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Huang C, Lu J, Zhai G, Cao J, Lu G, Perc M. Stability and Stabilization in Probability of Probabilistic Boolean Networks. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2021; 32:241-251. [PMID: 32217481 DOI: 10.1109/tnnls.2020.2978345] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
This article studies the stability in probability of probabilistic Boolean networks and stabilization in the probability of probabilistic Boolean control networks. To simulate more realistic cellular systems, the probability of stability/stabilization is not required to be a strict one. In this situation, the target state is indefinite to have a probability of transferring to itself. Thus, it is a challenging extension of the traditional probability-one problem, in which the self-transfer probability of the target state must be one. Some necessary and sufficient conditions are proposed via the semitensor product of matrices. Illustrative examples are also given to show the effectiveness of the derived results.
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Zhou R, Guo Y, Wu Y, Gui W. Asymptotical Feedback Set Stabilization of Probabilistic Boolean Control Networks. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2020; 31:4524-4537. [PMID: 31899440 DOI: 10.1109/tnnls.2019.2955974] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
In this article, we investigate the asymptotical feedback set stabilization in distribution of probabilistic Boolean control networks (PBCNs). We prove that a PBCN is asymptotically feedback stabilizable to a given subset if and only if (iff) it constitutes asymptotically feedback stabilizable to the largest control-invariant subset (LCIS) contained in this subset. We proposed an algorithm to calculate the LCIS contained in any given subset with the necessary and sufficient condition for asymptotical set stabilizability in terms of obtaining the reachability matrix. In addition, we propose a method to design stabilizing feedback based on a state-space partition. Finally, the results were applied to solve asymptotical feedback output tracking and asymptotical feedback synchronization of PBCNs. Examples were detailed to demonstrate the feasibility of the proposed method and results.
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Distributed Pinning Impulsive Control for Inner–Outer Synchronization of Dynamical Networks on Time Scales. Neural Process Lett 2020. [DOI: 10.1007/s11063-020-10204-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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Guo Y, Li Q, Gui W. Optimal State Estimation of Boolean Control Networks With Stochastic Disturbances. IEEE TRANSACTIONS ON CYBERNETICS 2020; 50:1355-1359. [PMID: 30575558 DOI: 10.1109/tcyb.2018.2885124] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
This paper presents an investigation of the optimal estimation of state for Boolean control networks subject to stochastic disturbances. The disturbances are modeled as independently and identically distributed processes that are assumed to be both mutually independent and independent of the current and the historical states. An iterative algorithm is proposed to calculate the conditional probability distribution of the state given the output measurements. This algorithm is applied to the problems of minimum mismatching estimation and maximum posterior estimation of the state. An example is provided to illustrate the proposed results.
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Chen H, Liang J, Lu J, Qiu J. Synchronization for the Realization-Dependent Probabilistic Boolean Networks. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2018; 29:819-831. [PMID: 28129189 DOI: 10.1109/tnnls.2017.2647989] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
This paper investigates the synchronization problem for the realization-dependent probabilistic Boolean networks (PBNs) coupled unidirectionally in the drive-response configuration. The realization of the response PBN is assumed to be uniquely determined by the realization signal generated by the drive PBN at each discrete time instant. First, the drive-response PBNs are expressed in their algebraic forms based on the semitensor product method, and then, a necessary and sufficient condition is presented for the synchronization of the PBNs. Second, by resorting to a newly defined matrix operator, the reachable set from any initial state is expressed by a column vector. Consequently, an easily computable algebraic criterion is derived assuring the synchronization of the drive-response PBNs. Finally, three illustrative examples are employed to demonstrate the applicability and usefulness of the developed theoretical results.
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Lu X, Zhang X, Liu Q. Finite-time synchronization of nonlinear complex dynamical networks on time scales via pinning impulsive control. Neurocomputing 2018. [DOI: 10.1016/j.neucom.2017.10.033] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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Sun L, Lu J, Liu Y, Huang T, Alsaadi FE, Hayat T. Variable structure controller design for Boolean networks. Neural Netw 2017; 97:107-115. [PMID: 29096199 DOI: 10.1016/j.neunet.2017.09.012] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2017] [Revised: 07/08/2017] [Accepted: 09/26/2017] [Indexed: 11/19/2022]
Abstract
The paper investigates the variable structure control for stabilization of Boolean networks (BNs). The design of variable structure control consists of two steps: determine a switching condition and determine a control law. We first provide a method to choose states from the reaching mode. Using this method, we can guarantee that the number of nodes which should be controlled is minimized. According to the selected states, we determine the switching condition to guarantee that the time of global stabilization in the BN is the shortest. A control law is then determined to ensure that all selected states can enter into the sliding mode, such that any initial state can arrive in the steady-state mode. Some examples are provided to illustrate the theoretical results.
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Affiliation(s)
- Liangjie Sun
- School of Mathematics, Southeast University, Nanjing 210096, China
| | - Jianquan Lu
- School of Mathematics, Southeast University, Nanjing 210096, China; Department of Mathematics, King Abdulaziz University, Jeddah 21589, Saudi Arabia.
| | - Yang Liu
- College of Mathematics, Physics and Information Engineering, Zhejiang Normal University, Jinhua 321004, China; School of Mathematics, Southeast University, Nanjing 210096, China
| | | | - Fuad E Alsaadi
- Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia
| | - Tasawar Hayat
- Department of Mathematics, King Abdulaziz University, Jeddah 21589, Saudi Arabia; Department of Mathematics, Quaid-I-Azam University, Islamabad, Pakistan
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Zhong J, Lu J, Huang T, Ho DWC. Controllability and Synchronization Analysis of Identical-Hierarchy Mixed-Valued Logical Control Networks. IEEE TRANSACTIONS ON CYBERNETICS 2017; 47:3482-3493. [PMID: 27323388 DOI: 10.1109/tcyb.2016.2560240] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
This paper investigates the controllability and synchronization problems for identical-hierarchy mixed-valued logical control networks. The logical network considered is hierarchical, and Boolean network is a special case of logical network. Here, identical-hierarchy means that there are identical number of nodes in each layer of logical network and corresponding nodes have the same dimension for any two layers of logical networks. Meanwhile, in each layer of logical networks, the dimensions of nodes are distinct, and it is called a mixed-valued logical network. First, the controllability problem is investigated and two notions of controllability are presented, i.e., group-controllability and simultaneously-controllability. By resorting to Perron-Frobenius theorem, some necessary and sufficient criteria are obtained to guarantee group-controllability and simultaneously-controllability, respectively. Second, based on the algebraic representation of the studied model, synchronization problems are analytically discussed for two types of controls, i.e., free control sequences and state-output feedback control. Finally, two numerical examples are presented to show the validness of our main results.
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Wu Y, Xu J, Sun XM, Wang W. Observability of Boolean multiplex control networks. Sci Rep 2017; 7:46495. [PMID: 28452370 PMCID: PMC5408230 DOI: 10.1038/srep46495] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2016] [Accepted: 03/17/2017] [Indexed: 11/09/2022] Open
Abstract
Boolean multiplex (multilevel) networks (BMNs) are currently receiving considerable attention as theoretical arguments for modeling of biological systems and system level analysis. Studying control-related problems in BMNs may not only provide new views into the intrinsic control in complex biological systems, but also enable us to develop a method for manipulating biological systems using exogenous inputs. In this article, the observability of the Boolean multiplex control networks (BMCNs) are studied. First, the dynamical model and structure of BMCNs with control inputs and outputs are constructed. By using of Semi-Tensor Product (STP) approach, the logical dynamics of BMCNs is converted into an equivalent algebraic representation. Then, the observability of the BMCNs with two different kinds of control inputs is investigated by giving necessary and sufficient conditions. Finally, examples are given to illustrate the efficiency of the obtained theoretical results.
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Affiliation(s)
- Yuhu Wu
- School of Control Science and Engineering, Dalian University of Technology, Dalian 116024, P.R. China.,School of Control Science and Engineering, Dalian University of Technology, Dalian 116024, P.R. China
| | - Jingxue Xu
- School of Control Science and Engineering, Dalian University of Technology, Dalian 116024, P.R. China.,School of Control Science and Engineering, Dalian University of Technology, Dalian 116024, P.R. China
| | - Xi-Ming Sun
- School of Control Science and Engineering, Dalian University of Technology, Dalian 116024, P.R. China.,Key Laboratory of Ocean Energy Utilization and Energy Conservation of Ministry of Education, Dalian University of Technology, 116024, Dalian, China.,School of Control Science and Engineering, Dalian University of Technology, Dalian 116024, P.R. China
| | - Wei Wang
- School of Control Science and Engineering, Dalian University of Technology, Dalian 116024, P.R. China.,School of Control Science and Engineering, Dalian University of Technology, Dalian 116024, P.R. China
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Optimization-Based Approaches to Control of Probabilistic Boolean Networks. ALGORITHMS 2017. [DOI: 10.3390/a10010031] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Chen H, Liang J, Lu J. Partial Synchronization of Interconnected Boolean Networks. IEEE TRANSACTIONS ON CYBERNETICS 2017; 47:258-266. [PMID: 26780825 DOI: 10.1109/tcyb.2015.2513068] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
This paper addresses the partial synchronization problem for the interconnected Boolean networks (BNs) via the semi-tensor product (STP) of matrices. First, based on an algebraic state space representation of BNs, a necessary and sufficient criterion is presented to ensure the partial synchronization of the interconnected BNs. Second, by defining an induced digraph of the partial synchronized states set, an equivalent graphical description for the partial synchronization of the interconnected BNs is established. Consequently, the second partial synchronization criterion is derived in terms of adjacency matrix of the induced digraph. Finally, two examples (including an epigenetic model) are provided to illustrate the efficiency of the obtained results.
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Liu Y, Cao J, Sun L, Lu J. Sampled-Data State Feedback Stabilization of Boolean Control Networks. Neural Comput 2016; 28:778-99. [DOI: 10.1162/neco_a_00819] [Citation(s) in RCA: 58] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
In this letter, we investigate the sampled-data state feedback control (SDSFC) problem of Boolean control networks (BCNs). Some necessary and sufficient conditions are obtained for the global stabilization of BCNs by SDSFC. Different from conventional state feedback controls, new phenomena observed the study of SDSFC. Based on the controllability matrix, we derive some necessary and sufficient conditions under which the trajectories of BCNs can be stabilized to a fixed point by piecewise constant control (PCC). It is proved that the global stabilization of BCNs under SDSFC is equivalent to that by PCC. Moreover, algorithms are given to construct the sampled-data state feedback controllers. Numerical examples are given to illustrate the efficiency of the obtained results.
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Affiliation(s)
- Yang Liu
- Department of Mathematics, Southeast University, Nanjing 210096, China, and College of Mathematics, Physics and Information Engineering, Zhejiang Normal University, Jinhua 321004, China
| | - Jinde Cao
- Research Center for Complex Systems and Network Sciences, Department of Mathematics, Southeast University, Nanjing 210096, China
| | - Liangjie Sun
- Department of Mathematics, Southeast University, Nanjing 210096, China, and College of Mathematics, Physics and Information Engineering, Zhejiang Normal University, Jinhua 321004, China
| | - Jianquan Lu
- Department of Mathematics, Southeast University, Nanjing 210096, China
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Zhong J, Lu J, Huang C, Li L, Cao J. Finding graph minimum stable set and core via semi-tensor product approach. Neurocomputing 2016. [DOI: 10.1016/j.neucom.2015.09.073] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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