Next Article in Journal
Weakly Supervised Specular Highlight Removal Using Only Highlight Images
Previous Article in Journal
Review of Fault-Tolerant Control Methods for Suspension Systems: From Road Vehicles to Maglev Trains
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

The Global Existence and Boundedness of Solutions to a Chemotaxis–Haptotaxis Model with Nonlinear Diffusion and Signal Production

School of Mathematics and Statistics, Linyi University, Linyi 276005, China
*
Author to whom correspondence should be addressed.
Mathematics 2024, 12(16), 2577; https://doi.org/10.3390/math12162577
Submission received: 15 July 2024 / Revised: 14 August 2024 / Accepted: 19 August 2024 / Published: 21 August 2024
(This article belongs to the Special Issue Recent Advances in Complex Dynamics in Non-Smooth Systems)

Abstract

:
In this paper, we investigate the following chemotaxis–haptotaxis system (1) with nonlinear diffusion and signal production under homogenous Neumann boundary conditions in a bounded domain with smooth boundary. Under suitable conditions on the data we prove the following: (i) For 0 < γ 2 n , if α > γ k + 1 and β > 1 k , problem (1) admits a classical solution ( u , v , w ) which is globally bounded. (ii) For 2 n < γ 1 , if α > γ k + 1 e + 1 and β > max { ( n γ 2 ) ( n γ + 2 k 2 ) 2 n k + 1 , ( n γ 2 ) ( γ + 1 e ) n k + 1 } or α > γ k + 1 and β > max { ( n γ 2 ) ( n γ + 2 k 2 ) 2 n k + 1 , ( n γ 2 ) ( α + k 1 ) n k + 1 } , problem (1) admits a classical solution ( u , v , w ) which is globally bounded.
MSC:
35K55; 35K65; 35A07; 35B35

1. Introduction

In the present work, we consider the following chemotaxis–haptotaxis system with nonlinear diffusion and signal production:
u t = · ( D ( u ) u ) · ( H ( u ) v ) · ( I ( u ) w ) + u ( a μ u k 1 λ w ) , x Ω , t > 0 , v t = v v + g ( u ) , x Ω , t > 0 , w t = v w , x Ω , t > 0 , D ( u ) u ν H ( u ) v ν I ( u ) w ν = v ν = 0 , x Ω , t > 0 , u ( x , 0 ) = u 0 ( x ) , v ( x , 0 ) = v 0 ( x ) , w ( x , 0 ) = w 0 ( x ) , x Ω ,
where Ω R n ( n 2 ) is a bounded domain with a smooth boundary, the function u = u ( x , t ) denotes the cancer cell density, v = v ( x , t ) represents the concentration of matrix-degrading enzymes, and w = w ( x , t ) represents the density of an extracellular matrix. We assume that D , H , I C 2 ( [ 0 , ) ) fulfils, for all s 0 ,
D ( s ) K D ( s + 1 ) m 1 ,
0 H ( s ) χ s ( s + 1 ) α and H ( 0 ) = 0 ,
0 I ( s ) ξ s ( s + 1 ) β and I ( 0 ) = 0 ,
with K D , χ , ξ > 0 and α , β , m R . Moreover, we assume g C 1 ( [ 0 , ) ) such that
0 g ( s ) K g s γ for   all s 0 ,
where K g , γ > 0 . To this end, we assume that the initial data satisfy
u 0 , v 0 , w 0 C 2 + δ ( Ω ¯ ) , δ ( 0 , 1 ) , u 0 , v 0 , w 0 0 , u 0 ν | Ω = 0 , v 0 ν | Ω = 0 , w 0 ν | Ω = 0 .
The model (1) is reduced to the chemotaxis system if w 0 , which has been widely researched by many authors over the past several decades (see [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15]). In the case of g ( u ) = u , Zheng [5] proved that all solutions are global and uniformly bounded if 0 < 2 α m < max { k m , 2 N } or 2 α = k and μ is large enough. In the case of g ( u ) = u γ , Tao et al. [6] considered problem (1), showing that if 1 + γ α < k or 1 + γ α = k and μ is large enough, then the solutions of (1) are globally bounded. When cell growth is neglected and 1 α m + γ < 2 N , they also proved that system (1) possesses a non-negative classical solution ( u , v ) which is globally bounded. Later, Ding et al. [7] provided a boundedness result under 1 α m + γ < 2 n and proved the asymptotic stability when the damping effects of the logistic source are strong enough. Nowadays, there are more and more mathematical models used to describe complex natural phenomena, and the results are also very impressive (see [16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34]).
The chemotaxis–haptotaxis model was first proposed by Chalain and Lolas [35]:
u t = u χ · ( u v ) ξ · ( u w ) + u ( a μ u k 1 λ w ) , v t = v v + u , w t = v w .
and described the process of cancer cells invading surrounding healthy tissue. In the absence of reconstruction mechanisms, problem (7), with η = 0 , has been studied by many authors. For instance, Tao Wang [36,37,38] proved the global solvability and uniform boundedness for n = 1 , 2 . For the case of n = 3 , the global existence and boundedness was proved for μ χ and is sufficiently large (see [36,39]). Later, Tao and Winkler [40] researched how, under the fully explicit condition μ > χ 2 8 , the solution ( u , v , w ) exponentially stabilizes to a constant stationary solution ( 1 , 1 , 0 ) . When μ u ( 1 u w ) was replaced by u ( a μ u k 1 λ w ) , Zheng and Ke [41] proved that model (7) possesses a global classical solution which is bounded for k > 2 or k = 2 , with μ being sufficiently large. And they demonstrated that if μ is large enough, the corresponding solution of (7) exponentially decays to ( ( a μ ) 1 k 1 , ( a μ ) 1 k 1 , 0 ) .
In recent years, many authors have begun to study the chemotaxis–haptotaxis model with nonlinear diffusion, that is
u t = · ( D ( u ) u ) χ · ( u v ) ξ · ( u w ) + μ u ( 1 u w ) , x Ω , t > 0 , v t = v v + u , x Ω , t > 0 , w t = v w , x Ω , t > 0 ,
where D ( u ) C D ( u + 1 ) m 1 for all u > 0 . Tao and Winkler [42] showed the global existence of solutions to (8) if m > 2 n 2 + 4 n 4 n ( n + 4 ) for n 8 or m > 2 n 2 + 3 n + 2 8 n ( n + 1 ) n ( n + 2 ) for n 9 . Further, Li Wang et al. [43,44] proved the boundedness of solutions for m > 2 2 n , and Wang and Zheng et al. [45,46] extended the results to m > 2 n n + 2 . Later, Jin [47] obtained similar results for any m > 0 , under a smallness assumption on χ μ .
Next, we consider problem (1) with g ( u ) = u , k = 2 , a = λ = μ . Liu et al. [48] proved the global existence and boundedness of solutions for n = 2 if max { 1 α , 1 β } < m + 2 n 1 or for n 3 if max { 1 α , 1 β } < m + 2 n 1 with either m > 2 2 n or m 1 . Afterwards, Xu et al. [49] proved that if m > 0 , α > 0 , β 0 for n = 3 , problem (1) possesses a globally bounded weak solution. Subsequently, they discussed the large time behavior of solutions and showed that when 0 < m 1 , for appropriately large μ , ( u , v , w ) ( 1 , 1 , 0 ) as t . Later, Jia et al. [50] extended the boundedness result of [49], which deals with the global boundedness of solutions with α > 0 , β > 1 6 . This paper is devoted to researching the boundedness of the solution of (1) with nonlinear diffusion and signal production in the case of n 2 .
Now, we present the primary result of this paper.
Theorem 1.
Let Ω R n ( n 2 ) be a bounded domain with a smooth boundary and ( u 0 , v 0 , w 0 ) that satisfies (6). Suppose that D , H , I and g fulfill (2)–(5). Then,
(i) For 0 < γ 2 n , if α > γ k + 1 and β > 1 k , problem (1) possesses a classical solution ( u , v , w ) which is globally bounded.
(ii) For 2 n < γ 1 , if α > γ k + 1 e + 1 and β > max { ( n γ 2 ) ( n γ + 2 k 2 ) 2 n k + 1 , ( n γ 2 ) ( γ + 1 e ) n k + 1 } or α > γ k + 1 and β > max { ( n γ 2 ) ( n γ + 2 k 2 ) 2 n k + 1 , ( n γ 2 ) ( α + k 1 ) n k + 1 } , problem (1) possesses a classical solution ( u , v , w ) which is globally bounded.
This paper is organized as follows. In Section 2, we present the local existence of classical solutions to system (1) and recall some preliminaries. In Section 3, we establish the global existence and boundedness of solutions to system (1).

2. Preliminaries

We first state the local existence result of classical solutions to (1) as follows. In fact, by a fixed point argument similar to [13,51], it can be proved.
Lemma 1.
Assume that u 0 , v 0 , w 0 satisfy (6) and D , H , I and g fulfill (2)–(5). Then, there exists T max ( 0 , ] such that the system (1) admits a classical solution ( u , v , w ) C 2 + δ , 1 + δ 2 ( Ω × ( 0 , T max ) ) with
u 0 , v 0 , w 0 f o r a l l ( x , t ) Ω × ( 0 , T max )
such that either T max = , or
lim t T max sup ( u ( · , t ) L ( Ω ) + v W 1 , ( Ω ) ) = .
Then, we will give a useful lemma referred to as a variation of maximal Sobolev regularity, as obtained in (Lemma 4 [52]).
Lemma 2.
Let z 0 W 2 , p ( Ω ) and f L p ( 0 , T ; L p ( Ω ) ) . Then, the following problem
z t = z z + f , z ν = 0 , z ( x , 0 ) = z 0 ( x ) ,
possesses a unique solution: z L l o c p ( ( 0 , + ) ; W 2 , p ( Ω ) ) and z t L l o c p ( ( 0 , + ) ; L p ( Ω ) ) . If t 0 ( 0 , T ) , then
t 0 T Ω e p t | z | p d x d t C p t 0 T Ω e p t | f | p d x d t + C p z ( · , t 0 ) W 2 , p ( Ω ) p ,
where C p is a constant independent of t 0 .
According to [38], we have the following lemma.
Lemma 3.
Assume ( u , v , w ) be the solution of model (1). Then,
w ( x , t ) w 0 L ( Ω ) v ( x , t ) + C f o r ( x , t ) Ω × ( 0 , T max ) ,
where
C : = w 0 L ( Ω ) + 4 w 0 L ( Ω ) 2 + w 0 L ( Ω ) e .
In order to prove Theorem 1, following the ideas in [43], we firstly state the lemma.
Lemma 4.
Assume that D , H , I and g fulfill (2)–(5) with 0 < γ 1 , then we have
(i) There exists K > 0 such that for all t ( 0 , T max )
u ( · , t ) L 1 ( Ω ) K μ 1 k 1 .
(ii) For r [ 1 , n ( n γ 2 ) + ) , there exists K r > 0 such that for all t ( 0 , T max )
v ( · , t ) L r ( Ω ) K r .
where ( n γ 2 ) + : = max { n γ 2 , 0 } .
(iii) Assume that p > max { n γ 2 , γ } and u ( · , t ) L p ( Ω ) K . Then, there exists K p > 0 such that for all t ( 0 , T max )
v ( · , t ) L ( Ω ) K p .
(iv) Assume that q > n γ and u ( · , t ) L q ( Ω ) K . Then, there exists a positive constant K q such that for all t ( 0 , T max )
v ( · , t ) L ( Ω ) K q .

3. Proof of Theorem 1

In this section, we deal with the global existence and boundedness of system (1). We firstly devote time to establishing the L p –boundedness of u. For convenience, we denote T = T max .
Lemma 5.
Assume that D , H , I and g fulfill (2)–(5) with β > 1 k . Then,
(i) Let α > γ k + 1 e + 1 and p > max { 1 , β , n γ 2 + 1 k , γ k + 1 e + 1 } . If K 0 > 0 fulfills for all t ( 0 , T )
v ( · , t ) L p + k 1 β + k 1 ( Ω ) K 0 ,
then,
u ( · , t ) L p ( Ω ) K f o r t ( 0 , T ) ,
where K > 0 depends on K 0 , μ .
(ii) Let α > γ k + 1 and p > max { 1 , α , β } . If there exists K 0 > 0 fulfills for all t ( 0 , T )
v ( · , t ) L p + k 1 β + k 1 ( Ω ) K 0 ,
then,
u ( · , t ) L p ( Ω ) K f o r t ( 0 , T ) ,
where K > 0 depends on K 0 , μ .
Proof. 
Multiplying the first equation in (1) with p ( 1 + u ) p 1 and integrating by parts yields
d d t Ω ( u + 1 ) p d x p ( p 1 ) K D Ω ( u + 1 ) m + p 3 | u | 2 d x + p ( p 1 ) Ω ( u + 1 ) p 2 H ( u ) u · v d x + p ( p 1 ) Ω ( u + 1 ) p 2 I ( u ) u · w d x + p Ω ( u + 1 ) p 1 u ( a μ u k 1 λ w ) d x .
Since ( u + 1 ) k 2 k 1 ( u k + 1 ) , we have
p Ω ( u + 1 ) p 1 u ( a μ u k 1 λ w ) d x | a | p Ω ( u + 1 ) p d x μ p 2 k 1 Ω ( u + 1 ) k + p 1 d x + μ p Ω ( u + 1 ) p 1 d x 5 μ 6 · 2 k 1 Ω ( 1 + u ) p + k 1 d x + C 1 ,
where C 1 = ( 3 · 2 k + 1 ) p k 1 ( | a | p ) p + k 1 k 1 | Ω | μ p k 1 + ( 3 · 2 k + 1 ) p 1 k | Ω | μ p k + p 1 k . It follows from (22) and (23) that
d d t Ω ( u + 1 ) p d x p ( p 1 ) Ω ( u + 1 ) p 2 H ( u ) u · v d x + p ( p 1 ) Ω ( u + 1 ) p 2 I ( u ) u · w d x 5 μ 6 · 2 k 1 Ω ( 1 + u ) p + k 1 d x + C 1 .
Define
φ ( u ) : = 0 u ( 1 + σ ) p 2 H ( σ ) d σ for u 0 .
We infer from (3) that
0 φ ( u ) χ 0 u ( 1 + σ ) p α 1 d σ .
This implies for u 0
φ ( u ) 2 χ | p α | , for p < α , χ ln ( 1 + u ) , for p = α , χ p α ( 1 + u ) p α , for p > α .
Integrating by parts the first term of (24), we obtain that
p ( p 1 ) Ω ( 1 + u ) p 2 H ( u ) u · v d x = p ( p 1 ) Ω φ ( u ) · v d x p ( p 1 ) Ω φ ( u ) | v | d x .
Case (i). Combining (25) with (26) yields, for γ k + 1 e + 1 < p < α and n 2 ,
p ( p 1 ) Ω ( 1 + u ) p 2 H ( u ) u · v d x 2 χ p ( p 1 ) | p α | Ω | v | d x 2 χ p ( p 1 ) | p α | Ω | v | n 2 d x + C 2 ,
where C 2 = 2 χ p ( p 1 ) | Ω | | p α | . For p > α , we obtain
p ( p 1 ) Ω ( 1 + u ) p 2 H ( u ) u · v d x χ p ( p 1 ) p α Ω ( 1 + u ) p α | v | d x , μ 3 · 2 k Ω ( 1 + u ) p + k 1 + C 3 Ω | v | p + k 1 k + α 1 ,
where C 3 = ( 3 · 2 k ) p α α + k 1 ( χ p ( p 1 ) p α ) p + k 1 α + k 1 μ p α α + k 1 . For p = α , we obtain
p ( p 1 ) Ω ( 1 + u ) p 2 H ( u ) u · v d x p ( p 1 ) χ Ω ln ( 1 + u ) | v | d x , p ( p 1 ) χ Ω ( 1 + u ) 1 e | v | d x , μ 3 · 2 k Ω ( 1 + u ) p + k 1 + C 4 Ω | v | e ( p + k 1 ) e ( p + k 1 ) 1 ,
where C 4 = ( 3 · 2 k ) 1 e ( p + k 1 ) 1 ( χ ( p 1 ) ) e ( p + k 1 ) e ( p + k 1 ) 1 μ 1 e ( p + k 1 ) 1 .
Denote ψ ( u ) = 0 u ( 1 + σ ) p 2 I ( σ ) d σ for all u 0 . We infer from (4) and p > β that
0 ψ ( u ) ξ p β ( 1 + u ) p β ,
for u 0 . This, together with Lemma 3 and β > 1 k , means that
p ( p 1 ) Ω ( 1 + u ) p 2 I ( u ) u · w d x = p ( p 1 ) Ω ψ ( u ) · w d x p ( p 1 ) w 0 L ( Ω ) Ω v ψ ( u ) d x + p ( p 1 ) C Ω ψ ( u ) d x ξ p ( p 1 ) p β w 0 L ( Ω ) Ω ( 1 + u ) p β v d x + ξ C p ( p 1 ) p β Ω ( 1 + u ) p β d x μ 3 · 2 k 1 Ω ( 1 + u ) p + k 1 d x + C 5 Ω v p + k 1 β + k 1 d x + C 6 ,
where
C 5 = ( 3 · 2 k ) p β β + k 1 ( ξ p ( p 1 ) p β w 0 L ( Ω ) ) p + k 1 β + k 1 μ p β β + k 1 , C 6 = ( 3 · 2 k ) p β β + k 1 ( ξ C p ( p 1 ) p β ) p + k 1 β + k 1 | Ω | μ p β β + k 1 .
For γ k + 1 e + 1 < p < α , we infer from (18), (24), (27) and (31) that
d d t Ω ( 1 + u ) p μ 2 k Ω ( 1 + u ) p + k 1 d x + 2 χ p ( p 1 ) | p α | Ω | v | n 2 d x + C 7 ,
where C 7 = C 5 K 0 p + k 1 β + k 1 + C 1 + C 2 + C 6 . Since
n 2 Ω ( 1 + u ) p d x μ 3 · 2 k 1 Ω ( 1 + u ) p + k 1 d x + C 8 ,
where C 8 = ( n 2 ) p + k 1 k 1 ( 3 · 2 k 1 ) p k 1 | Ω | μ p k 1 . Combining (32) with (33), we obtain
d d t Ω ( 1 + u ) p d x + n 2 Ω ( 1 + u ) p d x μ 3 · 2 k Ω ( 1 + u ) p + k 1 d x + 2 χ p ( p 1 ) | p α | Ω | v | n 2 d x + C 9 ,
where C 9 = C 7 + C 8 ; this, together with the variation-of-constants formula, shows that
Ω ( 1 + u ) p d x μ 3 · 2 k t 0 t Ω e n 2 ( t s ) ( 1 + u ) p + k 1 d x d s + 2 χ p ( p 1 ) | p α | t 0 t Ω e n 2 ( t s ) | v | n 2 d x d s + e n 2 ( t t 0 ) Ω ( 1 + u ( · , t 0 ) ) p d x + C 9 t 0 t e n 2 ( t s ) d s μ 3 · 2 k t 0 t Ω e n 2 ( t s ) ( 1 + u ) p + k 1 d x d s + 2 χ p ( p 1 ) | p α | t 0 t Ω e n 2 ( t s ) | v | n 2 d x d s + M 0 + C 9 ,
where M 0 = Ω ( 1 + u ( · , t 0 ) ) p d x is a positive constant. Since p > n γ 2 + 1 k , we have from Lemma 2 and (5) that
2 χ p ( p 1 ) | p α | t 0 t Ω e n 2 ( t s ) | v | n 2 d x d s 2 χ p ( p 1 ) C n | p α | t 0 t Ω e n 2 ( t s ) u n γ 2 d x d s + 2 χ p ( p 1 ) C n | p α | v ( · , t 0 ) W 2 , n 2 ( Ω ) n 2 μ 3 · 2 k t 0 t Ω e n 2 ( t s ) ( u + 1 ) p + k 1 d x d s + C 10 ,
where C n , C 10 is a positive constant related to n and independent of t 0 . From the combination of (35) and (36), we conclude that
Ω ( u + 1 ) p d x C 11 .
where C 11 = M 0 + C 9 + C 10 .
For p > α , we infer from (18), (24), (28) and (31) that
d d t Ω ( 1 + u ) p d x μ 3 · 2 k 1 Ω ( 1 + u ) p + k 1 d x + C 3 Ω | v | p + k 1 α + k 1 d x + C 12 .
where C 12 = C 5 K 0 p + k 1 β + k 1 + C 1 + C 6 . Define
m : = p + k 1 α + k 1 ,
we have from (38) that
d d t Ω ( 1 + u ) p d x + m Ω ( 1 + u ) p d x μ 3 · 2 k Ω ( 1 + u ) p + k 1 d x + C 3 Ω | v | m d x + C 13 ,
where C 13 = ( 3 · 2 k ) p k 1 m p + k 1 k 1 | Ω | μ p k 1 + C 12 . Recalling Lemma 2, it can be obtained from (39) that
Ω ( 1 + u ) p d x μ 3 · 2 k t 0 t Ω e m ( t s ) ( 1 + u ) p + k 1 d x d s + C 3 t 0 t Ω e m ( t s ) | v | m d x d s + e m ( t t 0 ) Ω ( 1 + u ( · , t 0 ) ) p d x + C 13 t 0 t e m ( t s ) d s μ 3 · 2 k t 0 t Ω e m ( t s ) ( 1 + u ) p + k 1 d x d s + C 3 C m t 0 t Ω e m ( t s ) ( 1 + u ) m γ d x d s + C 3 C m v ( · , t 0 ) W 2 , m ( Ω ) m + C 14 ,
where C 14 = M 0 + C 13 and C m is a positive constant related to m and independent of t 0 . Since α > r k + 1 e + 1 , m γ < p + k 1 ; we have from Young’s inequality that
C 3 C m t 0 t Ω e m ( t s ) ( 1 + u ) m γ d x d s μ 3 · 2 k t 0 t Ω e m ( t s ) ( 1 + u ) p + k 1 d x d s + C 15 ,
where C 15 = 1 m ( 3 · 2 k ) m γ p + k 1 m γ ( C 3 C m ) p + k 1 p + k 1 m γ | Ω | μ m γ p + k 1 m γ .
Inserting (41) into (40), we have
Ω ( u + 1 ) p d x C 16 ,
where C 16 = C 3 C m v ( · , t 0 ) W 2 , m ( Ω ) m + C 14 + C 15 .
For p = α , we infer from (18), (24), (29) and (31) that
d d t Ω ( 1 + u ) p d x μ 3 · 2 k 1 Ω ( 1 + u ) p + k 1 d x + C 4 Ω | v | e ( p + k 1 ) e ( p + k 1 ) 1 d x + C 17 ,
where C 17 = C 5 K 0 p + k 1 β + k 1 + C 1 + C 6 . Define
m ˜ : = e ( p + k 1 ) e ( p + k 1 ) 1 ,
Similar to (40), we have
Ω ( 1 + u ) p d x μ 3 · 2 k t 0 t Ω e m ˜ ( t s ) ( 1 + u ) p + k 1 d x d s + C 4 C m ˜ t 0 t Ω e m ˜ ( t s ) ( 1 + u ) m ˜ γ d x d s + C 4 C m ˜ v ( · , t 0 ) W 2 , m ˜ ( Ω ) m ˜ + C 18 ,
where C m ˜ , C 18 is a positive constant related to m ˜ and independent of t 0 .
Since α = p > r k + 1 e + 1 , m ˜ γ < p + k 1 ; we have from Young’s inequality that
C 4 C m ˜ t 0 t Ω e m ˜ ( t s ) ( 1 + u ) m ˜ γ d x d s μ 3 · 2 k t 0 t Ω e m ˜ ( t s ) ( 1 + u ) p + k 1 d x d s + C 19 ,
where C 19 = 1 m ˜ ( 3 · 2 k ) m ˜ γ p + k 1 m ˜ γ ( C 4 C m ˜ ) p + k 1 p + k 1 m ˜ γ | Ω | μ m ˜ γ p + k 1 m ˜ γ . Inserting (45) into (44), we have
Ω ( u + 1 ) p d x C 20 ,
where C 20 = C 4 C m ˜ v ( · , t 0 ) W 2 , m ˜ ( Ω ) m ˜ + C 18 + C 19 .
Case (ii). For p > α and α > γ k + 1 , define
m : = p + k 1 α + k 1 ,
we have from (40) that
Ω ( 1 + u ) p d x μ 3 · 2 k t 0 t Ω e m ( t s ) ( 1 + u ) p + k 1 d x d s + C 3 C m t 0 t Ω e m ( t s ) ( 1 + u ) m γ d x d s + C 3 C m v ( · , t 0 ) W 2 , m ( Ω ) m + C 21 .
Since α > r k + 1 , then m γ < p + k 1 . We infer from Young’s inequality and (47) that
Ω ( u + 1 ) p d x C 22 ,
where C 22 is a positive constant. This completes the proof of Lemma 5. □
Lemma 6.
Assume that D , H , I and g fulfill (2)–(5). Then,
(i) For 0 < γ 2 n , if α > γ k + 1 and β > 1 k , there exists a constant C > 0 such that v ( · , t ) W 1 , ( Ω ) C .
(ii) For 2 n < γ 1 , if α > γ k + 1 e + 1 and β > max { ( n γ 2 ) ( n γ + 2 k 2 ) 2 n k + 1 , ( n γ 2 ) ( γ + 1 e ) n k + 1 } or α > γ k + 1 and β > max { ( n γ 2 ) ( n γ + 2 k 2 ) 2 n k + 1 , ( n γ 2 ) ( α + k 1 ) n k + 1 } , there exists a constant C > 0 such that v ( · , t ) W 1 , ( Ω ) C .
Proof. 
Case (i). Since 0 < γ 2 n , we have
n γ 2 0 .
Lemma 4(ii) yields that
v ( · , t ) L s ( Ω ) C 23 for all t ( 0 , T ) ,
for any s 1 . Taking p 1 > max { n γ 2 , 1 , α , β } , this implies p 1 + k 1 β + k 1 > 1 , and so we obtain
v ( · , t ) L p 1 + k 1 β + k 1 ( Ω ) C 24 for all t ( 0 , T ) ,
which, along with Lemma 5(ii), we have for all t ( 0 , T )
u ( · , t ) L p 1 ( Ω ) C 25 .
Since p 1 > n γ 2 , we infer from Lemma 4(iii) that
v ( · , t ) L ( Ω ) C 26 for all t ( 0 , T ) .
By Lemma 5(ii), again, and letting p 2 > max { n γ , 1 , α , β } , one can find
u ( · , t ) L p 2 ( Ω ) C 27 for all t ( 0 , T ) .
From this, together with Lemma 4(iv), we obtain
v ( · , t ) L ( Ω ) C 28 for all t ( 0 , T ) .
This completes the proof of Case (i).
Case (ii). For 2 n < γ 1 . Since β > ( n γ 2 ) ( n γ + 2 k 2 ) 2 n k + 1 and β > ( n γ 2 ) ( γ + 1 e ) n k + 1 , we have
n γ 2 < n n r 2 ( β + k 1 ) + 1 k , γ k + 1 e + 1 < n n γ 2 ( β + k 1 ) + 1 k , β < n n r 2 ( β + k 1 ) + 1 k .
Taking max { n γ 2 , γ k + 1 e + 1 , β } < p 3 < n n r 2 ( β + k 1 ) + 1 k , then
p 3 + k 1 β + k 1 ( 1 , n n γ 2 ) .
By Lemma 4(ii), we obtain
v ( · , t ) L p 3 + k 1 β + k 1 ( Ω ) C 29 for all t ( 0 , T ) ,
from which, along with Lemma 5(i), we have
u ( · , t ) L p 3 ( Ω ) C 30 for all t ( 0 , T ) .
Since p 3 > n γ 2 , applying Lemma 4(iii), we obtain
v ( · , t ) L ( Ω ) C 31 for all t ( 0 , T ) .
By Lemma 5(i), again, and letting p 4 > max { n γ , γ k + 1 e + 1 , β } , one can find
u ( · , t ) L p 4 ( Ω ) C 32 for all t ( 0 , T ) .
From this, together with Lemma 4(iv), we obtain for all t ( 0 , T )
v ( · , t ) L ( Ω ) C 33 .
Similarly, we infer from β > max { ( n γ 2 ) ( n γ + 2 k 2 ) 2 n k + 1 , ( n γ 2 ) ( α + k 1 ) n k + 1 } that there exists a positive constant p 5 such that
max { n γ 2 , α , β } < p 5 < n n r 2 ( β + k 1 ) + 1 k ,
thus p 5 + k 1 β + k 1 ( 1 , n n γ 2 ) . Combining Lemmas 4(iii) and 5(ii), we have u ( · , t ) L p 5 ( Ω ) C 34 and v ( · , t ) L ( Ω ) C 35 . Using Lemmas 5(ii) and 4(iv), we deduce that v ( · , t ) L ( Ω ) C 36 . This completes the proof of Case (ii). □
Proof of Theorem 1.
From Lemma 6 and the well-known Moser iteration (Lemma 3.6, [49]), we obtain the boundedness of u L ( Ω ) . The proof of Theorem 1 is complete by Lemma 1. □

Author Contributions

Methodology, Z.J.; Validation, Z.J.; Writing—original draft, B.A.; Formal analysis, Z.J. All authors have read and agreed to the published version of the manuscript.

Funding

Project supported by the National Natural Science Foundation of China (Grant No. 12301251, 12271232); the Natural Science Foundation of Shandong Province, China (Grant No. ZR2021QA038); and the Scientific Research Foundation of Linyi University, China (Grant No. LYDX2020BS014).

Data Availability Statement

The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author/s.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Winkler, M. Does a ‘volume-filling effect’ always prevent chemotactic collapse? Math. Methods Appl. Sci. 2010, 33, 12–24. [Google Scholar]
  2. Tao, Y.; Winkler, M. Boundedness in a quasilinear parabolic-parabolic Keller-Segel system with subcritical sensitivity. J. Differ. Equ. 2012, 252, 692–715. [Google Scholar]
  3. Ishida, S.; Seki, K.; Yokota, T. Boundedness in quasilinear Keller-Segel systems of parabolic-parabolic type on non-convex bounded domains. J. Differ. Equ. 2014, 256, 2993–3010. [Google Scholar]
  4. CieśLak, T.; Stinner, C. New critical exponents in a fully parabolic quasilinear Keller-Segel and applications to volume filling models. J. Differ. Equ. 2015, 258, 2080–2113. [Google Scholar]
  5. Zheng, J. Boundedness of solutions to a quasilinear parabolic-parabolic Keller-Segel system with a logistic source. J. Math. Anal. Appl. 2015, 431, 867–888. [Google Scholar]
  6. Tao, X.; Zhou, A.; Ding, M. Boundedness of solutions to a quasilinear parabolic-parabolic chemotaxis model with nonlinear signal production. J. Math. Anal. Appl. 2019, 474, 733–747. [Google Scholar]
  7. Ding, M.; Wang, W.; Zhou, S.; Zheng, S. Asymptotic stability in a fully parabolic quasilinear chemotaxis model with general logistic source and signal production. J. Differ. Equ. 2020, 268, 6729–6777. [Google Scholar]
  8. CieśLak, T.; Stinner, C. Finite-time blowup and global-in-time unbounded solutions to a parabolic-parabolic quasilinear Keller-Segel system in higher dimensions. J. Differ. Equ. 2012, 252, 5832–5851. [Google Scholar]
  9. CieśLak, T.; Winkler, M. Finite-time blow-up in a quasilinear system of chemotaxis. Nonlinearity 2008, 21, 1057–1076. [Google Scholar]
  10. Jia, Z. Global boundedness of weak solutions for an attraction-repulsion chemotaxis system with p-Laplacian diffusion and nonlinear production. Discrete Contin. Dyn. Syst. Ser. B 2023, 28, 4847–4863. [Google Scholar]
  11. Wang, L.; Li, Y.; Mu, C. Boundedness in a parabolic-parabolic quasilinear chemotaxis system with logistic source. Discrete Contin. Dyn. Syst. Ser. A 2014, 34, 789–802. [Google Scholar]
  12. Wang, X.; Wang, Z.; Jia, Z. Global weak solutions for an attraction-repulsion chemotaxis system with p-Laplacian diffusion and logistic source. Acta Math. Sci. 2024, 44, 909–924. [Google Scholar]
  13. Winkler, M. Chemotaxis with logistic source: Very weak global solutions and their boundedness properties. J. Math. Anal. Appl. 2008, 348, 708–729. [Google Scholar]
  14. Winkler, M. Blow-up in a higher-dimensional chemotaxis system despite logistic growth restriction. J. Math. Anal. Appl. 2011, 384, 261–272. [Google Scholar]
  15. Zhuang, M.; Wang, W.; Zheng, S. Boundedness in a fully parabolic chemotaxis system with logistic-type source and nonlinear production. Nonlinear Anal. Real World Appl. 2019, 47, 473–483. [Google Scholar]
  16. Chen, T.; Li, F.; Yu, P. Nilpotent center conditions in cubic switching polynomial Linard systems by higher-order analysis. J. Differ. Equ. 2024, 379, 258–289. [Google Scholar]
  17. Ding, X.; Lu, J.; Chen, A. Lyapunov-based stability of time-triggered impulsive logical dynamic networks. Nonlinear Anal. Hybrid Syst. 2024, 51, 101417. [Google Scholar]
  18. He, X.; Qiu, J.; Li, X.; Cao, J. A brief survey on stability and stabilization of impulsive systems with delayed impulses. Discrete Contin. Dyn. Syst. S 2022, 15, 1797–1821. [Google Scholar]
  19. Jia, Z.; Yang, Z. Large time behavior to a chemotaxis-consumption model with singular sensitivity and logistic source. Math. Methods Appl. Sci. 2021, 44, 3630–3645. [Google Scholar]
  20. Jiang, C.; Zhang, F.; Li, T. Synchronization and antisynchronization of N-coupled fractional-order complex chaotic systems with ring connection. Math. Methods Appl. Sci. 2018, 41, 2625–2638. [Google Scholar]
  21. Lei, C.; Li, H.; Zhao, Y. Dynamical behavior of a reaction-diffusion SEIR epidemic model with mass action infection mechanism in a heterogeneous environment. Discrete Contin. Dyn. Syst. Ser. B 2024, 29, 3163–3198. [Google Scholar]
  22. Li, F.; Liu, Y.; Liu, Y.; Yu, P. Bi-center problem and bifurcation of limit cycles from nilpotent singular points in Z(2)-equivariant cubic vector fields. J. Differ. Equ. 2018, 265, 4965–4992. [Google Scholar]
  23. Li, F.; Liu, Y.; Liu, Y.; Yu, P. Complex isochronous centers and linearization transformations for cubic Z(2)-equivariant planar systems. J. Differ. Equ. 2020, 268, 3819–3847. [Google Scholar]
  24. Li, F.; Liu, Y.; Yu, P.; Wang, L. Complex integrability and linearizability of cubic Z2-equivariant systems with two 1: Q resonant singular points. J. Differ. Equ. 2021, 300, 786–813. [Google Scholar]
  25. Marciniak-Czochra, A.; Ptashnyk, M. Boundedness of solutions of a haptotaxis model. Math. Mod. Methods Appl. Sci. 2010, 20, 449–476. [Google Scholar]
  26. Mi, L. Blow-up rates of large solutions for infinity Laplace equations. Appl. Math. Comp. 2017, 298, 36–44. [Google Scholar]
  27. Qiu, J.; Yang, X. Convergence of the two-species vlasov-poisson system to the pressureless euler equations. Acta Appl. Math. 2016, 143, 179–187. [Google Scholar]
  28. Tong, X.; Jiang, H.; Chen, X.; Li, J.; Cao, Z. Deterministic and stochastic evolution of rumor propagation model with media coverage and classage-dependent education. Math. Methods Appl. Sci. 2023, 46, 7125–7139. [Google Scholar]
  29. Xu, M.; Liu, S.; Lou, Y. Persistence and extinction in the anti-symmetric Lotka-Volterra systems. J. Differ. Equ. 2024, 387, 299–323. [Google Scholar]
  30. Yan, D.; Pang, G.; Qiu, J.; Chen, X.; Zhang, A.; Liu, Y. Finite-time stability analysis of switched systems with actuator saturation based on event-triggered mechanism. Discrete Contin. Dyn. Syst. S 2023, 16, 1929–1943. [Google Scholar]
  31. Yang, M.; Fu, Z.; Sun, J. Existence and large time behavior to coupled chemotaxis-fluid equations in Besov-Morrey spaces. J. Differ. Equ. 2019, 266, 5867–5894. [Google Scholar]
  32. You, L.; Yang, X.; Wu, S.; Li, X. Finite-time stabilization for uncertain nonlinear systems with impulsive disturbance via aperiodic intermittent control. Appl. Math. Comp. 2023, 443, 127782. [Google Scholar]
  33. Zhang, D.; Chen, F. Global bifurcations and single-pulse homoclinic orbits of a plate subjected to the transverse and in-plane excitations. Math. Methods Appl. Sci. 2017, 40, 4338–4349. [Google Scholar]
  34. Zhang, X.; Liu, E.; Qiu, J.; Zhang, A.; Liu, Z. Output feedback finite-time stabilization of a class of large-scale high-order nonlinear stochastic feedforward systems. Discrete Contin. Dyn. Syst. S 2023, 16, 1892–1908. [Google Scholar]
  35. Chaplain, M.; Lolas, G. Mathematical modelling of cancer invasion of tissue: Dynamic heterogeneity. Netw. Heterogen. Media 2016, 1, 399–439. [Google Scholar]
  36. Tao, Y.; Wang, M. Global solution for a chemotactic-haptotactic model of cancer invasion. Nonlinearity 2008, 21, 2221–2238. [Google Scholar]
  37. Tao, Y. Global existence of classical solutions to a combined chemotaxis-haptotaxis model with logistic source. J. Math. Anal. Appl. 2009, 354, 60–69. [Google Scholar]
  38. Tao, Y. Boundedness in a two-dimensional chemotaxis-haptotaxis system. J. Donghua Univ. 2016, 70, 165–174. [Google Scholar]
  39. Cao, X. Boundedness in a three-dimensional chemotaxis-haptotaxis model. Z. Angew. Math. Phys. 2016, 67, 11. [Google Scholar]
  40. Tao, Y.; Winkler, M. Large time behavior in a multidimensional chemotaxis-hapotaxis model with slow signal diffusion. SIAM J. Math. Anal. 2015, 47, 4229–4250. [Google Scholar]
  41. Zheng, J.; Ke, Y. Large time behavior of solutions to a fully parabolic chemotaxis-haptotaxis model in N dimensions. J. Differ. Equ. 2019, 266, 1969–2018. [Google Scholar]
  42. Tao, Y.; Winkler, M. A chemotaxis-haptotaxis model: The roles of nonlinear diffusion and logistic source. SIAM J. Math. Anal. 2011, 43, 685–704. [Google Scholar]
  43. Li, Y.; Lankeit, J. Boundedness in a chemotaxis-haptotaxis model with nonlinear diffusion. Nonlinearity 2016, 29, 1564–1595. [Google Scholar]
  44. Wang, Y. Boundedness in the higher-dimensional chemotaxis-haptotaxis model with nonlinear diffusion. J. Differ. Equ. 2016, 260, 1975–1989. [Google Scholar]
  45. Wang, Y. Boundedness in a multi-dimensional chemotaxis-haptotaxis model with nonlinear diffusion. Appl. Math. Lett. 2016, 59, 122–126. [Google Scholar]
  46. Zheng, P.; Mu, C.; Song, X. On the boundedness and decay of solutions for a chemotaxis-haptotaxis system with nonlinear diffusion. Discrete Contin. Dyn. Syst. Ser. A 2016, 36, 1737–1757. [Google Scholar]
  47. Jin, C. Boundedness and global solvability to a chemotaxis-haptotaxis model with slow and fast diffusion. Discrete Contin. Dyn. Syst. Ser. B 2018, 23, 1675–1688. [Google Scholar]
  48. Liu, J.; Zheng, J.; Wang, Y. Boundedness in a quasilinear chemotaxis-haptotaxis system with logistic source. Z. Angew. Math. Phys. 2016, 67, 21. [Google Scholar]
  49. Xu, H.; Zhang, L.; Jin, C. Global solvability and large time behavior to a chemotaxis-haptotaxis model with nonlinear diffusion. Nonlinear Anal. Real World Appl. 2019, 46, 238–256. [Google Scholar]
  50. Jia, Z.; Yang, Z. Global boundedness to a chemotaxis-haptotaxis model with nonlinear diffusion. Appl. Math. Lett. 2020, 103, 106192. [Google Scholar]
  51. Tao, Y.; Winkler, M. Energy-type estimates and global solvability in a two-dimensional chemotaxis-hapotaxis model with remodeling of non-diffusible attractant. J. Differ. Equ. 2014, 257, 784–815. [Google Scholar]
  52. Jin, C. Global classical solution and boundedness to a chemotaxis-haptotaxis model with re-establishment mechanisms. Bull. Lond. Math. Soc. 2018, 50, 598–618. [Google Scholar]
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Ai, B.; Jia, Z. The Global Existence and Boundedness of Solutions to a Chemotaxis–Haptotaxis Model with Nonlinear Diffusion and Signal Production. Mathematics 2024, 12, 2577. https://doi.org/10.3390/math12162577

AMA Style

Ai B, Jia Z. The Global Existence and Boundedness of Solutions to a Chemotaxis–Haptotaxis Model with Nonlinear Diffusion and Signal Production. Mathematics. 2024; 12(16):2577. https://doi.org/10.3390/math12162577

Chicago/Turabian Style

Ai, Beibei, and Zhe Jia. 2024. "The Global Existence and Boundedness of Solutions to a Chemotaxis–Haptotaxis Model with Nonlinear Diffusion and Signal Production" Mathematics 12, no. 16: 2577. https://doi.org/10.3390/math12162577

APA Style

Ai, B., & Jia, Z. (2024). The Global Existence and Boundedness of Solutions to a Chemotaxis–Haptotaxis Model with Nonlinear Diffusion and Signal Production. Mathematics, 12(16), 2577. https://doi.org/10.3390/math12162577

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop