Output tracking control of Boolean control networks with impulsive effects

Xu, Xiaobin; Li, Haitao; Li, Yalu; Alsaadi, Fuad E.

doi:10.1002/mma.4685

Cited by 52 publications

(22 citation statements)

References 38 publications

(75 reference statements)

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“…The main results show the effectiveness via an illustrative example about the obtained new results. For the future works, we can extend the results to the theories of evolutionary game and impulse control, see details in previous studies …”

Section: Resultsmentioning

confidence: 93%

Stability analysis of activation‐inhibition Boolean networks with stochastic function structures

Zhao

Liang

2020

Math Methods in App Sciences

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This paper analyzes the stability of activation‐inhibition Boolean networks with stochastic function structures. First, the activation‐inhibition Boolean networks with stochastic function structures are converted to the form of logical networks by the method of semitensor product of matrices. Second, based on the obtained algebraic forms, we use matrices to denote the index set of possible logical operators and transition probabilities for activation‐inhibition Boolean networks. Third, equivalence criterions are presented for the stabilities analysis of activation‐inhibition Boolean networks with stochastic function structures. Finally, an example is given to verify the validity of the results.

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Section: Resultsmentioning

confidence: 93%

Stability analysis of activation‐inhibition Boolean networks with stochastic function structures

Zhao

Liang

2020

Math Methods in App Sciences

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“…Although [43] and this article investigate the output tracking problem of BCNs-IE, there are some differences between these two papers. From Theorems 3.7 and 3.8 of [43], the corresponding results hold under the assumption that is an L 1 -invariant set and anL 2 -invariant set. However, Theorem 1 of this article holds without any preconditions.…”

Section: B Output Tracking Of Bcns-iementioning

confidence: 99%

“…In biological networks, to describe the dynamic process of sudden changes of states, BCNs with impulsive effects (BCNs-IE) were discussed firstly in [36]. Many related problems about BCNs-IE are solved, such as control problems [37]- [39], stability and stabilization [40]- [42], output tracking [43] and so on. Although the output tracking problem of BCNs-IE has been addressed in [43], stable complex attractors were not considered to deal with this problem, and the corresponding controller was not designed.…”

Section: Introductionmentioning

confidence: 99%

“…Many related problems about BCNs-IE are solved, such as control problems [37]- [39], stability and stabilization [40]- [42], output tracking [43] and so on. Although the output tracking problem of BCNs-IE has been addressed in [43], stable complex attractors were not considered to deal with this problem, and the corresponding controller was not designed. Therefore, this article re-discusses the output tracking problem of BCNs-IE on the basis of stable complex attractors.…”

Section: Introductionmentioning

confidence: 99%

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Output Tracking of Boolean Control Networks With Impulsive Effects

Feng

2020

IEEE Access

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In this article, the output tracking of Boolean control networks with impulsive effects (BCNs-IE) is discussed. Based on structure matrices of BCNs-IE and controllability matrices with respect to state subsets, stable complex attractors are studied. By constructing an auxiliary BCN-IE and using stable complex attractors, a necessary and sufficient condition for the output tracking problem is proposed. In addition, an algorithm to design state feedback controllers for the output tracking problem is provided. Moreover, an example is given to show the validity of the obtained results. INDEX TERMS Boolean control network, impulsive effect, output tracking, stable complex attractor, state feedback controller.

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“…Especially, considering the sudden changes in gene regulation, the impulsive effect on genetic regulatory networks attracts many scholars' interest [40], [56]. It is noted that the ASSR method was also applied to Boolean networks with impulsive effects [5], [49]- [51]. Li et al [21] firstly introduced impulsive effects into Boolean networks.…”

Section: Introductionmentioning

confidence: 99%

Finite-Time Controllability and Set Controllability of Impulsive Probabilistic Boolean Control Networks

Wang

Liu

2020

IEEE Access

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This paper addresses the finite-time controllability and set controllability of impulsive probabilistic Boolean control networks (IPBCNs). Firstly, using the algebraic state space representation (ASSR) method, the transition probability matrix of IPBCNs is established. Secondly, a kind of finite step reachability matrix with probability one is constructed, based on which, several effective criteria are proposed for the finite-time controllability with probability one of IPBCNs. Thirdly, a necessary and sufficient condition is presented for the finite-time set controllability with probability one of IPBCNs by constructing the set controllability probability distribution vector. Finally, the obtained results are extended to switching topology case.

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Output tracking control of Boolean control networks with impulsive effects

Cited by 52 publications

References 38 publications

Stability analysis of activation‐inhibition Boolean networks with stochastic function structures

Stability analysis of activation‐inhibition Boolean networks with stochastic function structures

Output Tracking of Boolean Control Networks With Impulsive Effects

Finite-Time Controllability and Set Controllability of Impulsive Probabilistic Boolean Control Networks

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