22,885 research outputs found

    H∞ control for networked systems with random communication delays

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    Copyright [2006] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.This note is concerned with a new controller design problem for networked systems with random communication delays. Two kinds of random delays are simultaneously considered: i) from the controller to the plant, and ii) from the sensor to the controller, via a limited bandwidth communication channel. The random delays are modeled as a linear function of the stochastic variable satisfying Bernoulli random binary distribution. The observer-based controller is designed to exponentially stabilize the networked system in the sense of mean square, and also achieve the prescribed H∞ disturbance attenuation level. The addressed controller design problem is transformed to an auxiliary convex optimization problem, which can be solved by a linear matrix inequality (LMI) approach. An illustrative example is provided to show the applicability of the proposed method

    A non-uniform predictor-observer for a networked control system

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    The final publication is available at Springer via http://dx.doi.org/10.1007/s12555-011-0621-5This paper presents a Non-Uniform Predictor-Observer (NUPO) based control approach in order to deal with two of the main problems related to Networked Control Systems (NCS) or Sensor Networks (SN): time-varying delays and packet loss. In addition, if these delays are longer than the sampling period, the packet disordering phenomenon can appear. Due to these issues, a (scarce) nonuniform, delayed measurement signal could be received by the controller. But including the NUPO proposal in the control system, the delay will be compensated by the prediction stage, and the nonavailable data will be reconstructed by the observer stage. So, a delay-free, uniformly sampled controller design can be adopted. To ensure stability, the predictor must satisfy a feasibility problem based on a time-varying delay-dependent condition expressed in terms of Linear Matrix Inequalities (LMI). Some aspects like the relation between network delay and robustness/performance trade-off are empirically studied. A simulation example shows the benefits (robustness and control performance improvement) of the NUPO approach by comparison to another similar proposal. © ICROS, KIEE and Springer 2011.This work was supported by the Spanish Ministerio de Ciencia y Tecnologia Projects DPI2008-06737-C02-01 and DPI2009-14744-C03-03, by Generalitat Valenciana Project GV/2010/018, by Universidad Politecnica de Valencia Project PAID06-08.Cuenca Lacruz, ÁM.; García Gil, PJ.; Albertos Pérez, P.; Salt Llobregat, JJ. (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/s12555-011-0621-5S1194120296K. Ogata, Discrete-time Control Systems, Prentice-Hall, Inc., Upper Saddle River, NJ, USA, 1987.Y. Tipsuwan and M. Chow, “Control methodologies in networked control systems,” Control Eng. Practice, vol. 11, no. 10, pp. 1099–1111, 2003.T. Jia, Y. Niu, and X. Wang, “H ∞ control for networked systems with data packet dropout,” Int. J. Control, Autom., and Syst., vol. 8, no. 2, pp. 198–203, 2010.Y. Wang and G. Yang, “Robust H ∞ model reference tracking control for networked control systems with communication constraints,” Int. J. Control, Autom., and Syst., vol. 7, no. 6, pp. 992–1000, 2009.H. Gao and T. Chen, “Network-based H ∞ output tracking control,” IEEE Trans. Autom. Control, vol. 53, no. 3, pp. 655–667, 2008.H. Karimi, “Robust H ∞ filter design for uncertain linear systems over network with network-induced delays and output quantization,” Modeling, Identification and Control, vol. 30, no. 1, pp. 27–37, 2009.H. R. Karimi, “Delay-range-dependent linear matrix inequality approach to quantized H ∞ control of linear systems with network-induced delays and norm-bounded uncertainties,” Proc. of the Inst. of Mech. Eng., Part I: J. of Syst. and Control Eng., vol. 224, no. 6, pp. 689–700, 2010.K. Lee, S. Lee, and M. Lee, “Remote fuzzy logic control of networked control system via Profibus-DP,” IEEE Trans. Ind. Electron., vol. 50, no. 4, pp. 784–792, 2003.Y. Tipsuwan and M.-Y. Chow, “Gain scheduler middleware: a methodology to enable existing controllers for networked control and teleoperationpart I: networked Control,” IEEE Trans. on Industrial Electronics, vol. 51, no. 6, pp. 1218–1227, December 2004.A. Sala, A. Cuenca, and J. Salt, “A retunable PID multi-rate controller for a networked control system,” Inform. Sci., vol. 179, no. 14, pp. 2390–2402, June 2009.A. Cuenca, J. Salt, V. Casanova, and R. Piza, “An approach based on an adaptive multi-rate Smith predictor and gain scheduling for a networked control system: implementation over Profibus-DP,” Int. J. Control, Autom., and Syst., vol. 8, no. 2, pp. 473–481, April 2010.A. Cuenca, J. Salt, A. Sala, and R. Piza, “A delay-dependent dual-rate PID controller over an Ethernet network,” IEEE Trans. Ind. Informat., vol. 7, no. 1, pp. 18–29, Feb. 2011.Y. Tian and D. Levy, “Compensation for control packet dropout in networked control systems,” Inform. Sci., vol. 178, no. 5, pp. 1263–1278, 2008.Y. Zhao, G. Liu, and D. Rees, “Modeling and stabilization of continuous-time packet-based networked control systems.” IEEE Trans. Syst., Man, Cybern. B, vol. 39, no. 6, pp. 1646–1652, Dec. 2009.X. Zhao, S. Fei, and C. Sun, “Impulsive controller design for singular networked control systems with packet dropouts,” Int. J. Control, Autom., and Syst., vol. 7, no. 6, pp. 1020–1025, 2009.H. Gao and T. Chen, “H ∞ estimation for uncertain systems with limited communication capacity,” IEEE Trans. Autom. Control, vol. 52, no. 11, pp. 2070–2084, 2007.S. Oh, L. Schenato, P. Chen, and S. Sastry, “Tracking and coordination of multiple agents using sensor networks: System design, algorithms and experiments,” Proc. of the IEEE, vol. 95, no. 1, pp. 234–254, 2007.M. Moayedi, Y. Foo, and Y. Soh, “Optimal and suboptimal minimum-variance filtering in networked systems with mixed uncertainties of random sensor delays, packet dropouts and missing measurements,” Int. J. Control, Autom., and Syst., vol. 8, no. 6, pp. 1179–1188, 2010.W. Zhang, M. Branicky, and S. Phillips, “Stability of networked control systems,” IEEE Control Syst. Mag., vol. 21, no. 1, pp. 84–99, 2001.J. Hespanha, P. Naghshtabrizi, and Y. Xu, “A survey of recent results in networked control systems,” Proc. of the IEEE, vol. 95, no. 1, pp. 138–162, 2007.J. Baillieul and P. Antsaklis, “Control and communication challenges in networked real-time systems,” Proc. of the IEEE, vol. 95, no. 1, pp. 9–28, 2007.P. Garcia, P. Castillo, R. Lozano, and P. Albertos, “Robustness with respect to delay uncertainties of a predictor-observer based discrete-time controller,” Proc. of the 45th IEEE Conf. on Decision and Control, pp. 199–204, 2006.C. Lien, “Robust observer-based control of systems with state perturbations via LMI approach,” IEEE Trans. Autom. Control, vol. 49, no. 8, pp. 1365–1370, 2004.A. Sala, “Computer control under time-varying sampling period: an LMI gridding approach,” Automatica, vol. 41, no. 12, pp. 2077–2082, Dec. 2005.J. Li, Q. Zhang, Y. Wang, and M. Cai, “H ∞ control of networked control systems with packet disordering,” IET Control Theory Appl., vol. 3, no. 11, pp. 1463–1475, March 2009.Y. Zhao, G. Liu, and D. Rees, “Improved predictive control approach to networked control systems,” IET Control Theory Appl., vol. 2, no. 8, pp. 675–681, Aug. 2008.K. Astrom, “Event based control,” Analysis and Design of Nonlinear Control Systems, pp. 127–147, 2007.A. Cuenca, P. García, K. Arzén, and P. Albertos, “A predictor-observer for a networked control system with time-varying delays and non-uniform sampling,” Proc. Eur. Control Conf., pp. 946–951, 2009.J. Xiong and J. Lam, “Stabilization of linear systems over networks with bounded packet loss,” Automatica, vol. 43, no. 1, pp. 80–87, 2007.H. Song, L. Yu, and A. Liu, “H ∞ filtering for network-based systems with communication constraints and packet dropouts,” Proc. of the 7th Asian Control Conf., pp. 220–225, 2009.P. Garcia, A. Gonzalez, P. Castillo, R. Lozano, and P. Albertos, “Robustness of a discrete-time predictor-based controller for time-varying measurement delay,” Proc. of the 9th IFAC Workshop on Time Delay Systems, 2010.J. Sturm, “Using SeDuMi 1.02, a MATLAB toolbox for optimization over symmetric cones,” Optimization methods and software, vol. 11, no. 1, pp. 625–653, 1999.T. Henningsson and K. Astrom, “Log-concave observers,” Proc. of the 17th Int. Symp. on Mathematical Theory of Networks and Systems, pp. 2163–2170, 2006.D. Davison and E. Hwang, “Automating radiotherapy cancer treatment: use of multirate observer-based control,” Proc. of American Control Conf., vol. 2, pp. 1194–1199, 2003

    Linear matrix inequalities in multirate control over networks

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    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 HH_{\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. 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    H∞ control for 2-D time-delay systems with randomly occurring nonlinearities under sensor saturation and missing measurements

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    In this paper, the H∞ output-feedback control problem is investigated for a class of two-dimensional (2-D) nonlinear systems with time-varying delays under imperfect measurements. Randomly occurring nonlinearities (RONs) are introduced in the system to account for probabilistic nonlinear disturbances typically caused by networked environments and governed by a sequence of random variables obeying the Bernoulli distribution. The imperfect measurement outputs are subject to both data missing and randomly occurring sensor saturations (ROSSs), which are put forward to characterize the network-induced phenomena such as probabilistic communication failures and limited capacity of the communication devices. The aim of this paper is to design an output-feedback controller such that the closed-loop system is globally asymptotically stable in the mean square and the prescribed H∞ performance index is satisfied. Sufficient conditions are presented by resorting to intensive stochastic analysis and matrix inequality techniques, which not only guarantee the existence of the desired controllers for all possible time-delays, RONs, missing measurements and ROSSs but also lead to the explicit expressions of such controllers. Finally, a numerical simulation example is given to demonstrate the applicability of the proposed control scheme.This work was supported in part by the National Natural Science Foundation of China under Grants 61174136, 61134009 and 61329301, the Natural Science Foundation of Jiangsu Province of China under Grant BK20130017, the “333 Project” Foundation of Jiangsu Province, the Programme for New Century Excellent Talents in University under Grant NCET-12-0117, the Royal Society of the U.K., and the Alexander von Humboldt Foundation of Germany

    Robust H∞ filtering for a class of nonlinear networked systems with multiple stochastic communication delays and packet dropouts

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    Copyright [2010] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.In this paper, the robust H∞ filtering problem is studied for a class of uncertain nonlinear networked systems with both multiple stochastic time-varying communication delays and multiple packet dropouts. A sequence of random variables, all of which are mutually independent but obey Bernoulli distribution, are introduced to account for the randomly occurred communication delays. The packet dropout phenomenon occurs in a random way and the occurrence probability for each sensor is governed by an individual random variable satisfying a certain probabilistic distribution in the interval. The discrete-time system under consideration is also subject to parameter uncertainties, state-dependent stochastic disturbances and sector-bounded nonlinearities. We aim to design a linear full-order filter such that the estimation error converges to zero exponentially in the mean square while the disturbance rejection attenuation is constrained to a give level by means of the H∞ performance index. Intensive stochastic analysis is carried out to obtain sufficient conditions for ensuring the exponential stability as well as prescribed H∞ performance for the overall filtering error dynamics, in the presence of random delays, random dropouts, nonlinearities, and the parameter uncertainties. These conditions are characterized in terms of the feasibility of a set of linear matrix inequalities (LMIs), and then the explicit expression is given for the desired filter parameters. Simulation results are employed to demonstrate the effectiveness of the proposed filter design technique in this paper.This work was supported in part by the Engineering and Physical Sciences Research Council (EPSRC) of the U.K. under Grant GR/S27658/01, the Royal Society of the U.K., the Alexander von Humboldt Foundation of Germany, National Natural Science Foundation of China under Grant 60825303, 60834003, 973 Project under Grant 2009CB320600, Fok Ying Tung Education Foundation under Grant 111064, and the Youth Science Fund of Heilongjiang Province under Grant QC2009C63

    Analysis, filtering, and control for Takagi-Sugeno fuzzy models in networked systems

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    Copyright © 2015 Sunjie Zhang 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.The fuzzy logic theory has been proven to be effective in dealing with various nonlinear systems and has a great success in industry applications. Among different kinds of models for fuzzy systems, the so-called Takagi-Sugeno (T-S) fuzzy model has been quite popular due to its convenient and simple dynamic structure as well as its capability of approximating any smooth nonlinear function to any specified accuracy within any compact set. In terms of such a model, the performance analysis and the design of controllers and filters play important roles in the research of fuzzy systems. In this paper, we aim to survey some recent advances on the T-S fuzzy control and filtering problems with various network-induced phenomena. The network-induced phenomena under consideration mainly include communication delays, packet dropouts, signal quantization, and randomly occurring uncertainties (ROUs). With such network-induced phenomena, the developments on T-S fuzzy control and filtering issues are reviewed in detail. In addition, some latest results on this topic are highlighted. In the end, conclusions are drawn and some possible future research directions are pointed out.This work was supported in part by the National Natural Science Foundation of China under Grants 61134009, 61329301, 11301118 and 61174136, the Natural Science Foundation of Jiangsu Province of China under Grant BK20130017, the Fundamental Research Funds for the Central Universities of China under Grant CUSF-DH-D-2013061, the Royal Society of the U.K., and the Alexander von Humboldt Foundation of Germany

    On general systems with network-enhanced complexities

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    In recent years, the study of networked control systems (NCSs) has gradually become an active research area due to the advantages of using networked media in many aspects such as the ease of maintenance and installation, the large flexibility and the low cost. It is well known that the devices in networks are mutually connected via communication cables that are of limited capacity. Therefore, some network-induced phenomena have inevitably emerged in the areas of signal processing and control engineering. These phenomena include, but are not limited to, network-induced communication delays, missing data, signal quantization, saturations, and channel fading. It is of great importance to understand how these phenomena influence the closed-loop stability and performance properties
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