Recent progress in networked control systems — A survey

  • Yuan-Qing Xia
  • Yu-Long Gao
  • Li-Ping Yan
  • Meng-Yin Fu
Survey Paper

Abstract

For the past decades, networked control systems (NCSs), as an interdisciplinary subject, have been one of the main research highlights and many fruitful results from different aspects have been achieved. With these growing research trends, it is significant to consolidate the latest knowledge and information to keep up with the research needs. In this paper, the results of different aspects of NCSs, such as quantization, estimation, fault detection and networked predictive control, are summarized. In addition, with the development of cloud technique, cloud control systems are proposed for the further development of NCSs.

Keywords

Networked control systems quantization filter data fusion fault detection networked predictive control cloud control systems 

References

  1. [1]
    A. Onat, T. Naskali, E. Parlakay, O. Mutluer. Control over imperfect networks: Model-based predictive networked control systems. IEEE Transactions on Industrial Electronics, vol. 58, no. 3, pp. 905–913, 2011.CrossRefGoogle Scholar
  2. [2]
    Y. Ge, Q. G. Chen, M. Jiang, Y. Q. Huang. Modeling of random delays in networked control systems. Journal of Control Science and Engineering, vol. 2013, Article number 383415, 2013.Google Scholar
  3. [3]
    L. X. Zhang, H. J. Gao, O. Kaynak. Network-induced constraints in networked control systems-A survey. IEEE Transactions on Industrial Informatics, vol. 9, no. 1, pp. 403–416, 2013.CrossRefGoogle Scholar
  4. [4]
    D. F. Delchamps. Stabilizing a linear system with quantized state feedback. IEEE Transactions on Automatic Control, vol. 35, no. 8, pp. 916–924, 1990.MathSciNetMATHCrossRefGoogle Scholar
  5. [5]
    L. Bao, M. Skoglund, K. H. Johansson. Encoder-decoder design for event-triggered feedback control over bandlimited channels. In Proceedings of the American Control Conference, IEEE, Minneapolis, USA, pp. 4183–4188, 2006.Google Scholar
  6. [6]
    S. L. Hu, D. Yue. Event-triggered control design of linear networked systems with quantizations. ISA Transactions, vol. 51, no. 1, pp. 153–162, 2012.CrossRefGoogle Scholar
  7. [7]
    E. Garcia, P. J. Antsaklis. Model-based event-triggered control for systems with quantization and time-varying network delays. IEEE Transactions on Automatic Control, vol. 58, no. 2, pp. 422–434, 2013.MathSciNetCrossRefGoogle Scholar
  8. [8]
    L. C. Li, X. F. Wang, M. Lemmon. Stabilizing bit-rates in quantized event triggered control systems. In Proceedings of the 15th ACM International Conference on Hybrid Systems: Computation and Control, ACM, Beijing, China, pp. 245–254, 2012.Google Scholar
  9. [9]
    N. Elia, S. K. Mitter. Stabilization of linear systems with limited information. IEEE Transactions on Automatic Control, vol. 46, no. 9, pp. 1384–1400, 2001.MathSciNetMATHCrossRefGoogle Scholar
  10. [10]
    M. Y. Fu, L. H. Xie. The sector bound approach to quantized feedback control. IEEE Transactions on Automatic Control, vol. 50, no. 11, pp. 1698–1711, 2005.MathSciNetCrossRefGoogle Scholar
  11. [11]
    H. Ishii, T. Başar. Remote control of LTI systems over networks with state quantization. Systems & Control Letters, vol. 54, no. 1, pp. 15–31, 2005.MathSciNetMATHCrossRefGoogle Scholar
  12. [12]
    T. Hayakawa, H. Ishii, K. Tsumura. Adaptive quantized control for linear uncertain discrete-time systems. Automatica, vol. 45, no. 3, pp. 692–700, 2009.MathSciNetMATHCrossRefGoogle Scholar
  13. [13]
    T. Hayakawa, H. Ishii, K. Tsumura. Adaptive quantized control for nonlinear uncertain systems. Systems & Control Letters, vol. 58, no. 9, pp. 625–632, 2009.MathSciNetMATHCrossRefGoogle Scholar
  14. [14]
    K. Y. You, W. Z. Su, M. Y. Fu, L. H. Xie. Attainability of the minimum data rate for stabilization of linear systems via logarithmic quantization. Automatica, vol. 47, no. 1, pp. 170–176, 2011.MathSciNetMATHCrossRefGoogle Scholar
  15. [15]
    B. Zhou, G. R. Duan, J. Lam. On the absolute stability approach to quantized feedback control. Automatica, vol. 46, no. 2, pp. 337–346, 2010.MathSciNetMATHCrossRefGoogle Scholar
  16. [16]
    D. Yue, C. Peng, G. Y. Tang. Guaranteed cost control of linear systems over networks with state and input quantisations. IET Control Theory & Applications, vol. 153, no. 6, pp. 658–664, 2006.MathSciNetCrossRefGoogle Scholar
  17. [17]
    C. Z. Zhang, G. Feng, H. J. Gao, J. B. Qiu. Generalized H2 filter design for T-S fuzzy systems with quantization and packet loss. In Proceedings of IEEE Symposium on Computational Intelligence in Control and Automation, IEEE, Paris, France, pp. 52–59, 2011.CrossRefGoogle Scholar
  18. [18]
    C. Z. Zhang, G. Feng, H. J. Gao, J. B. Qiu. H filtering for nonlinear discrete-time systems subject to quantization and packet dropouts. IEEE Transactions on Fuzzy Systems, vol. 19, no. 2, pp. 353–365, 2011.CrossRefGoogle Scholar
  19. [19]
    L. Li, Y. Q. Xia, J. Q. Qiu, H. J. Yang. Robust H networked control for discrete-time fuzzy systems with state quantisation. International Journal of Systems Science, vol. 43, no. 12, pp. 2249–2260, 2012.MathSciNetMATHCrossRefGoogle Scholar
  20. [20]
    J. J. Yan, Y. Q. Xia. Stabilisation of non-linear continuous system with input quantisation and packet dropout. IET Control Theory & Applications, vol. 6, no. 15, pp. 2426–2433, 2012.MathSciNetCrossRefGoogle Scholar
  21. [21]
    Y. Q. Xia, J. J. Yan, P. Shi, M. Y. Fu. Stability analysis of discrete-time systems with quantized feedback and measurements. IEEE Transactions on Industrial Informatics, vol. 9, no. 1, pp. 313–324, 2013.CrossRefGoogle Scholar
  22. [22]
    R. W. Brockett, D. Liberzon. Quantized feedback stabilization of linear systems. IEEE Transactions on Automatic Control, vol. 45, no. 7, pp. 1279–1289, 2000.MathSciNetMATHCrossRefGoogle Scholar
  23. [23]
    D. Liberzon. Hybrid feedback stabilization of systems with quantized signals. Automatica, vol. 39, no. 9, pp. 1543–1554, 2003.MathSciNetMATHCrossRefGoogle Scholar
  24. [24]
    F. Fagnani, S. Zampieri. Quantized stabilization of linear systems: Complexity versus performance. IEEE Transactions on Automatic Control, vol. 49, no. 9, pp. 1534–1548, 2004.MathSciNetCrossRefGoogle Scholar
  25. [25]
    F. Bullo, D. Liberzon. Quantized control via locational optimization. IEEE Transactions on Automatic Control, vol. 51, no. 1, pp. 2–13, 2006.MathSciNetCrossRefGoogle Scholar
  26. [26]
    D. Liberzon, D. Nesic. Input-to-state stabilization of linear systems with quantized state measurements. IEEE Transactions on Automatic Control, vol. 52, no. 5, pp. 767–781, 2007.MathSciNetCrossRefGoogle Scholar
  27. [27]
    D. Nešić, D. Liberzon. A unified framework for design and analysis of networked and quantized control systems. IEEE Transactions on Automatic Control, vol. 54, no. 4, pp. 732–747, 2009.MathSciNetCrossRefGoogle Scholar
  28. [28]
    K. Y. You, L. H. Xie. Minimum data rate for mean square stabilization of discrete LTI systems over lossy channels. IEEE Transactions on Automatic Control, vol. 55, no. 10, pp. 2373–2378, 2010.MathSciNetCrossRefGoogle Scholar
  29. [29]
    K. Y. You, L. H. Xie. Minimum data rate for mean square stabilizability of linear systems with Markovian packet losses. IEEE Transactions on Automatic Control, vol. 56, no. 4, pp. 772–785, 2011.MathSciNetCrossRefGoogle Scholar
  30. [30]
    E. Tian, D. Yue, X. Zhao. Quantised control design for networked control systems. IET Control Theory & Applications, vol. 1, no. 6, pp. 1693–1699, 2007.CrossRefGoogle Scholar
  31. [31]
    C. De Persis. On stabilization of nonlinear systems under data rate constraints using output measurements. International Journal of Robust and Nonlinear Control, vol. 16, no. 6, pp. 315–332, 2006.MathSciNetMATHCrossRefGoogle Scholar
  32. [32]
    C. De Persis. Robust stabilization of nonlinear systems by quantized and ternary control. Systems & Control Letters, vol. 58, no. 8, pp. 602–608, 2009.MathSciNetMATHCrossRefGoogle Scholar
  33. [33]
    J. J. Yan, Y. Q. Xia, B. Liu, M. Y. Fu. Stabilisation of quantised linear systems with packet dropout. IET Control Theory & Applications, vol. 5, no. 8, pp. 982–989, 2011.MathSciNetCrossRefGoogle Scholar
  34. [34]
    J. J. Yan, Y. Q. Xia, L. Li. Stabilization of fuzzy systems with quantization and packet dropout. International Journal of Robust and Nonlinear Control, vol. 24, no. 10, pp. 1563–1583, 2014.MathSciNetMATHCrossRefGoogle Scholar
  35. [35]
    Y. Q. Xia, J. J. Yan, J. Z. Shang, M. Y. Fu, B. Liu. Stabilization of quantized systems based on Kalman filter. Control Engineering Practice, vol. 20, no. 10, pp. 954–962, 2012.CrossRefGoogle Scholar
  36. [36]
    Y. Sharon, D. Liberzon. Input to state stabilizing controller for systems with coarse quantization. IEEE Transactions on Automatic Control, vol. 57, no. 4, pp. 830–844, 2012.MathSciNetCrossRefGoogle Scholar
  37. [37]
    R. E. Kalman. A new approach to linear filtering and prediction problems. Journal of Fluids Engineering, vol. 82, no. 1, pp. 35–45, 1960.Google Scholar
  38. [38]
    K. Y. You, L. H. Xie. Kalman filtering with scheduled measurements. IEEE Transactions on Signal Processing, vol. 61, no. 6, pp. 1520–1530, 2013.MathSciNetCrossRefGoogle Scholar
  39. [39]
    M. Sahebsara, T. W. Chen, S. L. Shah. Optimal H2 filtering in networked control systems with multiple packet dropout. IEEE Transactions on Automatic Control, vol. 52, no. 8, pp. 1508–1513, 2007.MathSciNetCrossRefGoogle Scholar
  40. [40]
    M. Sahebsara, T. W. Chen, S. L. Shah. Optimal H filtering in networked control systems with multiple packet dropouts. Systems & Control Letters, vol. 57, no. 9, pp. 696–702, 2008.MathSciNetMATHCrossRefGoogle Scholar
  41. [41]
    W. A. Zhang, L. Yu, H. B. Song. H filtering of networked discrete-time systems with random packet losses. Information Sciences, vol. 179, no. 22, pp. 3944–3955, 2009.MathSciNetMATHCrossRefGoogle Scholar
  42. [42]
    B. Sinopoli, L. Schenato, M. Franceschetti, K. Poolla, M. I. Jordan, S. S. Sastry. Kalman filtering with intermittent observations. IEEE Transactions on Automatic Control, vol. 49, no. 9, pp. 1453–1464, 2004.MathSciNetCrossRefGoogle Scholar
  43. [43]
    X. He, Z. D. Wang, D. Zhou. Robust H filtering for networked systems with multiple state delays. International Journal of Control, vol. 80, no. 8, pp. 1217–1232, 2007.MathSciNetMATHCrossRefGoogle Scholar
  44. [44]
    S. L. Hu, D. Yue. Event-based H filtering for networked system with communication delay. Signal Processing, vol. 92, no. 9, pp. 2029–2039, 2012.CrossRefGoogle Scholar
  45. [45]
    M. Moayedi, Y. K. Foo, Y. C. Soh. Adaptive Kalman filtering in networked systems with random sensor delays, multiple packet dropouts and missing measurements. IEEE Transactions on Signal Processing, vol. 58, no. 3, pp. 1577–1588, 2010.MathSciNetCrossRefGoogle Scholar
  46. [46]
    L. Schenato. Optimal estimation in networked control systems subject to random delay and packet drop. IEEE Transactions on Automatic Control, vol. 53, no. 5, pp. 1311–1317, 2008.MathSciNetCrossRefGoogle Scholar
  47. [47]
    M. Sahebsara, T. Chen, S. L. Shah. Optimal filtering with random sensor delay, multiple packet dropout and uncertain observations. International Journal of Control, vol. 80, no. 2, pp. 292–301, 2007.MathSciNetMATHCrossRefGoogle Scholar
  48. [48]
    G. L. Wei, Z. D. Wang, X. He, H. S. Shu. Filtering for networked stochastic time-delay systems with sector nonlinearity. IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 56, no. 1, pp. 71–75, 2009.CrossRefGoogle Scholar
  49. [49]
    Y. Shi, H. Z. Fang. Kalman filter-based identification for systems with randomly missing measurements in a network environment. International Journal of Control, vol. 83, no. 3, pp. 538–551, 2010.MathSciNetMATHCrossRefGoogle Scholar
  50. [50]
    M. Moayedi, Y. K. Foo, Y. C. Soh. Filtering for networked control systems with single/multiple measurement packets subject to multiple-step measurement delays and multiple packet dropouts. International Journal of Systems Science, vol. 42, no. 3, pp. 335–348, 2011.MathSciNetMATHCrossRefGoogle Scholar
  51. [51]
    D. Yue, Q. L. Han. Network-based robust H filtering for uncertain linear systems. IEEE Transactions on Signal Processing, vol. 54, no. 11, pp. 4293–4301, 2006.MathSciNetCrossRefGoogle Scholar
  52. [52]
    Y. Q. Xia, J. Q. Han. Robust Kalman filtering for systems under norm bounded uncertainties in all system matrices and error covariance constraints. Journal of Systems Science and Complexity, vol. 18, no. 4, pp. 439–445, 2005.MathSciNetMATHGoogle Scholar
  53. [53]
    H. J. Yang, Y. Q. Xia, P. Shi, M. Y. Fu. A novel delta operator Kalman filter design and convergence analysis. IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 58, no. 10, pp. 2458–2468, 2011.MathSciNetCrossRefGoogle Scholar
  54. [54]
    W. Xie, Y. Q. Xia. Data-driven method for Kalman filtering. In Proceedings of the 2nd International Conference on Intelligent Control and Information Processing, IEEE, Harbin, China, pp. 830–835, 2011.Google Scholar
  55. [55]
    J. F. Wu, Q. S. Jia, K. H. Johansson, L. Shi. Event-based sensor data scheduling: Trade-off between communication rate and estimation quality. IEEE Transactions on Automatic Control, vol. 58, no. 4, pp. 1041–1046, 2013.MathSciNetCrossRefGoogle Scholar
  56. [56]
    D. E. Quevedo, D. Nešić. Robust stability of packetized predictive control of nonlinear systems with disturbances and Markovian packet losses. Automatica, vol. 48, no. 8, pp. 1803–1811, 2012.MathSciNetMATHCrossRefGoogle Scholar
  57. [57]
    R. N. Yang, P. Shi, G. P. Liu. Filtering for discrete-time networked nonlinear systems with mixed random delays and packet dropouts. IEEE Transactions on Automatic Control, vol. 56, no. 11, pp. 2655–2660, 2011.MathSciNetCrossRefGoogle Scholar
  58. [58]
    H. L. Dong, Z. D. Wang, H. J. Gao. Robust H filtering for a class of nonlinear networked systems with multiple stochastic communication delays and packet dropouts. IEEE Transactions on Signal Processing, vol. 58, no. 4, pp. 1957–1966, 2010.MathSciNetCrossRefGoogle Scholar
  59. [59]
    M. Hilairet, F. Auger, E. Berthelot. Speed and rotor flux estimation of induction machines using a two-stage extended Kalman filter. Automatica, vol. 45, no. 8, pp. 1819–1827, 2009.Google Scholar
  60. [60]
    H. W. Sorenson. Kalman Filtering: Theory and Application, Piscataway, New Jersey, USA: IEEE, 1985.Google Scholar
  61. [61]
    J. J. LaViola. A comparison of unscented and extended Kalman filtering for estimating quaternion motion. In Proceedings of the American Control Conference, IEEE, Colorado, USA, pp. 2435–2440, 2003.Google Scholar
  62. [62]
    N. J. Gordon, D. J. Salmond, A. F. M. Smith. Novel approach to nonlinear/non-Gaussian Bayesian state estimation. IEE Proceedings F on Radar and Signal Processing, vol. 140, no. 2, pp. 107–113, 1993.CrossRefGoogle Scholar
  63. [63]
    S. Guadarrama, A. Ruiz-Mayor. Approximate robotic mapping from sonar data by modeling perceptions with antonyms. Information Sciences, vol. 180, no. 21, pp. 4164–4188, 2010.CrossRefGoogle Scholar
  64. [64]
    H. P. Liu, F. C. Sun. Efficient visual tracking using particle filter with incremental likelihood calculation. Information Sciences, vol. 195, pp. 141–153, 2012.CrossRefGoogle Scholar
  65. [65]
    Y. Q. Xia, Z. H. Deng, L. Li, X.M. Geng. A new continuousdiscrete particle filter for continuous-discrete nonlinear systems. Information Sciences, vol. 242, pp. 64–75, 2013.MathSciNetMATHCrossRefGoogle Scholar
  66. [66]
    S. Kluge, K. Reif, M. Brokate. Stochastic stability of the extended Kalman filter with intermittent observations. IEEE Transactions on Automatic Control, vol. 55, no. 2, pp. 514–518, 2010.MathSciNetCrossRefGoogle Scholar
  67. [67]
    L. Li, Y. Q. Xia. Stochastic stability of the unscented Kalman filter with intermittent observations. Automatica, vol. 48, no. 5, pp. 978–981, 2012.MathSciNetMATHCrossRefGoogle Scholar
  68. [68]
    L. Li, Y. Q. Xia. Unscented Kalman filter over unreliable communication networks with Markovian packet dropouts. IEEE Transactions on Automatic Control, vol. 58, no. 12, pp. 3224–3230, 2013.CrossRefGoogle Scholar
  69. [69]
    R. A. Singer, A. J. Kanyuck. Computer control of multiple site track correlation. Automatica, vol. 7, no. 4, pp. 455–463, 1971.CrossRefGoogle Scholar
  70. [70]
    D. Willner, C. B. Chang, K. P. Dunn. Kalman filter algorithms for a multi-sensor system. In Proceedings of IEEE Conference on Decision and Control including the 15th Symposium on Adaptive Processes, IEEE, Clearwater, USA, pp. 570–574, 1976.Google Scholar
  71. [71]
    K. Salahshoor, M. Mosallaei, M. Bayat. Centralized and decentralized process and sensor fault monitoring using data fusion based on adaptive extended Kalman filter algorithm. Measurement, vol. 41, no. 10, pp. 1059–1076, 2008.CrossRefGoogle Scholar
  72. [72]
    M. Munz, M. Mählisch, K. Dietmayer. Generic centralized multi sensor data fusion based on probabilistic sensor and environment models for driver assistance systems. IEEE Intelligent Transportation Systems Magazine, vol. 2, no. 1, pp. 6–17, 2010.CrossRefGoogle Scholar
  73. [73]
    A. Polychronopoulos, U. Scheunert, F. Tango. Centralized data fusion for obstacle and road borders tracking in a collision warning system. In Proceedings of the 7th International Conference on Information Fusion, 2004.Google Scholar
  74. [74]
    G. J. Bierman, M. R. Belzer. A decentralized square root information filter/smoother. In Proceedings of the 24th IEEE Conference on Decision and Control, IEEE, Fort Lauderdale, USA, pp. 1902–1905, 1985.Google Scholar
  75. [75]
    N. A. Carlson. Federated square root filter for decentralized parallel processors. IEEE Transactions on Aerospace and Electronic Systems, vol. 26, no. 3, pp. 517–525, 1990.CrossRefGoogle Scholar
  76. [76]
    D. A. Castanon, D. Teneketzis. Distributed estimation algorithms for nonlinear systems. IEEE Transactions on Automatic Control, vol. 30, no. 5, pp. 418–425, 1985.MathSciNetMATHCrossRefGoogle Scholar
  77. [77]
    R. Lobbia, M. Kent. Data fusion of decentralized local tracker outputs. IEEE Transactions on Aerospace and Electronic Systems, vol. 30, no. 3, pp. 787–799, 1994.CrossRefGoogle Scholar
  78. [78]
    Y. Bar-Shalom. On the track-to-track correlation problem. IEEE Transactions on Automatic Control, vol. 26, no. 2, pp. 571–572, 1981.MathSciNetMATHCrossRefGoogle Scholar
  79. [79]
    S. Grime, H. F. Durrant-Whyte, P. Ho. Communication in decentralized data-fusion systems. In Proceedings of the American Control Conference, IEEE, Chicago, USA, pp. 3299–3303, 1992.Google Scholar
  80. [80]
    R. Kumar, M. Wolenetz, B. Agarwalla, J. S. Shin, P. W. Hutto, A. Paul, U. Ramachandran. DFuse: A framework for distributed data fusion. In Proceedings of the 1st International Conference on Embedded Networked Sensor Systems, ACM, New York, USA, pp. 114–125, 2003.CrossRefGoogle Scholar
  81. [81]
    M. S. Mahmoud, Y. Q. Xia. Networked Filtering and Fusion in Wireless Sensor Networks, New York: CRC Press, 2014.CrossRefGoogle Scholar
  82. [82]
    S. Challa, M. Palaniswami, A. Shilton. Distributed data fusion using support vector machines. In Proceedings of the 5th International Conference on Information Fusion, IEEE, Annapolis, USA, pp. 881–885, 2002.Google Scholar
  83. [83]
    C. S. Regazzoni, A. Tesei. Distributed data fusion for realtime crowding estimation. Signal Processing, vol. 53, no. 1, pp. 47–63, 1996.MATHCrossRefGoogle Scholar
  84. [84]
    M. E. Liggins, C. Y. Chong, I. Kadar, M. G. Alford, V. Vannicola, S. Thomopoulos. Distributed fusion architectures and algorithms for target tracking. Proceedings of the IEEE, vol. 85, no. 1, pp. 95–107, 1997.CrossRefGoogle Scholar
  85. [85]
    E. Besada-Portas, J. A. Lopez-Orozco, J. Besada, J. M. De la Cruz. Multisensor fusion for linear control systems with asynchronous, out-of-sequence and erroneous data. Automatica, vol. 47, no. 7, pp. 1399–1408, 2011.MathSciNetMATHCrossRefGoogle Scholar
  86. [86]
    X. J. Shen, E. B. Song, Y. M. Zhu, Y. T. Luo. Globally optimal distributed Kalman fusion with local out-of-sequencemeasurement updates. IEEE Transactions on Automatic Control, vol. 54, no. 8, pp. 1928–1934, 2009.MathSciNetCrossRefGoogle Scholar
  87. [87]
    B. Chen, W. A. Zhang, L. Yu. Distributed fusion estimation with missing measurements, random transmission delays and packet dropouts. IEEE Transactions on Automatic Control, vol. 59, no. 7, pp. 1961–1967, 2014.MathSciNetCrossRefGoogle Scholar
  88. [88]
    Y. Q. Xia, J. Z. Shang, J. Chen, G. P. Liu. Data fusion over network. In Proceedings of the 27th Chinese Control Conference, IEEE, Kunming, China, pp. 452–456, 2008.Google Scholar
  89. [89]
    Y. Q. Xia, J. Z. Shang, J. Chen, G. P. Liu. Networked data fusion with packet losses and variable delays. IEEE Transactions on Systems, Man, and Cybernetics — Part B: Cybernetics, vol. 39, no. 5, pp. 1107–1120, 2009.CrossRefGoogle Scholar
  90. [90]
    C. Zhu, Y. Q. Xia, L. P. Yan, M. Y. Fu. Multi-channel networked data fusion with intermittent observations. In Proceedings of the 29th Chinese Control Conference, IEEE, Beijing, China, pp. 4317–4322, 2010.Google Scholar
  91. [91]
    C. Zhu, Y. Q. Xia, L. P. Yan, M. Y. Fu. Centralised fusion over unreliable networks. International Journal of Control, vol. 85, no. 4, pp. 409–418, 2012.MathSciNetMATHCrossRefGoogle Scholar
  92. [92]
    W. A. Zhang, G. Feng, L. Yu. Multi-rate distributed fusion estimation for sensor networks with packet losses. Automatica, vol. 48, no. 9, pp. 2016–2028, 2012.MathSciNetMATHCrossRefGoogle Scholar
  93. [93]
    Y. Liang, T. W. Chen, Q. Pan. Multi-rate stochastic H filtering for networked multi-sensor fusion. Automatica, vol. 46, no. 2, pp. 437–444, 2010.MathSciNetMATHCrossRefGoogle Scholar
  94. [94]
    L. P. Yan, B. Xiao, Y. Q. Xia, M. Y. Fu. State estimation for asynchronous multirate multisensor nonlinear dynamic systems with missing measurements. International Journal of Adaptive Control and Signal Processing, vol. 26, no. 6, pp. 516–529, 2012.MathSciNetMATHCrossRefGoogle Scholar
  95. [95]
    M. Renzo, L. Imbriglio, F. Graziosi, F. Santucci. Distributed data fusion over correlated log-normal sensing and reporting channels: Application to cognitive radio networks. IEEE Transactions on Wireless Communications, vol. 8, no. 12, pp. 5813–5821, 2009.CrossRefGoogle Scholar
  96. [96]
    L. P. Yan, X. R. Li, Y. Q. Xia, M. Y. Fu. Optimal sequential and distributed fusion for state estimation in crosscorrelated noise. Automatica, vol. 49, no. 12, pp. 3607–3612, 2013.MathSciNetMATHCrossRefGoogle Scholar
  97. [97]
    X. L. Bian, Y. Q. Xia, Z. H. Deng, M. Y. Fu. Onechannel networked data fusion with communication constraint. Journal of the Franklin Institute, vol. 351, no. 1, pp. 156–173, 2014.MathSciNetMATHCrossRefGoogle Scholar
  98. [98]
    X. L. Bian, Y. Q. Xia. Energy efficient data fusion over wireless channels with power control. IET Signal Processing, vol. 9, no. 3, pp. 206–217, 2015.CrossRefGoogle Scholar
  99. [99]
    H. Ye, S. X. Ding. Fault detection of networked control systems with network-induced delay. In Proceedings of the 8th International Conference on Control, Automation, Robotics and Vision, IEEE, Kunming, China, pp. 294–297, 2004.Google Scholar
  100. [100]
    W. Zhang, M. S. Branicky, S. M. Phillips. Stability of networked control systems. IEEE Control Systems Magazine, vol. 21, no. 1, pp. 84–99, 2001.CrossRefGoogle Scholar
  101. [101]
    H. Ye, P. Zhang, S. X. Ding, G. Z. Wang. A time-frequency domain fault detection approach based on parity relation and wavelet transform. In Proceedings of the 39th IEEE Conference on Control and Decision, IEEE, Sydney, Australia, pp. 4156–4161, 2000.Google Scholar
  102. [102]
    D. Huang, S. K. Nguang. Robust fault estimator design for uncertain networked control systems with random time delays: An ILMI approach. Information Sciences, vol. 180, no. 3, pp. 465–480, 2010.MathSciNetMATHCrossRefGoogle Scholar
  103. [103]
    L. B. Xie, H. J. Fang, Y. Zheng. Guaranteed cost control for networked control systems. Journal of Control Theory and Applications, vol. 2, no. 2, pp. 143–148, 2004.MathSciNetMATHCrossRefGoogle Scholar
  104. [104]
    H. Ye, Y. Q. Wang. Application of parity relation and stationary wavelet transform to fault detection of networked control systems. In Proceedings of the 1st IEEE Conference on Industrial Electronics and Application, IEEE, Singapore, pp. 1–6, 2006.Google Scholar
  105. [105]
    H. Ye, G. Z. Wang, S. X. Ding. A new parity space approach for fault detection based on stationary wavelet transform. IEEE Transactions on Automatic Control, vol. 49, no. 2, pp. 281–287, 2004.MathSciNetCrossRefGoogle Scholar
  106. [106]
    H. Ye, R. He, H. Liu, G. Z. Wang. A new approach for fault detection of networked control systems. In Proceedings of the 14th IFAC Symposium on System Identification, IFAC, New castle, Australia, pp. 654–659, 2006.Google Scholar
  107. [107]
    Z. H. Huo, H. J. Fang. Robust H filter design for networked control system with random time delays. In Proceedings of the 10th IEEE International Conference on Engineering of Complex Computer Systems, IEEE, Shanghai, China, pp. 333–340, 2005.Google Scholar
  108. [108]
    Z. H. Huo, H. J. Fang. Research on robust fault detection for NCS with long delay based on LMI. International Journal of Advances in Systems Science and Applications, vol.5, no. 3, pp. 404–410, 2005.Google Scholar
  109. [109]
    Z. H. Huo, H. J. Fang. Fault-tolerant control research for networked control system under communication constraints. Acta Automatica Sinica, vol. 32, no. 5, pp. 659–666, 2006.MathSciNetGoogle Scholar
  110. [110]
    Z. H. Huo, H. J. Fang. Fault-tolerant control of networked control systems with random time-delays. Information and Control, vol. 35, no. 5, pp. 584–587, 2006.MathSciNetGoogle Scholar
  111. [111]
    H. J. Fang, H. Zhang, Y. W. Fang, F. Yang. Quasi T-S fuzzy models and stable controllers for networked control systems. In Proceedings of the 6th World Congress on Intelligent Control and Automation, IEEE, Dalian, China, pp. 220–223, 2006.Google Scholar
  112. [112]
    Y. Zheng, H. J. Fang, H. O. Wang. Takagi-sugeno fuzzymodel-based fault detection for networked control systems with Markov delays. IEEE Transactions on Systems, Man, and Cybernetics — Part B: Cybernetics, vol. 36, no. 4, pp. 924–929, 2006.CrossRefGoogle Scholar
  113. [113]
    H. J. Fang, F. Yang, Y. Zheng, H. Zhang. Fuzzy modeling and fault detection for networked control systems. In Proceedings of the 6th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes, IFAC, Beijing, China, pp. 1091–1096, 2006.Google Scholar
  114. [114]
    Z. H. Mao, B. Jiang, P. Shi. Protocol and fault detection design for nonlinear networked control systems. IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 56, no. 3, pp. 255–259, 2009.CrossRefGoogle Scholar
  115. [115]
    B. Liu, Y. Q. Xia, Y. Yang, M. Y. Fu. Robust fault detection of linear systems over networks with bounded packet loss. Journal of the Franklin Institute, vol. 349, no. 7, pp. 2480–2499, 2012.MathSciNetMATHCrossRefGoogle Scholar
  116. [116]
    H. J. Yang, Y. Q. Xia, B. Liu. Fault detection for TCS fuzzy discrete systems in finite-frequency domain. IEEE Transactions on Systems, Man, and Cybernetics — Part B: Cybernetics, vol. 41, no. 4, pp. 911–920, 2011.CrossRefGoogle Scholar
  117. [117]
    B. Liu, Y. Q. Xia. Fault detection and compensation for linear systems over networks with random delays and clock asynchronism. IEEE Transactions on Industrial Electronics, vol. 58, no. 9, pp. 4396–4406, 2011.CrossRefGoogle Scholar
  118. [118]
    Y. Q. Xia, B. Liu. Maximum likelihood ratio detection of abrupt state change for MIMO linear systems based on frequency domain data. International Journal of Robust and Nonlinear Control, vol. 23, no. 8, pp. 858–877, 2013.MathSciNetMATHCrossRefGoogle Scholar
  119. [119]
    Y. Q. Xia, A. Amann, B. Liu. Detection of abrupt changes in electrocardiogram with generalised likelihood ratio algorithm. IET Signal Processing, vol. 4, no. 6, pp. 650–657, 2010.CrossRefGoogle Scholar
  120. [120]
    M. Y. Chow, Y. Tipsuwan. Network-based control systems: A tutorial. In Proceedings of the 27th Annual Conference of the IEEE Industrial Electronics Society, IEEE, Denver, USA, pp. 1593–1602, 2001.Google Scholar
  121. [121]
    D. Q. Mayne, J. B. Rawlings, C. V. Rao, P. O. M. Scokaert. Constrained model predictive control: Stability and optimality. Automatica, vol. 36, no. 6, pp. 789–814, 2000.MathSciNetMATHCrossRefGoogle Scholar
  122. [122]
    H. Chen, F. Allgöwer. A quasi-infinite horizon nonlinear model predictive control scheme with guaranteed stability. Automatica, vol. 34, no. 10, pp. 1205–1217, 1998.MathSciNetMATHCrossRefGoogle Scholar
  123. [123]
    G. W. Irwin, J. Chen, A. McKernan, W. G. Scanlon. Codesign of predictive controllers for wireless network control. IET Control Theory & Applications, vol. 4, no. 2, pp. 186–196, 2010.MathSciNetCrossRefGoogle Scholar
  124. [124]
    G. P. Liu, J. X. Mu, D. Rees, S. C. Chai. Design and stability analysis of networked control systems with random communication time delay using the modified MPC. International Journal of Control, vol. 79, no. 4, pp. 288–297, 2006.MathSciNetMATHCrossRefGoogle Scholar
  125. [125]
    H. Zhang, Y. Shi, M. X. Liu. H step tracking control for networked discrete-time nonlinear systems with integral and predictive actions. IEEE Transactions on Industrial Informatics, vol. 9, no. 1, pp. 337–345, 2013.CrossRefGoogle Scholar
  126. [126]
    Y. B. Zhao, G. P. Liu, D. Rees. Improved predictive control approach to networked control systems. IET Control Theory & Applications, vol. 2, no. 8, pp. 675–681, 2008.MathSciNetCrossRefGoogle Scholar
  127. [127]
    Y. B. Zhao, G. P. Liu, D. Rees. Integrated predictive control and scheduling co-design for networked control systems. IET Control Theory & Applications, vol. 2, no. 1, pp. 7–15, 2008.MathSciNetCrossRefGoogle Scholar
  128. [128]
    G. F. Zhang, X. Chen, T. W. Chen. A model predictive control approach to networked systems. In Proceedings of the 46th IEEE Conference on Decision and Control, IEEE, New Orleans, USA, pp. 3339–3344, 2007.Google Scholar
  129. [129]
    G. C. Goodwin, H. Haimovich, D. E. Quevedo, J. S. Welsh. A moving horizon approach to networked control system design. IEEE Transactions on Automatic Control, vol. 49, no. 9, pp. 1427–1445, 2004.MathSciNetCrossRefGoogle Scholar
  130. [130]
    P. Varutti, B. Kern, T. Faulwasser, R. Findeisen. Eventbased model predictive control for networked control systems. In Proceedings of the 28th Chinese Control Conference and Decision and the 48th IEEE Conference on Control Conference, IEEE, Shanghai, China, pp. 567–572, 2009.Google Scholar
  131. [131]
    D. E. Quevedo, D. Nešić. Input-to-state stability of packetized predictive control over unreliable networks affected by packet-dropouts. IEEE Transactions on Automatic Control, vol. 56, no. 2, pp. 370–375, 2011.MathSciNetCrossRefGoogle Scholar
  132. [132]
    D. Muñoz de la Peña, P. D. Christofides. Lyapunovbased model predictive control of nonlinear systems subject to data losses. IEEE Transactions on Automatic Control, vol. 53, no. 9, pp. 2076–2089, 2008.CrossRefGoogle Scholar
  133. [133]
    G. Pin, T. Parisini. Networked predictive control of uncertain constrained nonlinear systems: Recursive feasibility and input-to-state stability analysis. IEEE Transactions on Automatic Control, vol. 56, no. 1, pp. 72–87, 2011.MathSciNetCrossRefGoogle Scholar
  134. [134]
    Y. Q. Xia, G. P. Liu, P. Shi, J. Chen, D. Rees. Robust constrained model predictive control based on parameterdependent Lyapunov functions. Circuits, Systems and Signal Processing, vol. 27, no. 4, pp. 429–446, 2008.MathSciNetMATHCrossRefGoogle Scholar
  135. [135]
    Y. Iino, T. Hatanaka, M. Fujita. Event-predictive control for energy saving of wireless networked control system. In Proceedings of the American Control Conference, IEEE, Saint Louis, USA, pp. 2236–2242, 2009.Google Scholar
  136. [136]
    E. Garcia, P. J. Antsaklis. Model-based event-triggered control with time-varying network delays. Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference, IEEE, Orlando, USA, pp. 1650–1655, 2011.CrossRefGoogle Scholar
  137. [137]
    A. Eqtami, D. V. Dimarogonas, K. J. Kyriakopoulos. Novel event-triggered strategies for model predictive controllers. In Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference, IEEE, Orlando, USA, pp. 3392–3397, 2011.CrossRefGoogle Scholar
  138. [138]
    E. Henriksson, D. E. Quevedo, H. Sandberg, K. H. Johansson. Self-triggered model predictive control for network scheduling and control. In Proceedings of the 8th IFAC Symposium on Advanced Control of Chemical Processes, IFAC, Furama Riverfront, Singapore, pp. 432–438, 2012.Google Scholar
  139. [139]
    J. Wu, L. Q. Zhang, T. W. Chen. Model predictive control for networked control systems. International Journal of Robust and Nonlinear Control, vol. 19, no. 9, pp. 1016–1035, 2009.MathSciNetMATHCrossRefGoogle Scholar
  140. [140]
    J. F. Liu, D. Muñoz de la Peña, P. D. Christofides, J. F. Davis. Lyapunov-based model predictive control of nonlinear systems subject to time-varying measurement delays. International Journal of Adaptive Control and Signal Processing, vol. 23, no. 8, pp. 788–807, 2009.MATHCrossRefGoogle Scholar
  141. [141]
    L. C. Jin, R. Kumar, N. Elia. Model predictive controlbased real-time power system protection schemes. IEEE Transactions on Power Systems, vol. 25, no. 2, pp. 988–998, 2010.CrossRefGoogle Scholar
  142. [142]
    B. Yu, Y. Shi, J. Huang. Modified generalized predictive control of networked systems with application to a hydraulic position control system. Journal of Dynamic Systems, Measurement, and Control, vol. 133, no. 3, Article number 031009, 2011.Google Scholar
  143. [143]
    Y. Zou, T. Chen, S. Li. Network-based predictive control of multirate systems. IET Control Theory & Applications, vol. 4, no. 7, pp. 1145–1156, 2010.MathSciNetCrossRefGoogle Scholar
  144. [144]
    Y. Zhang, S. Y. Li. Networked model predictive control based on neighbourhood optimization for serially connected large-scale processes. Journal of Process Control, vol. 17, no. 1, pp. 37–50, 2007.CrossRefGoogle Scholar
  145. [145]
    G. P. Liu, J. X. Mu, D. Rees. Networked predictive control of systems with random communication delay. In Proceedings of UKACC International Conference on Control, Bath, UK, 2004.Google Scholar
  146. [146]
    Y. B. Zhao, G. P. Liu, D. Rees. Networked predictive control systems based on the Hammerstein model. IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 55, no. 5, pp. 469–473, 2008.CrossRefGoogle Scholar
  147. [147]
    D. E. Quevedo, J. Ostergaard, D. Nešić. Packetized predictive control of stochastic systems over bit-rate limited channels with packet loss. IEEE Transactions on Automatic Control, vol. 56, no. 12, pp. 2854–2868, 2011.MathSciNetCrossRefGoogle Scholar
  148. [148]
    D. E. Quevedo, E. I. Silva, G. C. Goodwin. Packetized predictive control over erasure channels. In Proceedings of the American Control Conference, IEEE, New York, USA, pp. 1003–1008, 2007.Google Scholar
  149. [149]
    P. Mhaskar, N. H. El-Farra, P. D. Christofides. Predictive control of switched nonlinear systems with scheduled mode transitions. IEEE Transactions on Automatic Control, vol. 50, no. 11, pp. 1670–1680, 2005.MathSciNetCrossRefGoogle Scholar
  150. [150]
    B. Xue, N. Li, S. Li, Q. Zhu. Robust model predictive control for networked control systems with quantisation. IET Control Theory & Applications, vol. 4, no. 12, pp. 2896–2906, 2010.MathSciNetCrossRefGoogle Scholar
  151. [151]
    D. Srinivasagupta, H. Schättler, B. Joseph. Time-stamped model predictive control: An algorithm for control of processes with random delays. Computers & Chemical Engineering, vol. 28, no. 8, pp. 1337–1346, 2004.CrossRefGoogle Scholar
  152. [152]
    Y. Q. Xia, H. J. Yang, P. Shi, M. Y. Fu. Constrained infinite-horizon model predictive control for fuzzy-discretetime systems. IEEE Transactions on Fuzzy Systems, vol. 18, no. 2, pp. 429–436, 2010.Google Scholar
  153. [153]
    Y. Q. Xia, M. Y. Fu, P. Shi. Analysis and Synthesis of Dynamical Systems with Time-delays, Berlin, Germany, Heidelberg: Springer, 2009.MATHCrossRefGoogle Scholar
  154. [154]
    Y. Q. Xia, M. Y. Fu, G. P. Liu. Analysis and Synthesis of Networked Control Systems, Berlin, Germany, Heidelberg: Springer, 2011.MATHCrossRefGoogle Scholar
  155. [155]
    Y. Q. Xia, G. P. Liu, M. Y. Fu, D. Rees. Predictive control of networked systems with random delay and data dropout. IET Control Theory & Applications, vol. 3, no. 11, pp. 1476–1486, 2009.CrossRefGoogle Scholar
  156. [156]
    Y. Q. Xia, F. M. Fu, B. Liu, G. P. Liu. Design and performance analysis of networked control systems with random delay. Journal of Systems Engineering and Electronics, vol. 20, no. 4, pp. 807–822, 2009.Google Scholar
  157. [157]
    S. C. Chai, G. P. Liu, D. Rees. Design and implementation of networked predictive control systems. In Proceedings of the 16th IFAC World Congress, IFAC, Prague, Czech Republic, 2005.Google Scholar
  158. [158]
    W. S. Hu, G. P. Liu, D. Rees. Design and implementation of networked predictive control systems based on round trip time delay measurement. In Proceedings of the American Control Conference, IEEE, Minneapolis, USA, pp. 674–679, 2006.Google Scholar
  159. [159]
    S. C. Chai, G. P. Liu, D. Rees, Y. Q. Xia. Design and practical implementation of internet-based predictive control of a servo system. IEEE Transactions on Control Systems Technology, vol. 16, no. 1, pp. 158–168, 2008.CrossRefGoogle Scholar
  160. [160]
    G. P. Liu, D. Rees, S. C. Chai. Design and practical implementation of networked predictive control systems. In Proceedings of the 12th IEEE International Conference on Networking, Sensing and Control, IEEE, Tucson, USA, pp. 336–341, 2005.Google Scholar
  161. [161]
    G. P. Liu, Y. Q. Xia, D. Rees, W. S. Hu. Design and stability criteria of networked predictive control systems with random network delay in the feedback channel. IEEE Transactions on Systems, Man, and Cybernetics — Part C: Applications and Reviews, vol. 37, no. 2, pp. 173–184, 2007.CrossRefGoogle Scholar
  162. [162]
    W. S. Hu, G. P. Liu, D. Rees. Event-driven networked predictive control. IEEE Transactions on Industrial Electronics, vol. 54, no. 3, pp. 1603–1613, 2007.CrossRefGoogle Scholar
  163. [163]
    Y. Q. Xia, L. Li, G. P. Liu, P. Shi. H predictive control of networked control systems. International Journal of Control, vol. 84, no. 6, pp. 1080–1097, 2011.MathSciNetMATHCrossRefGoogle Scholar
  164. [164]
    R. Wang, G. P. Liu, W. Wang, D. Rees, Y. B. Zhao. H control for networked predictive control systems based on the switched Lyapunov function method. IEEE Transactions on Industrial Electronics, vol. 57, no. 10, pp. 3565–3571, 2010.CrossRefGoogle Scholar
  165. [165]
    B. Liu, Y. Q. Xia, M. S. Mahmoud, H. Wu, S. S. Cui. New predictive control scheme for networked control systems. Circuits, Systems, and Signal Processing, vol. 31, no. 3, pp. 945–960, 2012.MathSciNetMATHCrossRefGoogle Scholar
  166. [166]
    G. P. Liu, S. C. Chai, J. X. Mu, D. Rees. Networked predictive control of systems with random delay in signal transmission channels. International Journal of Systems Science, vol. 39, no. 11, pp. 1055–1064, 2008.MathSciNetMATHCrossRefGoogle Scholar
  167. [167]
    G. P. Liu, Y. Q. Xia, J. Chen, D. Rees, W. S. Hu. Networked predictive control of systems with random network delays in both forward and feedback channels. IEEE Transactions on Industrial Electronics, vol. 54, no. 3, pp. 1282–1297, 2007.CrossRefGoogle Scholar
  168. [168]
    G. P. Liu. Predictive controller design of networked systems with communication delays and data loss. IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 57, no. 6, pp. 481–485, 2010.CrossRefGoogle Scholar
  169. [169]
    R. N. Yang, G. P. Liu, P. Shi, C. Thomas, M. V. Basin. Predictive output feedback control for networked control systems. IEEE Transactions on Industrial Electronics, vol. 61, no. 1, pp. 512–520, 2014.CrossRefGoogle Scholar
  170. [170]
    Y. Q. Xia, J. Chen, G. P. Liu, D. Rees. Stability analysis of networked predictive control systems with random network delay. In Proceedings of IEEE International Conference on Networking, Sensing and Control, IEEE, London, UK, pp. 815–820, 2007.Google Scholar
  171. [171]
    R. Wang, B. Wang, G. P. Liu, W. Wang, D. Rees. H controller design for networked predictive control systems based on the average dwell-time approach. IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 57, no. 4, pp. 310–314, 2010.CrossRefGoogle Scholar
  172. [172]
    R. Kadali, B. Huang, A. Rossiter. A data driven subspace approach to predictive controller design. Control Engineering Practice, vol. 11, no. 3, pp. 261–278, 2003.CrossRefGoogle Scholar
  173. [173]
    D. Laurí, J. A. Rossiter, J. Sanchis, M. Martínez. Datadriven latent-variable model-based predictive control for continuous processes. Journal of Process Control, vol. 20, no. 10, pp. 1207–1219, 2010.CrossRefGoogle Scholar
  174. [174]
    J. X. Xu, Z. S. Hou. Notes on data-driven system approaches. Acta Automatica Sinica, vol. 35, no. 6, pp. 668–675, 2009.MathSciNetGoogle Scholar
  175. [175]
    Y. Q. Xia, W. Xie, B. Liu, X. Y. Wang. Data-driven predictive control for networked control systems. Information Sciences, vol. 235, pp. 45–54, 2013.MathSciNetMATHCrossRefGoogle Scholar
  176. [176]
    G. Chaloulos, P. Hokayem, J. Lygeros. Distributed hierarchical MPC for conflict resolution in air traffic control. In Proceedings of the American Control Conference, IEEE, Baltimore, USA, pp. 3945–3950, 2010.Google Scholar
  177. [177]
    T. Keviczky, F. Borrelli, K. Fregene, D. Godbole, G. J. Balas. Decentralized receding horizon control and coordination of autonomous vehicle formations. IEEE Transactions on Control Systems Technology, vol. 16, no. 1, pp. 19–33, 2008.CrossRefGoogle Scholar
  178. [178]
    B. T. Stewart, S. J. Wright, J. B. Rawlings. Cooperative distributed model predictive control for nonlinear systems. Journal of Process Control, vol. 21, no. 5, pp. 698–704, 2011.CrossRefGoogle Scholar
  179. [179]
    A. N. Venkat, I. A. Hiskens, J. B. Rawlings, S. J. Wright. Distributed MPC strategies with application to power system automatic generation control. IEEE Transactions on Control Systems Technology, vol. 16, no. 6, pp. 1192–1206, 2008.CrossRefGoogle Scholar
  180. [180]
    Y. Kuwata, A. Richards, T. Schouwenaars, J. P. How. Distributed robust receding horizon control for multivehicle guidance. IEEE Transactions on Control Systems Technology, vol. 15, no. 4, pp. 627–641, 2007.CrossRefGoogle Scholar
  181. [181]
    P. Trodden, A. Richards. Cooperative distributed MPC of linear systems with coupled constraints. Automatica, vol. 49, no. 2, pp. 479–487, 2013.MathSciNetMATHCrossRefGoogle Scholar
  182. [182]
    A. Richards, J. P. How. Robust distributed model predictive control. International Journal of Control, vol. 80, no. 9, pp. 1517–1531, 2007.MathSciNetMATHCrossRefGoogle Scholar
  183. [183]
    M. A. Müller, M. Reble, F. Allgöwer. A general distributed MPC framework for cooperative control. In Proceedings of the 18th IFAC World Congress, IFAC, Milano, Italy, pp. 7987–7992, 2011.Google Scholar
  184. [184]
    P. Wang, B. C. Ding. Distributed RHC for tracking and formation of nonholonomic multi-vehicle systems. IEEE Transactions on Automatic Control, vol. 59, no. 6, pp. 1439–1453, 2014.MathSciNetCrossRefGoogle Scholar
  185. [185]
    W. B. Dunbar. Distributed receding horizon control of dynamically coupled nonlinear systems. IEEE Transactions on Automatic Control, vol. 52, no. 7, pp. 1249–1263, 2007.MathSciNetCrossRefGoogle Scholar
  186. [186]
    J. M. Maestre, R. R. Negenborn. Distributed Model Predictive Control Made Easy, The Netherlands: Springer, 2014.CrossRefGoogle Scholar
  187. [187]
    R. R. Negenborn, J. M. Maestre. Distributed model predictive control: An overview and roadmap of future research opportunities. IEEE Control Systems Magazine, vol. 34, no. 4, pp. 87–97, 2014.MathSciNetCrossRefGoogle Scholar
  188. [188]
    A. Eqtami, D. V. Dimarogonas, K. J. Kyriakopoulos. Event-based model predictive control for the cooperation of distributed agents. In Proceedings of the American Control Conference, IEEE, Montreal, Canada, pp. 6473–6478, 2012.Google Scholar
  189. [189]
    A. Eqtami, D. V. Dimarogonas, K. J. Kyriakopoulos. Event-triggered strategies for decentralized model predictive controllers. In Proceedings of the 18th IFAC World Congress, IFAC, Milano, Italy, pp. 10068–10073, 2011.Google Scholar
  190. [190]
    W. B. Dunbar. Distributed Receding Horizon Control of Multiagent Systems, Ph.D dissertation, California Institute of Technology, USA, 2004.Google Scholar
  191. [191]
    W. B. Dunbar, R. M. Murray. Distributed receding horizon control for multi-vehicle formation stabilization. Automatica, vol. 42, no. 4, pp. 549–558. 2006.MathSciNetMATHCrossRefGoogle Scholar
  192. [192]
    T. Keviczky, F. Borrelli, G. J. Balas. Decentralized receding horizon control for large scale dynamically decoupled systems. Automatica, vol. 42, no. 12, pp. 2105–2115, 2006.MathSciNetMATHCrossRefGoogle Scholar
  193. [193]
    H. P. Li, Y. Shi. Distributed model predictive control of constrained nonlinear systems with communication delays. Systems & Control Letters, vol. 62, no. 10, pp. 819–826, 2013.MathSciNetMATHCrossRefGoogle Scholar
  194. [194]
    H. P. Li, Y. Shi. Robust distributed model predictive control of constrained continuous-time nonlinear systems: A robustness constraint approach. IEEE Transactions on Automatic Control, vol. 59, no. 6, pp. 1673–1678, 2014.CrossRefGoogle Scholar
  195. [195]
    H. P. Li, Y. Shi. Distributed receding horizon control of large-scale nonlinear systems: Handling communication delays and disturbances. Automatica, vol. 50, no. 4, pp. 1264–1271, 2014.MathSciNetMATHCrossRefGoogle Scholar
  196. [196]
    Y. Q. Xia, M. Y. Fu. Compound Control Methodology for Flight Vehicles, Berlin, Germany, Heidelberg: Springer, 2013.MATHCrossRefGoogle Scholar
  197. [197]
    N. Zhou, Y. Q. Xia, K. F. Lu, Y. Li. Decentralised finitetime attitude synchronisation and tracking control for rigid spacecraft. International Journal of Systems Science, to be published.Google Scholar
  198. [198]
    N. Zhou, Y. Q. Xia, M. L. Wang, M. Y. Fu. Finite-time attitude control of multiple rigid spacecraft using terminal sliding mode. International Journal of Robust and Nonlinear Control, to be published.Google Scholar
  199. [199]
    N. Zhou, Y. Q. Xia, K. F. Lu. Attitude synchronization of rigid spacecraft using terminal sliding mode. In Proceedings of the 32nd Chinese Control Conference, IEEE, Xi’an, China, pp. 706–711, 2013.Google Scholar
  200. [200]
    Y. Q. Xia, N. Zhou, K. F. Lu, Y. Li. Attitude control of multiple rigid bodies with uncertainties and disturbances. IEEE/CAA Journal of Automatica Sinica, vol. 2, no. 1, pp. 2–10, 2015.MathSciNetCrossRefGoogle Scholar
  201. [201]
    Y. Q. Xia. From networked control systems to cloud control systems. In Proceedings of the 31st Chinese Control Conference, IEEE, Hefei, China, pp. 5878–5883, 2012.Google Scholar
  202. [202]
    The economist, cloud computing: Clash of the clouds, [Online], Available: http://www.economist.com/node/14637206, 3 November, 2009.
  203. [203]
    Gartner says cloud computing will be as influential as e-business, [Online], Availabe: http://www.gartner.com/newsroom/id/707508, August 22, 2010.
  204. [204]
    G. Galen. What cloud computing really means. InfoWorld, [Online], Available: http://www.infoworld.com/d/cloudcomputing/what-cloud-computing-really-means-031, June 6, 2009.Google Scholar
  205. [205]
    Cloud computing, [Online], Available: http://en.wikipedia.org/wiki/Cloudcomputing, November 27, 2011.
  206. [206]
    Cloud computing, [Online], Available: http://www.cloudcomputingdefined.com/, July 17, 2010.
  207. [207]
    T. Segaran, J. Hammerbacher. Beautiful Data: The Stories Behind Elegant Data Solutions, Sebastopol: O’Reilly Media, 2009.Google Scholar
  208. [208]
    T. White. Hadoop: The Definitive Guide, 3rd ed., Sebastopol: O’Reilly Media, 2012.Google Scholar
  209. [209]
    Y. Q. Xia. Cloud control systems. IEEE/CAA Journal of Automatica Sinica, vol. 2, no. 2, pp. 134–142, 2015.MathSciNetCrossRefGoogle Scholar

Copyright information

© Institute of Automation, Chinese Academy of Sciences and Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Yuan-Qing Xia
    • 1
  • Yu-Long Gao
    • 1
  • Li-Ping Yan
    • 1
  • Meng-Yin Fu
    • 1
  1. 1.School of AutomationBeijing Institute of TechnologyBeijingChina

Personalised recommendations