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Periodic solution and dynamical analysis for a delayed food chain model with general functional response and discontinuous harvesting

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Abstract

In this paper, a delayed food chain model with general functional response and discontinuous harvesting is considered. Under some reasonable assumptions, one proves the positivity and boundedness of the solutions. Moreover, the sufficient conditions for the existence of the periodic solution are found by using differential inclusion theory and topological degree theory. Most interestingly, the globally asymptotically stable of the periodic solution is studied by using a selected Lyapunov function and the sufficient conditions for it are given. Finally, one gives the numerical simulations to confirm the theoretical results.

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References

  1. Dunbar, S.R., Rybakowski, K.P., Schmitt, K.: Persistence in models of predator-prey populations with diffusion. J. Differ. Equ. 65(1), 117–138 (1986)

    Article  MathSciNet  Google Scholar 

  2. Zhang, T., Zhang, T., Meng, X.: Stability analysis of a chemostat model with maintenance energy. Appl. Math. Lett. 68, 1–7 (2017)

    Article  MathSciNet  Google Scholar 

  3. Ko, W., Ryu, K.: Qualitative analysis of a predator-prey model with Holling type II functional response incorporating a prey refuge. J. Differ. Equ. 231(2), 534–550 (2006)

    Article  MathSciNet  Google Scholar 

  4. Djilali, D.Salih: Effect of herd shape in a diffusive predator-prey model with time delay. J. Appl. Anal. Computat. 9(2), 638–654 (2019)

    MathSciNet  Google Scholar 

  5. Etoua, R.M., Rousseau, C.: Bifurcation analysis of a generalized Gause model with prey harvesting and a generalized Holling response function of type III. J. Differ. Equ. 249(9), 2316–2356 (2010)

    Article  MathSciNet  Google Scholar 

  6. Sarker, M., Sohel, R.: Bifurcations and chaos control in a discrete-time predator-prey system of Leslie type. J. Appl. Anal. Comput. 9(1), 31–44 (2019)

    MathSciNet  Google Scholar 

  7. Atabaigi, A.: Bifurcation and chaos in a discrete time predator-prey system of Leslie type with generalized Holling type III functional response. J. Appl. Anal. Comput. 7(2), 411–426 (2017)

    MathSciNet  Google Scholar 

  8. Kumari, N., Mohan, N.: Cross diffusion induced turing patterns in a tritrophic food chain model with Crowley-Martin functional response. Mathematics 7(3), 229 (2019)

    Article  Google Scholar 

  9. Li, H., Long, Z., Cheng, H., Jiang, Y., et al.: Dynamic analysis of a fractional-order single-species model with diffusion. Nonlinear Anal. Model. Control 22, 303–316 (2017)

    Article  MathSciNet  Google Scholar 

  10. Peng, R., Shi, J., Wang, M.: Stationary pattern of a ratio-dependent food chain model with diffusion. SIAM J. Appl. Math. 67(5), 1479–1503 (2007)

    Article  MathSciNet  Google Scholar 

  11. Roy, J., Alam, S.: Study on autonomous and nonautonomous version of a food chain model with intraspecific competition in top predator. Math. Methods Appl. Sci. 43(6), 3167–3184 (2020)

    Article  MathSciNet  Google Scholar 

  12. Alidousti, J., Ghahfarokhi, M.M.: Dynamical behavior of a fractional three-species food chain model. Nonlinear Dyn. 95(3), 1841–1858 (2019)

    Article  Google Scholar 

  13. Tuerxun, N., Teng, Z., Muhammadhaji, A., et al.: Global dynamics in a stochastic three species food-chain model with harvesting and distributed delays. Adv. Differ. Equ. 2019(1), 187 (2019)

    Article  MathSciNet  Google Scholar 

  14. Panday, P., Pal, N., Samanta, S., et al.: Stability and bifurcation analysis of a three-species food chain model with fear. Int. J. Bifurc. Chaos 28(01), 1850009 (2018)

    Article  MathSciNet  Google Scholar 

  15. Mukherjee, N., Ghorai, S., Banerjee, M.: Detection of turing patterns in a three species food chain model via amplitude equation. Commun. Nonlinear Sci. Numer. Simul. 69, 219–236 (2019)

    Article  MathSciNet  Google Scholar 

  16. Castellanos, V., Castillo-Santos, F.E., Dela-Rosa, M.A., et al.: Hopf and bautin bifurcation in a tritrophic food chain model with Holling functional response types III and IV. Int. J. Bifurc. Chaos 28(03), 1850035 (2018)

    Article  MathSciNet  Google Scholar 

  17. Ali, N., Chakravarty, S.: Stability analysis of a food chain model consisting of two competitive preys and one predator. Nonlinear Dyn. 82(3), 1303–1316 (2015)

    Article  MathSciNet  Google Scholar 

  18. Zuo, W., Jiang, D.: Periodic solutions for a stochastic non-autonomous Holling-Tanner predator-prey system with impulses. Nonlinear Anal. Hybrid Syst. 22, 191–201 (2016)

    Article  MathSciNet  Google Scholar 

  19. Jiang, D., Zuo, W., Hayat, T., et al.: Stationary distribution and periodic solutions for stochastic Holling-Leslie predator-prey systems. Phys. A Stat. Mech. Appl. 460, 16–28 (2016)

    Article  MathSciNet  Google Scholar 

  20. Huang, C., Song, X., et al.: Modeling, analysis and bifurcation control of a delayed fractional-order predator-prey model. Int. J. Bifurc. Chaos 28(09), 1850117 (2018)

    Article  MathSciNet  Google Scholar 

  21. Zhang, G., Shen, Y.: Periodic solutions for a neutral delay Hassell-Varley type predator-prey system. Appl. Math. Comput. 264, 443–452 (2015)

    MathSciNet  MATH  Google Scholar 

  22. Zu, L., Jiang, D., O’Regan, D., et al.: Periodic solution for a non-autonomous Lotka-Volterra predator-prey model with random perturbation. J. Math. Anal. Appl. 430(1), 428–437 (2015)

    Article  MathSciNet  Google Scholar 

  23. Zhang, M., Chen, L., Li, Z.: Homoclinic bifurcation of a state feedback impulsive controlled prey-predator system with Holling-II functional response. Nonlinear Dyn. 98(2), 929–942 (2019)

    Article  Google Scholar 

  24. Yang, Y., Shao, Y., Li, M.: Periodic solution for a stochastic Predator-Prey model with impulses and holling-II functional response. J. Appl. Math. Phys. 07(10), 2212–2230 (2019)

    Article  Google Scholar 

  25. Lu, C., Ding, X.: Periodic solutions and stationary distribution for a stochastic predator-prey system with impulsive perturbations. Appl. Math. Comput. 350, 313–322 (2019)

    MathSciNet  MATH  Google Scholar 

  26. Rui, Y., Jiang, W., Yong, W.: Saddle-node-Hopf bifurcation in a modified Leslie-Gower predator-prey model with time-delay and prey harvesting. J. Math. Anal. Appl. 422(2), 1072–1090 (2015)

    Article  MathSciNet  Google Scholar 

  27. Zhuang, K., Jia, G., Liu, D.: Stability and hopf bifurcation in a three-component planktonic model with spatial diffusion and time delay. Complexity 2019, 17 (2019)

    Article  Google Scholar 

  28. Huang, C., Li, H., Cao, J.: A novel strategy of bifurcation control for a delayed fractional predator-prey model. Appl. Math. Comput. 347, 808–838 (2019)

    Article  MathSciNet  Google Scholar 

  29. Nindjin, A.F., Tia, K.T., Okou, H., et al.: Stability of a diffusive predator-prey model with modified Leslie-Gower and Holling-type II schemes and time-delay in two dimensions. Adv. Differ. Equ. 2018(1), 1–17 (2018)

    Article  MathSciNet  Google Scholar 

  30. Du, Y., Niu, B., Wei, J., et al.: Two delays induce Hopf bifurcation and double Hopf bifurcation in a diffusive Leslie-Gower predator-prey system. Chaos 29(1), 013101 (2019)

    Article  MathSciNet  Google Scholar 

  31. Liu, M.: Dynamics of a stochastic regime-switching predator-prey model with modified Leslie-Gower Holling-type II schemes and prey harvesting. Nonlinear Dyn. 96(1), 417–442 (2019)

    Article  Google Scholar 

  32. Guo, Z., Zou, X.: Impact of discontinuous harvesting on fishery dynamics in a stock-effort fishing model. Commun. Nonlinear Sci. Numer. Simul. 20(2), 594–603 (2015)

    Article  MathSciNet  Google Scholar 

  33. Dong, L., Chen, L., Sun, L.: Optimal harvesting policies for periodic Gompertz systems. Nonlinear Anal. Real World Appl. 8(2), 572–578 (2007)

    Article  MathSciNet  Google Scholar 

  34. Leard, B., Rebaza, J.: Analysis of predator-prey models with continuous threshold harvesting. Appl. Math. Comput. 217(12), 5265–5278 (2011)

    MathSciNet  MATH  Google Scholar 

  35. Cai, Z., Huang, L., Zhang, L., et al.: Dynamical behavior for a class of predator-prey system with general functional response and discontinuous harvesting policy. Math. Methods Appl. Sci. 38(18), 4679–4701 (2015)

    Article  MathSciNet  Google Scholar 

  36. Filippov, A.F.: Differential Equations with Discontinuous Right-hand Sides. Kluwer Academic Publishers, Boston (1988)

    Book  Google Scholar 

  37. Aubin, J.P., Frankowska, H.: Set-Valued Analysis. Birkhauser, Boston (1990)

    MATH  Google Scholar 

  38. Clarke, F.H.: Optimization and Nonsmooth Analysis. Wiley, New York (1983)

    MATH  Google Scholar 

  39. Yong, L., Zhenghua, L.: Periodic solutions of differential inclusions. Nonlinear Anal. Theory Methods Appl. 24(5), 631–641 (1995)

    Article  MathSciNet  Google Scholar 

  40. Kristi, M., Modestino, J., Deng, H.: Stabilization of Nonlinear Uncertain Systems. Springer, New York (1998)

    Google Scholar 

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Correspondence to Zhen Wang.

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This work was supported by the National Natural Science Foundation of China (Nos. 61573008, 61973199, 61973200), and Taishan Scholar Project of Shandong Province of China.

Appendix

Appendix

\({\varvec{Proof A_1}}\): If \({\varvec{H_1}}-{\varvec{H_3}}\) are satisfied, it is clear that \((t,x)\rightarrow F(t,x)=(F_1(t,x),F_2(t,x),\cdots ,F_n(t,x))^T\) is a U.S.C. set-valued map with nonempty compact convex values. Then the local existence of a solution x(t) to system (1) on \([-\tau ,T)\) for some \(T\in (0,+\infty )\) is a straightforward consequence of ( [36], p. 77, Th. 1).

When \(x_i(t)=0\), \(\bar{co}[h(x_i(t))]x_i(t)=0\) and \(h(x_i(t))x_i(t)\) is continuous at \(x_i=0\). Then, \(\exists \delta _i>0\) such that when \(|x_i|<\delta _i\), \(h(x_i(t))x_i(t)\) is continuous. System (1) can be rewritten as the following right hand continuous function

$$\begin{aligned} \left\{ \begin{aligned}&\frac{dx_1(t)}{dt}=x_1(t)[r_1(t)-u_1(t)x_1(t)-c_1(t)h_1(x_1(t))-a_1(t)\varphi _1(x_1(t))x_2(t)],&\\&\frac{dx_i(t)}{dt}=x_i(t)[-r_i(t)+b_{i-1}(t)\phi _{i-1}(x_{i-1}(t-\tau _{i-1}))\\ {}&-u_{i}(t)x_i(t)-c_i(t)h_i(x_i(t))-a_i(t)\varphi _{i}(x_i(t))x_{i+1}(t)],&\\&\frac{dx_n(t)}{dt}=x_n(t)[-r_n(t)+b_{n-1}(t)\phi _{n-1}(x_{n-1}(t-\tau _{n-1}))\\ {}&-u_{n}(t)x_n(t)-c_n(t)h_n(x_n(t))].&\end{aligned} \right. \end{aligned}$$
(10)

One asserts that \(x_i(t) > 0\) for all \(t\in [-\tau ,T)\). Otherwise, let \(t_i=\inf \{t|x_i(t)=0\}\). Owing to \(x_i(t)\) is continuous on \([-\tau ,T)\), then there exists a positive constant \(\vartheta _i\) such that \(t_i-\vartheta _i>0\) and \(0<x_i(t)<\delta _i\) on \([t_i-\vartheta _i,t_i]\). One can obtain

$$\begin{aligned} 0=x_i(t_i)=x_i(t_i-\vartheta _i)exp\left\{ \int _{t_i-\vartheta _i}^{t_i}\frac{F(s,x(s))}{x(s)}ds\right\} >0. \end{aligned}$$
(11)

It is a contradiction. Thus, \(x_i(t) > 0\) for all \(t\in [-\tau ,T)\). That is to say \(x_i(t)\) is positive.

\({\varvec{Proof A_2}}\): By (1) one can see that

$$\begin{aligned} \frac{dx_1(t)}{dt}<x_1(t)[r_1^M-u_1^Lx_1(t)]. \end{aligned}$$
(12)

Substituting \(x_1(t)=\frac{r_1^M}{u_1^L}=N_1\) into (12), one gets

$$\begin{aligned} \frac{dx_1(t)}{dt}<N_1[r_1^M-u_1^LN_1]=0. \end{aligned}$$
(13)

So if \(0<x_1(0)\le N_1\), for all \(t>0\), \(x_1(t)\le N_1\); else if \(x_1(0)> N_1\), according to (13), there exists a \(t^*_1>0\) such that when \(t>t^*_1\), \(x_1(t)\le N_1\).

From (1), one can get that

$$\begin{aligned} \frac{dx_i(t)}{dt}<x_i(t)[b_{i-1}^M\Psi _i N_{i-1}-u_{i}(t)x_i(t)], \end{aligned}$$
(14)

where \(N_i= \frac{b_{i-1}^M\Psi _i N_{i-1}}{u_i^L}\) for \(i=2,3,\ldots ,n\). By using the same method, one can see that when \(0<x_i(0)\le N_i\), \(x_i(t)\le N_i\) for all \(t>0\). When \(x_i(0)> N_i\), there exists a \(t^*_i>0\) such that when \(t>t^*_i\), \(x_1(t)\le N_i\). Let \(t^*=\max _{i=1,2,\ldots ,n}\{t^*_i\}\), then when \(t>t^*\) \(x_i(t)\le N_i\) for \(i=1,2,\ldots ,n\). By theorem 1, \(x_i(t)>0\). Thus, \(x_i(t)\) is ultimately bounded.

\({\varvec{Proof A_3}}\): By Theorem 1, it is easy to see that the solution of system (1) remains positive for all \(t>0\). Let \(\mu _i(t)=ln(x_i(t))\). Substituting them into differential inclusion (3), one derives that

$$\begin{aligned} \left\{ \begin{aligned} \frac{d\mu _1(t)}{dt}\in&r_1(t)-u_1(t)e^{\mu _1(t)}-c_1(t)\bar{co}[h_1(e^{\mu _1(t)})]-a_1(t)\varphi _1(e^{\mu _1(t)})e^{\mu _2(t)}=F_1(t,\mu ),&\\ \frac{d\mu _i(t)}{dt}\in&-r_i(t)+b_{i-1}(t)\phi _{i-1}(e^{\mu _{i-1}(t-\tau _{i-1})})-u_{i}(t)e^{\mu _i(t)}\\ {}&-c_i(t)\bar{co}[h_i(e^{\mu _i(t)})]-a_i(t)\varphi _{i}(e^{\mu _i(t)})e^{\mu _{i+1}(t)}\\&=F_i(t,\mu ),&\\ \frac{d\mu _n(t)}{dt}\in&-r_n(t)+b_{n-1}(t)\phi _{n-1}(e^{\mu _{n-1}(t-\tau _{n-1})})-u_{n}(t)e^{\mu _n(t)}\\ {}&-c_n(t)\bar{co}[h_n(e^{\mu _n(t)})]=F_n(t,\mu ).&\end{aligned} \right. \end{aligned}$$
(15)

It is easy to see that any positive solution x(t) of system (1) is absolutely continuous on any compact interval of \([-\tau ,T)\), and \(\mu _i(t)=ln(x_i(t))\) are absolutely continuous on any compact interval of \([0,+\infty )\) with respect to t. Obviously, if differential inclusion (15) has one \(\omega \)-periodic solution \(\mu ^*(t)=(\mu _1^*(t),\mu _2^*(t),\ldots ,\mu _n^*(t))^T\), \(x^*(t)=(x_1^*(t),x_2^*(t),\ldots ,x_n^*(t))\) is a positive \(\omega \)-periodic solution of differential inclusion (1). Define

$$\begin{aligned} C_\omega =\{\mu (t)\in C(R,R^n):\mu (t+\omega )=\mu (t)\},\qquad \Vert \mu (t)\Vert _{C_\omega }=\sum _{i=1}^n\max _{t\in [0,\omega ]}|\mu _i(t)|.\nonumber \\ \end{aligned}$$
(16)

where \(C(R,R^n)\) donates the continuous function on \((R,R^n)\). Let \(F(t,\mu )=(F_1(t,\mu ),F_2(t,\mu ),\ldots ,F_n(t,\mu ))^T\) for \(\mu (t)\in C_\omega \). It is clear that \(F : R \times R^n \longrightarrow R^n\) is a U.S.C. set-valued map with nonempty compact convex values. Next one will search for appropriate open, bounded subset \(\Omega \). Corresponding to the differential inclusion \(\frac{d\mu }{dt}=\lambda F(t,\mu ),\lambda \in (0,1)\),

$$\begin{aligned} \left\{ \begin{aligned} \frac{d\mu _1(t)}{dt}\in&\lambda \{r_1(t)-u_1(t)e^{\mu _1(t)}-c_1(t)\bar{co}[h_1(e^{\mu _1(t)})]-a_1(t)\varphi _1(e^{\mu _1(t)})e^{\mu _2(t)}\},&\\ \frac{d\mu _i(t)}{dt}\in&\lambda \{-r_i(t)+b_{i-1}(t)\phi _{i-1}(e^{\mu _{i-1}(t-\tau _{i-1})})-u_{i}(t)e^{\mu _i(t)}\\ {}&-c_i(t)\bar{co}[h_i(e^{\mu _i(t)})]-a_i(t)\varphi _{i}(e^{\mu _i(t)})e^{\mu _{i+1}(t)}\},\\ \frac{d\mu _n(t)}{dt}\in&\lambda \{-r_n(t)+b_{n-1}(t)\phi _{n-1}(e^{\mu _{n-1}(t-\tau _{n-1})})-u_{n}(t)e^{\mu _n(t)}\\ {}&-c_n(t)\bar{co}[h_n(e^{\mu _n(t)})]\},&\end{aligned} \right. \end{aligned}$$
(17)

By the measurable selection theorem [37], it is easy to find a measurable function \(\gamma =(\gamma _1,\gamma _2,\ldots ,\gamma _n)\) such that \(\gamma _i(t)\in \bar{co}[h_1(e^{u_1(t)})]\) \((i=1,2,\ldots ,n)\) for a.e. \(t\in [0,T)\). Then, one has

$$\begin{aligned} \left\{ \begin{aligned} \frac{d\mu _1(t)}{dt}=&\lambda \{r_1(t)-u_1(t)e^{\mu _1(t)}-c_1(t)\gamma _1(t)-a_1(t)\varphi _1(e^{\mu _1(t)})e^{\mu _2(t)}\},&\\ \frac{d\mu _i(t)}{dt}=&\lambda \{-r_i(t)+b_{i-1}(t)\phi _{i-1}(e^{\mu _{i-1}(t-\tau _{i-1})})-u_{i}(t)e^{\mu _i(t)}-c_i(t)\gamma _i(t)\\ {}&-a_i(t)\varphi _{i}(e^{\mu _i(t)})e^{\mu _{i+1}(t)}\},\\ \frac{d\mu _n(t)}{dt}=&\lambda \{-r_n(t)+b_{n-1}(t)\phi _{n-1}(e^{\mu _{n-1}(t-\tau _{n-1})})-u_{n}(t)e^{\mu _n(t)}-c_n(t)\gamma _n(t)\}.&\end{aligned} \right. \end{aligned}$$
(18)

Integrating (18) over the interval \([0,\omega ]\), one obtains

$$\begin{aligned} \left\{ \begin{aligned}&\int _0^\omega r_1(t)dt=\int _0^\omega u_1(t)e^{\mu _1(t)}dt+\int _0^\omega c_1(t)\gamma _1(t)dt+\int _0^\omega a_1(t)\varphi _1(e^{\mu _1(t)})e^{\mu _2(t)}dt,&\\&\int _0^\omega b_{i-1}(t)\phi _{i-1}(e^{\mu _{i-1}(t-\tau _{i-1})})dt=\int _0^\omega u_{i}(t)e^{\mu _i(t)}dt\\ {}&+\int _0^\omega c_i(t)\gamma _i(t)dt+\int _0^\omega a_i(t)\varphi _{i}(e^{\mu _i(t)})e^{\mu _{i+1}(t)}dt&\\&\qquad +\int _0^\omega r_i(t)dt,\\&\int _0^\omega b_{n-1}(t)\phi _{n-1}(e^{\mu _{n-1}(t-\tau _{n-1})})dt=\int _0^\omega u_{n}(t)e^{\mu _n(t)}dt\\ {}&+\int _0^\omega c_n(t)\gamma _n(t)dt+\int _0^\omega r_n(t)dt,&\end{aligned} \right. \end{aligned}$$
(19)

Then, one has

$$\begin{aligned} \int _0^\omega |\dot{\mu }_1|dt\le & {} \int _0^\omega r_1(t)dt+\int _0^\omega u_1(t)e^{\mu _1(t)}dt+\int _0^\omega c_1(t)\gamma _1(t)dt\nonumber \\&\quad +\int _0^\omega a_1(t)\varphi _1(e^{\mu _1(t)})e^{\mu _2(t)}dt=2\bar{r}\omega ,\nonumber \\ \int _0^\omega |\dot{\mu }_i|dt\le & {} \int _0^\omega b_{i-1}(t)\phi _{i-1}(e^{\mu _{i-1}(t-\tau _{i-1})})dt+\int _0^\omega r_i(t)dt\nonumber \\&\quad +\int _0^\omega u_{i}(t)e^{\mu _i(t)}dt+\int _0^\omega c_i(t)\gamma _i(t)dt\nonumber \\&\quad +\int _0^\omega a_i(t)\phi _{i}(e^{\mu _i(t)})e^{\mu _{i+1}(t)}dt\nonumber \\&\le 2\int _0^\omega b_{i-1}(t)\Psi _{i-1}e^{\mu _{i-1}(t-\tau _{i-1})}dt,\nonumber \\ \int _0^\omega |\dot{\mu }_n|dt\le & {} \int _0^\omega b_{n-1}(t)\phi _{n-1}(e^{\mu _{n-1}(t-\tau _{n-1})})dt+\int _0^\omega u_{n}(t)e^{\mu _n(t)}dt\nonumber \\&\quad +\int _0^\omega c_n(t)\gamma _n(t)dt+\int _0^\omega r_n(t)dt\nonumber \\&\le 2\int _0^\omega b_{n-1}(t)\Psi _{n-1}e^{\mu _{n-1}(t-\tau _{n-1})}dt. \end{aligned}$$
(20)

Because of \(\mu (t)\in C_\omega \), then there exist \(\xi _i,\eta _i\in [0,\omega ]\) such that

$$\begin{aligned} \mu _i(\xi _i)=\min _{t\in [0,\omega ]}\mu _i(t),\mu _i(\eta _i)=\max _{t\in [0,\omega ]}\mu _i(t). \end{aligned}$$
(21)

By (19), it is easy to see that \(\bar{r}_1\omega >\int _0^\omega u_1(t)e^{\mu _1(t)}dt\) and \(\int _0^\omega b_{i-1}(t)\phi _{i-1}(e^{\mu _{i-1}(t-\tau _{i-1})})dt>\int _0^\omega u_{i}(t)e^{\mu _i(t)}dt\) for \(i=2,3,\ldots ,n\).

$$\begin{aligned} \begin{aligned}&\mu _1(\xi _1)\le \ln \frac{\bar{r}_1}{\bar{u}_1}, \qquad \mu _i(\xi _i)\le \ln \frac{\bar{b}_{i-1}\Psi _{i-1}}{\bar{u}_i}. \end{aligned} \end{aligned}$$
(22)

Then,

$$\begin{aligned} \begin{aligned}&\mu _1(t)\le \mu _1(\xi _1)+\int _0^\omega |\dot{\mu }_1|dt\le \ln \frac{\bar{r}_1}{\bar{u}_1}+2\bar{r}\omega =K_1,\\&\mu _i(t)\le \mu _i(\xi _i)+\int _0^\omega |\dot{\mu }_i|dt\le \ln \frac{\bar{b}_{i-1}\Psi _{i-1}}{\bar{u}_i}+ 2\omega \bar{b}_{i-1}(t)\Psi _{i-1}e^{K_{i-1}}=K_i. \end{aligned} \end{aligned}$$
(23)

By (20) and (23), one can see that

$$\begin{aligned} \begin{aligned} \int _0^\omega |\dot{\mu }_1|dt&\le 2\bar{r}_1\omega =A_1,\\ \int _0^\omega |\dot{\mu }_i|dt&\le 2\omega \bar{b}_{i-1}(t)\Psi _{i-1}e^{K_{i-1}}=A_i, \end{aligned} \end{aligned}$$
(24)

for \(i=2,3,\ldots ,n\). By (19), one can see that

$$\begin{aligned} \int _0^\omega r(t)dt\le \int _0^\omega u_1(t)e^{\mu _1(\xi _i)}dt+\int _0^\omega c_1(t)Mdt +\int _0^\omega a_1(t)\varphi _1(e^{\mu _1(t)})e^{\mu _2(t)}dt.\nonumber \\ \end{aligned}$$
(25)

One has

$$\begin{aligned} \begin{aligned}&\omega \bar{r}_1\le \omega \bar{u}_1e^{\mu _1(\eta _1)}+\omega M\bar{c}_1+\omega \bar{a}_1\Psi _1 e^{K_2},\\&\mu _1(\eta _1)\ge \ln \frac{\bar{r}_1-M_1\bar{c}_1-\bar{a}_1\Psi _1 e^{K_2}}{\bar{u}_1}. \end{aligned} \end{aligned}$$
(26)

Then,

$$\begin{aligned} \mu _1(t)\ge \mu _1(\eta _1)-\int _0^\omega |\dot{\mu }_1|dt\ge \ln \frac{\bar{r}_1-M_1\bar{c}_1-\bar{a}_1\Psi _1 e^{K_2}}{\bar{u}_1}-2\bar{r}\omega =P_1. \end{aligned}$$
(27)

By (19) and (24), one obtains

$$\begin{aligned} \begin{aligned}&\omega \bar{b}_{i-1}\phi ^*_{i-1}\le \omega \bar{r}_{i}+\omega \bar{u}_{i}e^{\mu _i(\eta _i)}+\omega \bar{c}_i M_i+\omega a_i\Psi _{i}e^{K_{i+1}},\\&\omega \bar{b}_{n-1}\phi ^*_{n-1}\le \omega \bar{r}_{n}+\omega \bar{u}_{n}e^{\mu _n(\eta _n)}+\omega \bar{c}_n M_n,\\&\mu _i(\eta _i)\ge \ln \frac{\bar{b}_{i-1}\phi ^*_{i-1}- \bar{c}_iM_i- \bar{a}_i\Psi _{i}e^{K_{i+1}}-\bar{r}_{i}}{\bar{u}_{i}}\\&\mu _i(\eta _n)\ge \ln \frac{\bar{b}_{n-1}\phi ^*_{n-1}- \bar{c}_nM_n-\bar{r}_{n}}{\bar{u}_n},\\&\mu _i(t)\ge \mu _i(\eta _i)-\int _0^\omega |\dot{\mu }_i|dt\ge \ln \frac{\bar{b}_{i-1}\phi ^*_{i-1}- \bar{c}_iM_i- \bar{a}_i\Psi _{i}e^{K_{i+1}}-\bar{r}_{i}}{\bar{u}_{i}}-A_i=P_i,\\&\mu _n(t)\ge \mu _n(\eta _n)-\int _0^\omega |\dot{\mu }_n|dt\ge \ln \frac{\bar{b}_{n-1}\phi ^*_{n-1}- \bar{c}_nM_n-\bar{r}_{n}}{\bar{u}_{n}}-A_n=P_n. \end{aligned} \end{aligned}$$
(28)

where \(\phi ^*_{i-1}=\min \limits _{\mu _{i-1}(t)\in [P_{i-1},K_{i-1}]}\phi _i(e^{\mu _{i-1}(t)})\), \(i=2,3,\ldots ,n-1\). So

$$\begin{aligned} \begin{aligned}&\max \limits _{t\in [0,\omega ]}|\mu _1(t)|<\max \left\{ |\ln \frac{\bar{r}_1}{\bar{u}_1}|+A_1,|\ln \frac{\bar{r}_1-M\bar{c}_1-\bar{a}_1\Psi _1 e^{K_2}}{\bar{u}_1}|+A_1\right\} =R_1\\&\max \limits _{t\in [0,\omega ]}|\mu _i(t)|<\max \left\{ |\ln \frac{\bar{b}_{i-1}\Psi _{i-1}}{\bar{u}_i}|\right. \\&\quad \left. + A_i,|\ln \frac{\bar{b}_{i-1}\phi ^*_{i-1}- \bar{c}_iM_i- \bar{a}_i\Psi _{i}e^{K_{i+1}}-\bar{r}_{i}}{\bar{u}_{i}}|+ A_i\right\} =R_i\\&\max \limits _{t\in [0,\omega ]}|\mu _n(t)|<\max \left\{ |\ln \frac{\bar{b}_{n-1}\Psi _{n-1}}{\bar{u}_n}|+ A_n,|\ln \frac{\bar{b}_{n-1}\phi ^*_{n-1}- \bar{c}_nM_n-\bar{r}_{n}}{\bar{u}_{n}}|+ A_n\right\} =R_n \end{aligned} \end{aligned}$$
(29)

Obviously, \(R_i\) in (29) are independent of \(\lambda \). Consider the following system of algebraic inclusion:

$$\begin{aligned} \left\{ \begin{aligned} 0\in&\bar{r}_1-\bar{u}_1e^{\mu _1(t)}-\bar{c}_1\bar{co}[h_1(e^{\mu _1(t)})]-\bar{a}_1\varphi _1(e^{\mu _1(t)})e^{\mu _2(t)},&\\ 0\in&-\bar{r}_{i}+\bar{b}_{i-1}\phi _{i-1}(e^{\mu _{i-1}(t-\tau _{i-1})})-\bar{u}_{i}e^{\mu _i(t)}-\bar{c}_i\bar{co}[h_i(e^{\mu _i(t)})]-\bar{a}_i\varphi _{i}(e^{\mu _i(t)})e^{\mu _{i+1}(t)},\\ 0\in&-\bar{r}_{n}+\bar{b}_{n-1}\phi _{n-1}(e^{\mu _{n-1}(t-\tau _{n-1})})-\bar{u}_{n}e^{\mu _n(t)}-\bar{c}_n\bar{co}[h_n(e^{\mu _n(t)})],&\end{aligned} \right. \nonumber \\ \end{aligned}$$
(30)

It is clear that the set of all solutions for (30) are bounded if there exists. Denote \(R=\sum _{i=0}^nR_i\) where \(R_0\) is taken sufficiently large such that each solution \(u^*\in \mathbb {R}^n\) of the algebraic inclusion (30) satisfies \(\sum _{i=1}^n\mu ^*_i<R\). Let \(\Omega =\{(\mu _1,\mu _2,\ldots ,\mu _n)^T\in C_\omega :\Vert (\mu _1,\mu _2,\ldots ,\mu _n)^T\Vert _{C_\omega }<R,\forall t\in \mathbb {R}\}\). Clearly, \(\Omega \) is an open bounded set of \(C_\omega \) and \(u\notin \partial \Omega \) for any \(\lambda \in (0,1)\).

Suppose that there exists a solution \(\mu =(\mu _1,\mu _2,\ldots ,\mu _n)^T\in \partial \Omega \bigcap \mathbb {R}^n\) of the inclusion \(0\in \frac{1}{\omega }\int _0^\omega F(t,\mu )dt\), then \(\Sigma _{i=1}^{n}\mu _i=R\). Since each solution \(u^*\in R^n\) of the algebraic inclusion (30) satisfies \(\sum _{i=1}^n\mu ^*_i<R\), one has that

$$\begin{aligned}&0\notin \frac{1}{\omega }\int _0^\omega F(t,\mu )dt\nonumber \\&\quad =g_0(\mu ) =\left( {\begin{array}{*{10}c} \bar{r}_1-\bar{u}_1e^{\mu _1}-\bar{c}_1\bar{co}[h_1(e^{\mu _1})]-\bar{a}_1\varphi _1(e^{\mu _1})e^{\mu _2}\\ -\bar{r}_{i}+\bar{b}_{i-1}\phi _{i-1}(e^{\mu _{i-1}})-\bar{u}_{i}e^{\mu _i}-\bar{c}_i\bar{co}[h_i(e^{\mu _i})]-\bar{a}_i\varphi _{i}(e^{\mu _i})e^{\mu _{i+1}}\\ -\bar{r}_{n}+\bar{b}_{n-1}\phi _{n-1}(e^{\mu _{n-1}})-\bar{u}_{n}e^{\mu _n}-\bar{c}_n\bar{co}[h_n(e^{\mu _n})] \end{array}}\right) ,\nonumber \\ \end{aligned}$$
(31)

for \(i=2,3,\ldots ,n-1\). This is a contradiction.

Define a homotopic set-valued map

$$\begin{aligned} G(\mu ,\nu )= & {} \left( {\begin{array}{*{10}c} \bar{r}_1-\bar{u}_1e^{\mu _1} \\ \bar{b}_{i-1}\phi _{i-1}(e^{\mu _{i-1}})-\bar{u}_{i}e^{\mu _i} \\ \bar{b}_{n-1}\phi _{n-1}(e^{\mu _{n-1}})-\bar{u}_{n}e^{\mu _n} \end{array}} \right) \\&+ \nu \left( {\begin{array}{*{10}c} -\bar{c}_1\bar{co}[h_1(e^{\mu _1})]-\bar{a}_1\varphi _1(e^{\mu _1})e^{\mu _2}\\ -\bar{r}_{i}-\bar{c}_i\bar{co}[h_i(e^{\mu _i})]-\bar{a}_i\varphi _{i}(e^{\mu _i})e^{\mu _{i+1}}\\ -\bar{r}_{n}-\bar{c}_n\bar{co}[h_n(e^{\mu _n})] \end{array}} \right) ,\nu \in [0,1]. \end{aligned}$$

If \(\mu =(\mu _1,\mu _2,\ldots ,\mu _n)^T\in \partial \Omega \bigcap \mathbb {R}^n\), then \(\mu \) is a constant vector in \(\partial \Omega \bigcap \mathbb {R}^n\) with \(\sum _{i=1}^n|\mu _i|=R\). If

$$\begin{aligned} \left\{ \begin{aligned} 0\in&\bar{r}_1-\bar{u}_1e^{\mu _1}+\nu (\bar{c}_1\bar{co}[h_1(e^{\mu _1})]-\bar{a}_1\varphi _1(e^{\mu _1})e^{\mu _2}),&\\ 0\in&\bar{b}_{i-1}\phi _{i-1}(e^{\mu _{i-1}})-\bar{u}_{i}e^{\mu _i}+\nu (-\bar{r}_{i}-\bar{c}_i\bar{co}[h_i(e^{\mu _i})]-\bar{a}_i\varphi _{i}(e^{\mu _i})e^{\mu _{i+1}}),\\ 0\in&\bar{b}_{n-1}\phi _{n-1}(e^{\mu _{n-1}(t-\tau _{n-1})})-\bar{u}_{n}e^{\mu _n(t)}+\nu (-\bar{r}_{n}-\bar{c}_n\bar{co}[h_n(e^{\mu _n(t)})]).&\end{aligned} \right. \end{aligned}$$
(32)

One has that

$$\begin{aligned} \begin{aligned}&|\mu _1(t)|<\max \left\{ |\ln \frac{\bar{r}_1}{\bar{u}_1}|,|\ln \frac{\bar{r}_1-M\bar{c}_1-\bar{a}_1\Psi _1 e^{K_2}}{\bar{u}_1}|\right\}<R_1,\\&|\mu _i(t)|<\max \left\{ |\ln \frac{\bar{b}_{i-1}\Psi _{i-1}}{\bar{u}_i}|,|\ln \frac{\bar{b}_{i-1}\phi ^*_{i-1}- \bar{c}_i(t)M_i- \bar{a}_i\Psi _{i}e^{K_{i+1}}-\bar{r}_{i}}{\bar{u}_{i}}|\right\}<R_i,\\&|\mu _n(t)|<\max \left\{ |\ln \frac{\bar{b}_{n-1}\Psi _{n-1}}{\bar{u}_n}|,|\ln \frac{\bar{b}_{n-1}\phi ^*_{n-1}- \bar{c}_n(t)M_n-\bar{r}_{n}}{\bar{u}_{n}}|\right\} <R_n. \end{aligned}\nonumber \\\ \end{aligned}$$
(33)

So \(0\notin G(\mu ,\nu )\). It is easy to see that \(G(\mu ,0)=0\) has a unique solution. Assume \(\mu ^*=(\mu _1^*,\mu _2^*,\ldots ,\mu _n^*)\) is the solution of \(G(\mu ,0)=0\). Then

$$\begin{aligned} \begin{aligned} \deg \{g_0,\Omega \bigcap \mathbb {R}^n,0\}&=\deg \{G(\mu ,1),\Omega \bigcap \mathbb {R}^n,0\}=\deg \{G(\mu ,0),\Omega \bigcap \mathbb {R}^n,0\}\\&=sign \left| {\begin{array}{*{10}ccccc} -\bar{u}_1e^{\mu _1^*} &{}0 &{}0 &{}\cdots &{}0\\ * &{}-\bar{u}_{2}e^{\mu _2^*} &{}0 &{}\cdots &{}0\\ 0 &{}* &{}-\bar{u}_{3}e^{\mu _3^*} &{}\cdots &{}0\\ \vdots &{}\vdots &{}\vdots &{}\vdots &{}0\\ 0 &{}0 &{}0 &{}\cdots &{}-\bar{u}_{n}e^{\mu ^*_n} \end{array}} \right| \ne 0 \end{aligned} \end{aligned}$$
(34)

where \(deg(\cdot ,\cdot ,\cdot )\) denotes the topological degree for upper semi-continuous set-valued maps with compact convex values.

Above all, \(\Omega \) satisfies all the requirements in Lemma 1, then the differential inclusion (15) has at least one \(\omega \)-periodic solution. As a consequence, system (1) has at least one positive \(\omega \)-periodic solution.

\({\varvec{Proof A_4}}\): Suppose that \(\gamma (t)=(\gamma _1(t),\gamma _2(t),\ldots ,\gamma _n(t))\) is the harvesting solution associated with the solution \(x(t)=(x_1(t),x_2(t),\ldots ,x_n(t))\), and \(\gamma ^*(t)=(\gamma _1^*(t),\gamma ^*_2(t),\ldots ,\gamma ^*_n(t))\) is the harvesting solution associated with the positive \(\omega \)-periodic solution \(x^*(t)=(x_1^*(t),x_2^*(t),\ldots ,x_n^*(t))\). Define

$$\begin{aligned} \begin{aligned}&z_i(t)=\ln x_i(t)-\ln x_i^*(t),&V_i(z_i(t))=|z_i(t)|, \end{aligned} \end{aligned}$$
(35)

for \(i=1,2,\ldots ,n\). Then

$$\begin{aligned} \frac{dV_i(t)}{dt}=\kappa _i\left( \frac{\dot{x}_i(t)}{x_i(t)}-\frac{\dot{x}^*_i(t)}{x_i^*(t)}\right) , \end{aligned}$$
(36)

where \(\kappa _i\) can be chosen as follow

$$\begin{aligned} \kappa _i=\left\{ \begin{array}{l@{\quad }l} 0, &{}x_i(t)-x_i^*(t)=0,\gamma _i(t)-\gamma _i^*(t)=0, \\ sign(\gamma _i(t)-\gamma _i^*(t)), &{}x_i(t)-x_i^*(t)=0,\gamma _i(t)-\gamma _i^*(t)\ne 0, \\ sign(x_i(t)-x_i^*(t)) &{}x_i(t)-x_i^*(t)\ne 0. \end{array}\right. \end{aligned}$$

Then

$$\begin{aligned} \begin{aligned} \kappa _i(x_i(t)-x_i^*(t))=|x_i(t)-x_i^*(t)|,\\ \kappa _i(\gamma _i(t)-\gamma _i^*(t))=|\gamma _i(t)-\gamma _i^*(t)|. \end{aligned} \end{aligned}$$
(37)

So one has that

$$\begin{aligned}&\begin{aligned} \frac{dV_1(t)}{dt}&=\kappa _1\left( \frac{\dot{x}_1(t)}{x_1(t)}-\frac{\dot{x}^*_1(t)}{x_1^*(t)}\right) \\&=\kappa _1[-u_1(t)(x_1(t)-x_1^*(t))-c_1(t)(\gamma _1(t)-\gamma ^*_1(t))-a_1(t)(\varphi _1(x_1(t))x_2(t)\\&\quad -\varphi _1(x^*_1(t))x^*_2(t))]\\&\le -u_1(t)|x_1(t)-x_1^*(t)|-c_1(t)|\gamma _1(t)-\gamma _1^*(t)|+a_1(t)\varphi _1(x_1(t))|x_2(t)-x^*_2(t)|\\&\quad +a_1(t)x^*_2(t)|\varphi _1(x_1(t))-\varphi _1(x^*_1(t))| \end{aligned} \end{aligned}$$
(38)
$$\begin{aligned}&\begin{aligned} \frac{dV_i(t)}{dt}&=\kappa _i\left( \frac{\dot{x}_i(t)}{x_i(t)}-\frac{\dot{x}^*_i(t)}{x_i^*(t)}\right) \\&=\kappa _i[b_{i-1}(t)(\phi _{i-1}(x_{i-1}(t-\tau _{i-1}))\\&\quad -\phi _{i-1}(x^*_{i-1}(t-\tau _{i-1})))-u_{i}(t)(x_i(t)-x_i^*(t))\\&\quad -c_i(t)(\gamma _i(t)-\gamma ^*_i(t))-a_i(t)(\varphi _{i}(x_i(t))x_{i+1}(t)-\varphi _{i}(x^*_i(t))x^*_{i+1}(t))]\\&\le b_{i-1}(t)|\phi _{i-1}(x_{i-1}(t-\tau _{i-1}))-\phi _{i-1}(x^*_{i-1}(t-\tau _{i-1}))|-u_{i}(t)|x_i(t)-x_i^*(t)|\\&\quad -c_i(t)|\gamma _i(t)-\gamma ^*_i(t)|+a_i(t)|\varphi _{i}(x_i(t))x_{i+1}(t)-\varphi _{i}(x^*_i(t))x^*_{i+1}(t)| \end{aligned} \end{aligned}$$
(39)
$$\begin{aligned}&\begin{aligned} \frac{dV_n(t)}{dt}&=\kappa _n\left( \frac{\dot{x}_n(t)}{x_n(t)}-\frac{\dot{x}^*_n(t)}{x_n^*(t)}\right) \\&=\kappa _n[b_{n-1}(t)(\phi _{n-1}(x_{n-1}(t-\tau _{n-1}))\\&\quad -\phi _{n-1}(x^*_{n-1}(t-\tau _{n-1})))-u_{n}(t)(x_n(t)-x_n^*(t))\\&\quad -c_n(t)(\gamma _n(t)-\gamma ^*_n(t))]\\&\le b_{n-1}(t)|\phi _{n-1}(x_{n-1}(t-\tau _{n-1}))-\phi _{n-1}(x^*_{n-1}(t-\tau _{n-1}))|-u_{n}(t)|x_n(t)-x_n^*(t)|\\&\quad -c_n(t)|\gamma _n(t)-\gamma ^*_n(t)| \end{aligned} \end{aligned}$$
(40)

Since \(\varphi _i(x_i(t))\) and \(\phi _i(x_i(t))\) have continuous derivatives for \(x_i\in [0,+\infty )\), \(\varphi ^{'}_i(x_i(t))\) and \(\phi _i(x_i(t))\) have maximum value on \([0,N_i]\). Assume that \(\max \limits _{x_i\in [0,N_i]}|\varphi ^{'}_i(x_i(t))|=D_i\) and \(\max \limits _{x_i\in [0,N_i]}|\phi ^{'}_i(x_i(t))|=E_i\), then \(|\varphi _i(x_i(t))-\varphi _i(x^*_i(t))|\le D_i|x_i(t)-x_i^*(t)|\) and \(|\phi _i(x_i(t))-\phi _i(x^*_i(t))|\le E_i|x_i(t)-x_i^*(t)|\). So

$$\begin{aligned}&\frac{dV_1(z_1(t))}{dt}\le -(u_1(t)-a_1(t)x^*_2(t)D_1)|x_1(t)-x_1^*(t)|\nonumber \\&\qquad -\,c_1(t)|\gamma _1(t)-\gamma _1(t)|+a_1(t)\Phi _1|x_2(t)-x^*_2(t)|. \end{aligned}$$
(41)
$$\begin{aligned}&\frac{dV_i(z_i(t))}{dt}\le -(u_i(t)-a_i(t)x^*_{i+1}(t)D_i)|x_i(t)-x_i^*(t)|\nonumber \\&\qquad -\,c_i(t)|\gamma _i(t)-\gamma _i(t)|+a_i(t)\Phi _i|x_{i+1}(t)-x^*_{i+1}(t)|\nonumber \\&\qquad +\,b_{i-1}(t)E_{i-1}|x_{i-1}(t-\tau _{i-1})-x_{i-1}^*(t-\tau _{i-1})|. \end{aligned}$$
(42)
$$\begin{aligned}&\frac{dV_n(z_n(t))}{dt}\le b_{n-1}(t)E_{n-1}|x_{n-1}(t-\tau _{n-1})-x_{n-1}^*(t-\tau _{n-1})|\nonumber \\&\qquad -\,c_n(t)|\gamma _n(t)-\gamma ^*_n(t)|-u_{n}(t)|x_n(t)-x_n^*(t)|. \end{aligned}$$
(43)

Define \(y(t)=(y_1(t),y_2(t),\ldots ,y_n(t))\) and \(y_i(t)=x_i(t)-x_i^*(t)\). The selected Lyapunov function is defined as follow

$$\begin{aligned} \begin{aligned} V(z(t),y(t))=&\sum _{i=1}^nV_i(z_i(t))+\sum _{i=1}^{n-1}b_{i}(t)E_{i}\int _{t-\tau _{i}}^t|y_i(t)|dt \end{aligned} \end{aligned}$$
(44)

It is easy to see that V(z(t), y(t)) is C-regular. By (41), (42) and (43), one has that

$$\begin{aligned} \begin{aligned} \frac{dV(z(t),y(t))}{dt}\le&-\sum _{i=2}^{n-1}(u_i(t)-a_i(t)x^*_{i+1}(t)D_i-b_{i}(t)E_{i}\\&-a_{i-1}(t)\Phi _{i-1})|x_i(t)-x_i^*(t)|-u_{n}(t)|x_n(t)-x_n^*(t)|\\&-(u_1(t)-a_1(t)x^*_{2}(t)D_1-b_{1}(t)E_{1})|x_1(t)-x_1^*(t)|\\&-\sum _{i=1}^nc_i(t)|\gamma _i(t)-\gamma _i(t)|\\ \le&-\sum _{i=2}^{n-1}(u^L_i-a^M_iN_{i+1}D_i-b^M_{i}E_{i}-a^M_{i-1}\Phi _{i-1})|x_i(t)-x_i^*(t)|\\&-\sum _{i=1}^nc^L_i|\gamma _i(t)-\gamma _i(t)|\\&-u_{n}^L|x_n(t)-x_n^*(t)|-(u_1^L-a_1^M N_{2}D_1-b^M_{1}E_{1})|x_1(t)-x_1^*(t)|. \end{aligned} \end{aligned}$$
(45)

By the conditions \(u^L_i-a^M_iN_{i+1}D_i-b^M_{i}E_{i}-a^M_{i-1}\Phi _{i-1}>0\) for \(i=2,3,\ldots ,n-1\) and \(u_1^L-a_1^M N_{2}D_1-b^M_{1}E_{1}>0\), there exist a positive constant \(\beta =\min \limits _{i=2,3,\ldots ,n-1}\{u_1^L-a_1^M N_{2}D_1-b^M_{1}E_{1},u^L_i-a^M_iN_{i+1}D_i-b^M_{i}E_{i}-a^M_{i-1}\Phi _{i-1},u_{n}^L\}\) such that

$$\begin{aligned} \frac{dV(z(t),y(t))}{dt}<-\beta \sum _{i=1}^n|x_i(t)-x_i^*(t)|, \end{aligned}$$
(46)

for a.e. \(t>t^*\) where \(t^*\) is defined in Theorem 2. Integrating both sides of inequality, one has

$$\begin{aligned} \begin{aligned} V(z(t),y(t))+\beta \int _{t^*}^t\sum _{i=1}^{n}|x_i(s)-x_i^*(s)|ds\le V(z(t^*),y(t^*)). \end{aligned} \end{aligned}$$
(47)

So V(t) is bounded on \([0,+\infty )\).

$$\begin{aligned} \int _{t^*}^t\sum _{i=1}^{n}|x_i(s)-x_i^*(s)|ds<+\infty . \end{aligned}$$
(48)

By using Lemma 2, one can conclude that

$$\begin{aligned} lim_{t\rightarrow +\infty }\left( \sum _{i=1}^n|x_i(t)-x_i^*(t)|\right) =0. \end{aligned}$$
(49)

That is to say, the positive \(\omega \)-periodic solution of system (1) is globally asymptotically stable and the positive \(\omega \)-periodic solution \(x^*\) of system (1) is unique.

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Xie, Y., Wang, Z. Periodic solution and dynamical analysis for a delayed food chain model with general functional response and discontinuous harvesting. J. Appl. Math. Comput. 65, 223–243 (2021). https://doi.org/10.1007/s12190-020-01389-6

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