NETWORKED ROBUST PREDICTIVE CONTROL SYSTEMS DESIGN WITH PACKET LOSS

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Abstract

The paper addresses problem of designing a robust output feedback model predictive control for uncertain linear systems over networks with packet-loss. The packet-loss process is arbitrary and bounded by the control horizon of model predictive control. Networked predictive control systems with packet loss are modeled as switched linear systems. This enables us to apply the theory of switched systems to establish the stability condition. The stabilizing controller design is based on sufficient robust stability conditions formulated as a solution of bilinear matrix inequality. Finally, a benchmark numerical example-double integrator is given to illustrate the effectiveness of the proposed method.

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  • [1] AZIMI-SADJADI B. : Stability of Networked Control Systems in the Presence of Packet Losses In: Proceedings of the Conference on Decision and Control Hawaii USA 2003 pp. 676-681.

  • [2] CHEN J.-IRWIN-G. W.-McKERNAN A. : Packet-Based Robust mpc for Wireless Networked Control using Co-Design In: American Control Conference Marriott Waterfront Baltimore MD USA 2010 pp. 1829-1834.

  • [3] DING B. : A Synthesis Approach of Model Predictive Control for Linear Systems over Networks with Bounded Packet Loss In: Proceedings of the 8th IEEE International Conference on Control and Automation Xiamen China 2010 pp. 2258-2263.

  • [4] DING B. : Stabilization of Linear Systems over Networks with Bounded Packet Loss and its Use in Synthesizing Model Predictive Control In: Proceedings of 8th International Conference on Control and Automation Xiamen China pp. 2258-2263.

  • [5] FINDEISEN R.-GR¨UNE L.-PANNEK J.-VARUTTI P. : Robustness of Prediction Based Delay Compensation for Nonlinear Systems In: Proceedings of the 18th IFAC World Congress Milano Italy pp. 203-208.

  • [6] GR¨UNE L.-PANNEK J.-WORTHMANN K. : A Networked Unconstrained Nonlinear mpc Scheme In: Proceedings of the European Control Conference 2009 pp. 91-96.

  • [7] GR¨UNE L.-PANNEK J.-WORTHMANN K. : A Prediction Based Control Scheme for Networked Systems with Delays and Packet Dropouts In: Proceedings of the 48th IEEE CDC Shanghai China 2009 pp. 537-542.

  • [8] LEE J. H.-COOLEY B. : Recent advances in model predictive control Chemical Process Control 93 No. 316 (2007) 201-216 AIChE Symposium Series - American Institute of Chemical Engineers.

  • [9] LI Z. J. SUN D. H.-SHI Y. T.-WANG L. F. : A Stabilizing Model Predictive Control for Network Control System with Data Packet Dropout Journal of Control Theory and Application 7 No. 3 (2009) 281-284.

  • [10] LIU G. P.-MU J. X.-REES D. : Networked Predictive Control of Systems with Random Communication Delay In: UKACC 2004 International Conference on Control Bath UK 2004 ID-015.

  • [11] LUNZE J.-LAMNABHI-LAGARRIGUE F. : Handbook of Hybrid Systems Control Cambridge University Press The Edinburgh Building Cambridge CB2 8RU UK 2009.

  • [12] MU J. X.-LIU G. P.-REES D. : Design of Robust Networked Predictive Control Systems In: American Control Conference vol. 1 2005 pp. 638-643.

  • [13] NEŠI´ IC D.-TEEL A. R. : Input-to-State Stability of Networked Control Systems Automatica 40 No. 12 (2004) 2121-2128.

  • [14] NGUYEN Q. T.-VESEL´Y V. : Design of Robust Networked Predictive Control Systems with Packed Loss In: 4th IFAC NMPC’12 August The Netherlands 2012 CD-ROM.

  • [15] NGUYEN Q. T.-VESEL´Y V.-ROSINOVÁ D. : Design of Robust Model Predictive Control with Input Constraints International Journal of Systems Science (2011) http://dx.doi.org/10.1080/00207721.2011.627476.

  • [16] NILSON J. : Real-time Control System with Delays Department of Automatic Control Lund Institute of Technology Lund Sweden 1998.

  • [17] QIN S. J.-BADGEWELL T. : An Overview of Industrial Model Predictive Control Technology Chemical Process Control 93 No. 316 (1997) 232-256 AIChe Symposium Series - American Institute of Chemical Engineers.

  • [18] RAY A.-HALEVY Y. : Integrated Communication and Control Systems: Part ii Design Considerations ASME Journal of Dynamic Systems Measurement and Control 110 (1988) 374-381.

  • [19] ROHAL-ILKIV B. : A Note on Calculation of Polytopic Invariant and Feasible Sets for Linear Continuous-Time Systems Annual Review in Control 28 (2004) 59-64.

  • [20] ROSINOVÁ D.-VESEL´Y V.-KUˇCERA V. : A necessary and Sufficient Condition for Static Output Feedback Stabilizability of Linear Discrete-Time Systems Kybernetika 39 No. 4 (2003) 447-459.

  • [21] SEILER P.-SENGUPTA R. : An h1 Approach to Networked Control IEEE Transactions on Automatic Control 50 (2005) 356-364.

  • [22] SRINIVASAGUTA D.-SCHATTLER H.-JOSEPH B. : Time-Stamped Model Predictive Control of Processes with Random Delays Computer and Chemical Engineering 28 No. 3 (2004) 1337-1346.

  • [23] TANG P. L.-de SILVA C. W. : Ethernet-Based Predictive Control for an Industrial Hydraulic Machine In: Proceedings of IEEE Conference on Decision and Control vol. 1 2003 pp. 695-700.

  • [24] TANG P. L.-de SILVA C. W. : Stability and Optimality of Constrained Model Predictive Control with Future Input Buffering in networked Control Systems In: American Control Conference vol. 2 2005 pp. 1245-1250.

  • [25] VESEL´Y V.-ROSINOVÁ D.-FOLTIN M. : Robust Model Predictive Control Design with Input Constraints ISA Transactions 49 (2010) 114-12.

  • [26] WALSH G. C.-YE H.-BUSHNELL L. : Stability Analysis of Networked Control Systems In: Proceedings of the American Control Conference 1999 pp. 2876-2880.

  • [27] XIONG J.-LAM J. : Stabilization of Linear Systems over Networks with Bounded Packet Loss Automatica 43 (2007) 80-87.

  • [28] YU M.-WANG L.-CHU T.-XIE G. : Stabilization of Networked Control Systems with Data Packet Dropout and Network Delays via Switching System Approach In: 43rd IEEE conference on decision and control Atlantis Paradise Island ahamas 2004 pp. 3539-3544.

  • [29] ZHANG W.-BRANICKY M. S.-PHILIP S. M. : Stability of Networked Control Systems IEEE Control System Magazine 21 No. 1 (2001) 84-89.

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