Lan Yuqing, Zhao Tong. Evaluate interoperability of foundational software platform by Bayesian networks[J]. Journal of Beijing University of Aeronautics and Astronautics, 2009, 35(9): 1148-1151. (in Chinese)
Citation: XIE Ronghua, FAN Weihua, CHEN Qingweiet al. Distributed H control for hierarchical networked control system[J]. Journal of Beijing University of Aeronautics and Astronautics, 2017, 43(12): 2392-2399. doi: 10.13700/j.bh.1001-5965.2016.0931(in Chinese)

Distributed H control for hierarchical networked control system

doi: 10.13700/j.bh.1001-5965.2016.0931
Funds:

National Natural Science Foundation of China 61673219

Jiangsu Overseas Research & Training Program for University Prominent Young & Middle-aged Teachers and Presidents 

Jiangsu Foresight Joint Research Project BY2016004-07

Jiangsu Six Talents Peaks Project of Province under Grant XNYQC-CXTD-001

Tianjin Major Projects of Science and Technology under Grant 15ZXZNGX00250

More Information
  • Corresponding author: FAN Weihua, E-mail:fanweihua@njust.edu.cn
  • Received Date: 09 Dec 2016
  • Accepted Date: 10 Mar 2017
  • Publish Date: 20 Dec 2017
  • Considering the centralized control mode cannot be used in hierarchical networked control system which is widely applied in the fields of modern industry, aerospace, etc., the distributed H control for the hierarchical networked control system is studied. First, considering the network induced delay, data packet loss and partial information available, a distributed control law for hierarchical networked control system is proposed. And the closed-loop networked control system is modeled as a switched discrete system with distributed time varying delay. Second, based on Lyapunov-Krasovskii functional method, a sufficient condition for system stability and to satisfy the requirement of given H performance index is deduced, which is less conservative and depends on the upper bound of the delay. Using cone complement linearization method, the controller design is converted to an optimal problem with linear matrix inequalities, and an iterative approach for controller design is given. Finally, a simulation example is used to validate the effectiveness of the proposed method.

     

  • [1]
    ZHANG W.Stability analysis of networked control systems[D].Cleveland:Case Western Reserve University, 2001.
    [2]
    ZHANG L X, GAO H J, KYANAK O.Network-induced constraints in networked control systems-A survey[J].IEEE Transactions on Industrial Informatics, 2012, 9(1):403-416.
    [3]
    XIA Y Q, LIU X P, LIU G P, et al.Stabilization analysis and implementation for MIMO NCS with time-varying delays[J].International Journal of Adaptive Control and Signal Process, 2011, 25(7):639-652. doi: 10.1002/acs.v25.7
    [4]
    OKAJIMA H, SAWADA K, MATSUNAGA N, et al.Dynamic quantizer design for MIMO systems based on communication rate constraint[J].Electronics and Communications in Japan, 2013, 96(5):28-36. doi: 10.1002/ecj.v96.5
    [5]
    GUAN Z H, ZHAN X S, FENG G.Optimal tracking performance of MIMO discrete-time systems with communication constraints[J].International Journal of Robust and Nonlinear Control, 2012, 22(13):1429-1439. doi: 10.1002/rnc.v22.13
    [6]
    LI J N, ZHANG Q L, YU H B, et al.Real-time guaranteed cost control of MIMO networked control systems with packet disordering[J].Journal of Process Control, 2011, 21(6):967-975. doi: 10.1016/j.jprocont.2010.10.011
    [7]
    DU D J, FEI M R, JIA T G.Modelling and stability analysis of MIMO networked control systems with multi-channel random packet losses[J].Transactions of the Institute of Measurement and Control, 2011, 35(1):66-74.
    [8]
    YANG X, WANG J Z.Distributed robust H consensus control of multi-agent systems with communication errors using dynamic output feedback protocol[J/OL].Mathematical Problems in Engineering, 2013:979087[2016-12-06].http://dx.doi.org/10.1155/2013/979087.
    [9]
    GAO Y P, MA J W, ZUO M, et al.Consensus of discrete-time second-order agents with time-varying topology and time-varying delays[J].Journal of the Franklin Institute, 2012, 349(8):2598-2608. doi: 10.1016/j.jfranklin.2012.06.009
    [10]
    LI Z K, GUAN Z S, XIE L H, et al.Distributed robust control of linear multi-agent systems with parameter uncertainties[J].International Journal of Robust and Nonlinear Control, 2012, 85(8):1039-1050.
    [11]
    ANDREASSON M, DIMAEOFONAS D V, SANDVERG H, et al.Distributed control of networked dynamical systems:Static feedback, integral action and consensus[J].IEEE Transactions on Automatic Control, 2014, 59(7):1750-1764. doi: 10.1109/TAC.2014.2309281
    [12]
    HIRCHE S, MATIAKIS T, BUSS M.A distributed controller approach for delay-independent stability of networked control systems[J].Automatica, 2009, 45(8):1828-1836. doi: 10.1016/j.automatica.2009.04.016
    [13]
    ZHENG Y, LI S L, QIU H.Networked coordination-based distributed model predictive control for large-scale system[J].IEEE Transaction on Control Systems Technology, 2013, 21(3):991-998. doi: 10.1109/TCST.2012.2196280
    [14]
    LIU D, HAO F.Decentralized event-triggered control strategy in distributed networked systems with delays[J].International Journal of Control, Automation, and Systems, 2013, 11(1):33-40. doi: 10.1007/s12555-012-0094-1
    [15]
    GUINALDO M, DIMAROGONAS D V, JOHANSSON K H, et al.Distributed event-based control strategies for interconnected linear systems[J].IET Control Theory and Applications, 2013, 7(6):877-886. doi: 10.1049/iet-cta.2012.0525
    [16]
    LATRACH C, KCHAOU M, RACHI A, et al.Decentralized networked control system design using Takagi-Sugeno (TS) fuzzy approach[J].International Journal of Automation and Computing, 2015, 12(2):125-133. doi: 10.1007/s11633-015-0879-9
    [17]
    GHAOUI L E, QUSTRY F, AITRAMI M.A cone complementarity linearization algorithm for static output-feedback and related problems[J].IEEE Transaction on Automatic Control, 1997, 42(8):1171-1176. doi: 10.1109/9.618250
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