([0,t_f )\). According to the properties of Nussbaum-type function, there exist two monotone increasing sequences \(\{ t_n^{(j)} \}\), \(j=1,2\), such that \(\zeta (t_n^{(j)} ) = - \zeta _n^{(j)},\;j = 1,2\). Obviously, \(\mathop {\lim }\limits _{n \rightarrow \infty } t_n^{(j)} = t_f,\;j = 1,2\). Noting that the function \(N(\cdot )\) is even, (69) can be further written as

$$\begin{aligned} 0 \le EV(t,x(t)) \le Const1 \mp \int _0^{ - \zeta (t)} {N(\zeta )\hbox{d}\zeta },\;\;\;4\forall t \in [0,t_f ) \end{aligned}$$
(75)

Dividing (75) by \(\zeta (t_n^{(j)} ) = -\zeta _n^{(j)},\;j = 1,2\), we obtain

$$\begin{aligned}&0 \le \frac{{EV(t_n^{(1)},x(t_n^{(1)} ))}}{{ - \zeta (t_n^{(1)} )}} \le \frac{{Const1}}{{\zeta _n^{(1)} }} \mp \frac{{\int _0^{\zeta _n^{(1)}} {N(\zeta )\hbox{d}\zeta } }}{{\zeta _n^{(1)} }}\end{aligned}$$
(76)
$$\begin{aligned}&0 \le \frac{{EV(t_n^{(2)},x(t_n^{(2)} ))}}{{ - \zeta (t_n^{(2)} )}} \le \frac{{Const1}}{{\zeta _n^{(2)} }} \mp \frac{{\int _0^{\zeta _n^{(2)}} {N(\zeta )\hbox{d}\zeta } }}{{\zeta _n^{(2)} }} \end{aligned}$$
(77)

where \(n=1,2,\ldots\). Noting that \(t_n^{(j)} \rightarrow t_f\), \(\zeta _n^{(j)} \rightarrow \infty, j=1,2\) when \(n \rightarrow \infty\). Similarly, a contradiction can be found no matter what the sign of \(N(\zeta )\) is. Therefore, \(\zeta (t)\) has lower bound on \([0,t_f )\).

From the above analysis, we thus conclude the boundedness of \(\zeta (t)\) on \([0,t_f )\), which in turns shows that \(\int _0^t {N(\zeta )\dot{\zeta }\hbox{d}s}\) and \(EV(t,x(t))\) must be bounded on \([0,t_f )\).

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Yu, Z., Li, S. & Du, H. Adaptive neural output feedback control for stochastic nonlinear time-delay systems with unknown control directions. Neural Comput & Applic 25, 1979–1992 (2014). https://doi.org/10.1007/s00521-014-1686-x

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