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Article

Keywords:
robust control; adaptive control; $H_{\infty }$ method; tube-MPC; surge
Summary:
This paper presents a new robust adaptive model predictive control for a special class of continuous-time non-linear systems with uncertainty. These systems have bounded disturbances with unknown upper bound, as well as constraints on input states. An adaptive control is used in the new controller to estimate the system uncertainty. Also, to avoid the system disturbances, a $H_{\infty }$ method is employed to find the appropriate gain in Tube-MPC. Finally, a surge avoidance problem in centrifugal compressors is solved to show the efficiency and effectiveness of the proposed algorithm.
References:
[1] Bindlish, R.: Nonlinear model predictive control of an industrial polymerization process. Computers Chemical Engrg. 73 (2015), 43-48. DOI 10.1016/j.compchemeng.2014.11.001
[2] Cuzzola, F. A., Geromel, J. C., Morari, M.: An improved approach for constrained robust model predictive control. Automatica 38 (2002), 1183-1189. DOI 10.1016/s0005-1098(02)00012-2 | MR 2133479
[3] Ding, B., Zou, T.: A synthesis approach for output feedback robust model predictive control based-on input-output model. J. Process Control 24 (2014), 60-72. DOI 10.1016/j.jprocont.2013.12.006
[4] Ghanavati, M., Chakravarthy, A.: Demand-side energy management by use of a design-then-approximate controller for aggregated thermostatic loads. In: Amer. Control Conference (ACC), Chicago 2015. DOI 10.1109/acc.2015.7171900
[5] Ghanavati, M., Chakravarthy, A.: Demand-side energy management using an adaptive control strategy for aggregate thermostatic loads. In: AIAA SciTech Forum 2015, pp. 1-7. DOI 10.2514/6.2015-0121
[6] Ghanavati, M., Mobayen, S., Majd, V. J.: A new robust model predictive control strategy for rotational inverted pendulum system. In: Int. Siberian Conference on Control and Communications (SIBCON) 2011, pp. 33-38. DOI 10.1109/sibcon.2011.6072589
[7] Gravdahl, J. T., Egeland, O.: Compressor Surge and Rotating Stall: Modeling and Control. Springer-Verlag, London 1999. DOI 10.1007/978-1-4471-0827-6
[8] Greitzer, E. M.: Surge and rotating stall in axial flow compressors. Part I: Theoretical compression system model. ASME J. Engrg. for Power 98 (1976), 2, 191-198. DOI 10.1115/1.3446138
[9] Gu, B., Gupta, Y. P.: Control of nonlinear processes by using linear model predictive control algorithms. ISA Trans. 47 (2008), 211-216. DOI 10.1016/j.isatra.2007.12.002
[10] He, D. F., Huang, H., Chen, Q. X.: Quasi-min-max MPC for constrained nonlinear systems with guaranteed input-to-state stability. J. Franklin Inst. 351 (2014), 3405-3423. DOI 10.1016/j.jfranklin.2014.03.006 | MR 3201039
[11] Kothare, M. V., Balakrishnan, V., Morari, M.: Robust constrained model predictive control using linear matrix inequalities. Automatica 32 (1996), 1361-1379. DOI 10.1016/0005-1098(96)00063-5 | MR 1420038
[12] Kouvaritakis, B., Rossiter, J. A., Schuurmans, J.: Efficient robust predictive control. IEEE Trans. Automat. Control 45 (2000), 1545-1549. DOI 10.1109/9.871769 | MR 1797413
[13] Magni, L., Nicolao, G. De, Magnani, L., Scattolini, R.: A stabilizing model based predictive control algorithm for nonlinear systems. Automatica 37 (2001), 1351-1362. DOI 10.1016/s0005-1098(01)00083-8 | MR 2110338
[14] Moore, F. K., Greitzer, E. M.: A theory of post-stall transientin axial compression systems: Part I - Development of equations. ASME J. Engrg. for Gas Turbines and Power 108 (1986), 68-76. DOI 10.1115/1.3239887
[15] Poursafar, N., Taghirad, H. D., Haeri, M.: Model predictive control of nonlinear discrete time systems: a linear matrix inequality approach. IET Proc. Control Theory Appl. 4 (2010), 1922-1932. DOI 10.1049/iet-cta.2009.0650 | MR 2760324
[16] Razi, M., Haeri, M.: Design of a robust model predictive controller with reduced computational complexity. ISA Trans. 53 (2014), 1754-1759. DOI 10.1016/j.isatra.2014.09.008
[17] Shamaghdari, S., Nikravesh, S. K. Y., Haeri, M.: Integrated guidance and control of elastic flight vehicle based on robust MPC. Int. J. Robust Nonlinear Control 25 (2015), 2608-2630. DOI 10.1002/rnc.3215 | MR 3397713
[18] Sheng, H., Huang, W., Zhang, T., Huang, X.: Robust Adaptive Fuzzy Control of Compressor Surge Using Backstepping. Arabian J. Science and Engrg. 39 (2014), 9301-9308. DOI 10.1007/s13369-014-1448-1
[19] Wang, L. X.: Adaptive Fuzzy Systems and Control: Design and Stability Analysis. Prentice-Hall, Englewood Cliffs 1994.
[20] Yu, S. Y., Bohm, C., Chen, H., Allgower, F.: Robust model predictive control with disturbance invariant sets. In: Proc. Amer. Contr. Conf., Baltimore 2010, pp. 6262-6267. DOI 10.1109/acc.2010.5531520
[21] Yu, S., Maier, C., Chen, H., Allgower, F.: Tube MPC scheme based on robust control invariant set with application to Lipschitz nonlinear systems. Systems Control Lett. 62 (2013), 194-200. DOI 10.1016/j.sysconle.2012.11.004 | MR 3017875
[22] Zheng, P., Li, D., Xi, Y., Zhang, J.: Improved model prediction and RMPC design for LPV systems with bounded parameter changes. Automatica 49 (2013), 3695-3699. DOI 10.1016/j.automatica.2013.09.024 | MR 3127581
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