Time-and event-driven communication process for networked control systems: A survey

Copyright © 2014 Lei Zou et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.In recent years, theoretical and practical research topics on networked control systems (NCSs) have gained an increasing interest from many researchers in a variety of disciplines owing to the extensive applications of NCSs in practice. In particular, an urgent need has arisen to understand the effects of communication processes on system performances. Sampling and protocol are two fundamental aspects of a communication process which have attracted a great deal of research attention. Most research focus has been on the analysis and control of dynamical behaviors under certain sampling procedures and communication protocols. In this paper, we aim to survey some recent advances on the analysis and synthesis issues of NCSs with different sampling procedures (time-and event-driven sampling) and protocols (static and dynamic protocols). First, these sampling procedures and protocols are introduced in detail according to their engineering backgrounds as well as dynamic natures. Then, the developments of the stabilization, control, and filtering problems are systematically reviewed and discussed in great detail. Finally, we conclude the paper by outlining future research challenges for analysis and synthesis problems of NCSs with different communication processes.This work was supported in part by the National Natural Science Foundation of China under Grants 61329301, 61374127, and 61374010, the Royal Society of the UK, and the Alexander von Humboldt Foundation of Germany

Dynamics analysis and integrated design of real-time control systems

Real-time control systems are widely deployed in many applications. Theory and practice for the design and deployment of real-time control systems have evolved significantly. From the design perspective, control strategy development has been the focus of the research in the control community. In order to develop good control strategies, process modelling and analysis have been investigated for decades, and stability analysis and model-based control have been heavily studied in the literature. From the implementation perspective, real-time control systems require timeliness and predictable timing behaviour in addition to logical correctness, and a real-time control system may behave very differently with different software implementations of the control strategies on a digital controller, which typically has limited computing resources. Most current research activities on software implementations concentrate on various scheduling methodologies to ensure the schedulability of multiple control tasks in constrained environments. Recently, more and more real-time control systems are implemented over data networks, leading to increasing interest worldwide in the design and implementation of networked control systems (NCS). Major research activities in NCS include control-oriented and scheduling-oriented investigations. In spite of significant progress in the research and development of real-time control systems, major difficulties exist in the state of the art. A key issue is the lack of integrated design for control development and its software implementation. For control design, the model-based control technique, the current focus of control research, does not work when a good process model is not available or is too complicated for control design. For control implementation on digital controllers running multiple tasks, the system schedulability is essential but is not enough; the ultimate objective of satisfactory quality-of-control (QoC) performance has not been addressed directly. For networked control, the majority of the control-oriented investigations are based on two unrealistic assumptions about the network induced delay. The scheduling-oriented research focuses on schedulability and does not directly link to the overall QoC of the system. General solutions with direct QoC consideration from the network perspective to the challenging problems of network delay and packet dropout in NCS have not been found in the literature. This thesis addresses the design and implementation of real-time control systems with regard to dynamics analysis and integrated design. Three related areas have been investigated, namely control development for controllers, control implementation and scheduling on controllers, and real-time control in networked environments. Seven research problems are identified from these areas for investigation in this thesis, and accordingly seven major contributions have been claimed. Timing behaviour, quality of control, and integrated design for real-time control systems are highlighted throughout this thesis. In control design, a model-free control technique, pattern predictive control, is developed for complex reactive distillation processes. Alleviating the requirement of accurate process models, the developed control technique integrates pattern recognition, fuzzy logic, non-linear transformation, and predictive control into a unified framework to solve complex problems. Characterising the QoC indirectly with control latency and jitter, scheduling strategies for multiple control tasks are proposed to minimise the latency and/or jitter. Also, a hierarchical, QoC driven, and event-triggering feedback scheduling architecture is developed with plug-ins of either the earliest-deadline-first or fixed priority scheduling. Linking to the QoC directly, the architecture minimises the use of computing resources without sacrifice of the system QoC. It considers the control requirements, but does not rely on the control design. For real-time NCS, the dynamics of the network delay are analysed first, and the nonuniform distribution and multi-fractal nature of the delay are revealed. These results do not support two fundamental assumptions used in existing NCS literature. Then, considering the control requirements, solutions are provided to the challenging NCS problems from the network perspective. To compensate for the network delay, a real-time queuing protocol is developed to smooth out the time-varying delay and thus to achieve more predictable behaviour of packet transmissions. For control packet dropout, simple yet effective compensators are proposed. Finally, combining the queuing protocol, the packet loss compensation, the configuration of the worst-case communication delay, and the control design, an integrated design framework is developed for real-time NCS. With this framework, the network delay is limited to within a single control period, leading to simplified system analysis and improved QoC

Integrated feedback scheduling and control co-design for motion coordination of networked induction motor systems

This paper investigates the codesign of remote speed control and network scheduling for motion coordination of multiple induction motors through a shared communication network. An integrated feedback scheduling algorithm is designed to allocate the optimal sampling period and priority to each control loop to optimize the global performance of a networked control system (NCS), while satisfying the constraints of stability and schedulability. A speed synchronization method is incorporated into the scheduling algorithm to improve the speed synchronization performance of multiple induction motors. The rational gain of the network speed controllers is calculated using the Lyapunov theorem and tuned online by fuzzy logic to guarantee the robustness against complicated variations on the communication network. Furthermore, a state predictor is designed to compensate the time delay which occurred in data transmission from the sensor to the controller, as a part of the networked controller. Simulation results support the effectiveness of the proposed control-and-scheduling codesign approach

Linear matrix inequalities in multirate control over networks

This paper faces two of the main drawbacks in networked control systems: bandwidth constraints and timevarying delays. The bandwidth limitations are solved by using multirate control techniques. The resultant multirate controller must ensure closed-loop stability in the presence of time-varying delays. Some stability conditions and a state feedback controller design are formulated in terms of linear matrix inequalities. The theoretical proposal is validated in two different experimental environments: a crane-based test-bed over Ethernet, and a maglev based platform over Profibus. © 2012 Ángel Cuenca et al.The authors A. Cuenca, R. Piza, and J. Salt are grateful to the Spanish Ministry of Education research Grants DPI2011-28507-C02-01 and DPI2009-14744-C03-03, and Generalitat Valenciana Grant GV/2010/018. A. Sala is grateful to the financial support of Spanish Ministry of Economy research Grant DPI2011-27845-C02-01, and Generalitat Valenciana Grant PROMETEO/2008/088.Cuenca Lacruz, ÁM.; Pizá, R.; Salt Llobregat, JJ.; Sala Piqueras, A. (2012). Linear matrix inequalities in multirate control over networks. Mathematical Problems in Engineering. 2012(768212):1-22. doi:10.1155/2012/768212S1222012768212Tipsuwan, Y., & Chow, M.-Y. (2003). Control methodologies in networked control systems. Control Engineering Practice, 11(10), 1099-1111. doi:10.1016/s0967-0661(03)00036-4Halevi, Y., & Ray, A. (1988). Integrated Communication and Control Systems: Part I—Analysis. Journal of Dynamic Systems, Measurement, and Control, 110(4), 367-373. doi:10.1115/1.3152698Yang, T. C. (2006). Networked control system: a brief survey. IEE Proceedings - Control Theory and Applications, 153(4), 403-412. doi:10.1049/ip-cta:20050178Cuenca, Á., Salt, J., Sala, A., & Piza, R. (2011). A Delay-Dependent Dual-Rate PID Controller Over an Ethernet Network. IEEE Transactions on Industrial Informatics, 7(1), 18-29. doi:10.1109/tii.2010.2085007Tipsuwan, Y., & Chow, M.-Y. (2004). On the Gain Scheduling for Networked PI Controller Over IP Network. IEEE/ASME Transactions on Mechatronics, 9(3), 491-498. doi:10.1109/tmech.2004.834645Hu, J., Wang, Z., Gao, H., & Stergioulas, L. K. (2012). Robust Sliding Mode Control for Discrete Stochastic Systems With Mixed Time Delays, Randomly Occurring Uncertainties, and Randomly Occurring Nonlinearities. IEEE Transactions on Industrial Electronics, 59(7), 3008-3015. doi:10.1109/tie.2011.2168791Wing Shing Wong, & Brockett, R. W. (1999). Systems with finite communication bandwidth constraints. II. Stabilization with limited information feedback. IEEE Transactions on Automatic Control, 44(5), 1049-1053. doi:10.1109/9.763226Casanova, V., Salt, J., Cuenca, A., & Piza, R. (2009). Networked Control Systems: control structures with bandwidth limitations. International Journal of Systems, Control and Communications, 1(3), 267. doi:10.1504/ijscc.2009.024556Cuenca, A., García, P., Albertos, P., & Salt, J. (2011). A Non-Uniform Predictor-Observer for a Networked Control System. International Journal of Control, Automation and Systems, 9(6), 1194-1202. doi:10.1007/s12555-011-0621-5Tian, Y.-C., & Levy, D. (2008). Compensation for control packet dropout in networked control systems. Information Sciences, 178(5), 1263-1278. doi:10.1016/j.ins.2007.10.012Wang, Z., Shen, B., Shu, H., & Wei, G. (2012). Quantized $H_{\infty }$ Control for Nonlinear Stochastic Time-Delay Systems With Missing Measurements. IEEE Transactions on Automatic Control, 57(6), 1431-1444. doi:10.1109/tac.2011.2176362Wang, Z., Shen, B., & Liu, X. (2012). H∞ filtering with randomly occurring sensor saturations and missing measurements. Automatica, 48(3), 556-562. doi:10.1016/j.automatica.2012.01.008Ma, L., Wang, Z., Bo, Y., & Guo, Z. (2011). Finite-horizonℋ2/ℋ∞control for a class of nonlinear Markovian jump systems with probabilistic sensor failures. International Journal of Control, 84(11), 1847-1857. doi:10.1080/00207179.2011.627379Li, J.-N., Cai, M., Wang, Y.-L., & Zhang, Q.-L. (2009). H∞ control of networked control systems with packet disordering. IET Control Theory & Applications, 3(11), 1463-1475. doi:10.1049/iet-cta.2008.0416Time synchronization in a local area network. (2004). IEEE Control Systems, 24(2), 61-69. doi:10.1109/mcs.2004.1275432Sala, A., Cuenca, Á., & Salt, J. (2009). A retunable PID multi-rate controller for a networked control system. Information Sciences, 179(14), 2390-2402. doi:10.1016/j.ins.2009.02.017Sala, A. (2005). Computer control under time-varying sampling period: An LMI gridding approach. Automatica, 41(12), 2077-2082. doi:10.1016/j.automatica.2005.05.017Salt, J., & Albertos, P. (2005). Model-based multirate controllers design. IEEE Transactions on Control Systems Technology, 13(6), 988-997. doi:10.1109/tcst.2005.857410Cuenca, Á., Salt, J., & Albertos, P. (2006). Implementation of algebraic controllers for non-conventional sampled-data systems. Real-Time Systems, 35(1), 59-89. doi:10.1007/s11241-006-9001-2Lall, S., & Dullerud, G. (2001). An LMI solution to the robust synthesis problem for multi-rate sampled-data systems. Automatica, 37(12), 1909-1922. doi:10.1016/s0005-1098(01)00167-4Shi, Y., Fang, H., & Yan, M. (2009). Kalman filter-based adaptive control for networked systems with unknown parameters and randomly missing outputs. International Journal of Robust and Nonlinear Control, 19(18), 1976-1992. doi:10.1002/rnc.1390Li, D., Shah, S. L., & Chen, T. (2002). Analysis of dual-rate inferential control systems. Automatica, 38(6), 1053-1059. doi:10.1016/s0005-1098(01)00295-3Boyd, S., El Ghaoui, L., Feron, E., & Balakrishnan, V. (1994). Linear Matrix Inequalities in System and Control Theory. doi:10.1137/1.9781611970777Yun-Bo Zhao, Guo-Ping Liu, & Rees, D. (2009). Modeling and Stabilization of Continuous-Time Packet-Based Networked Control Systems. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 39(6), 1646-1652. doi:10.1109/tsmcb.2009.2027714Salt, J., Casanova, V., Cuenca, A., & Pizá, R. (2008). Sistemas de Control Basados en Red Modelado y Diseño de Estructuras de Control. Revista Iberoamericana de Automática e Informática Industrial RIAI, 5(3), 5-20. doi:10.1016/s1697-7912(08)70157-2Yang Shi, & Bo Yu. (2009). Output Feedback Stabilization of Networked Control Systems With Random Delays Modeled by Markov Chains. IEEE Transactions on Automatic Control, 54(7), 1668-1674. doi:10.1109/tac.2009.2020638Shi, Y., & Yu, B. (2011). Robust mixed H2/H∞ control of networked control systems with random time delays in both forward and backward communication links. Automatica, 47(4), 754-760. doi:10.1016/j.automatica.2011.01.022Van Loan, C. (1978). Computing integrals involving the matrix exponential. IEEE Transactions on Automatic Control, 23(3), 395-404. doi:10.1109/tac.1978.1101743Khargonekar, P., Poolla, K., & Tannenbaum, A. (1985). Robust control of linear time-invariant plants using periodic compensation. IEEE Transactions on Automatic Control, 30(11), 1088-1096. doi:10.1109/tac.1985.1103841Marti, P., Yepez, J., Velasco, M., Villa, R., & Fuertes, J. M. (2004). Managing Quality-of-Control in Network-Based Control Systems by Controller and Message Scheduling Co-Design. IEEE Transactions on Industrial Electronics, 51(6), 1159-1167. doi:10.1109/tie.2004.837873Tipsuwan, Y., & Chow, M.-Y. (2004). Gain Scheduler Middleware: A Methodology to Enable Existing Controllers for Networked Control and Teleoperation—Part I: Networked Control. IEEE Transactions on Industrial Electronics, 51(6), 1218-1227. doi:10.1109/tie.2004.837866Apkarian, P., & Adams, R. J. (1998). Advanced gain-scheduling techniques for uncertain systems. IEEE Transactions on Control Systems Technology, 6(1), 21-32. doi:10.1109/87.654874Montestruque, L. A., & Antsaklis, P. (2004). Stability of Model-Based Networked Control Systems With Time-Varying Transmission Times. IEEE Transactions on Automatic Control, 49(9), 1562-1572. doi:10.1109/tac.2004.834107Sturm, J. F. (1999). Using SeDuMi 1.02, A Matlab toolbox for optimization over symmetric cones. Optimization Methods and Software, 11(1-4), 625-653. doi:10.1080/1055678990880576