\r\ncontrol method is presented for mobile robots which is modeled as

\r\nconstrained continuous-time linear parameter varying (LPV) systems.

\r\nThe presented sampled-data predictive controller is designed by linear

\r\nmatrix inequality approach. Based on the input delay approach, a

\r\ncontroller design condition is derived by constructing a new Lyapunov

\r\nfunction. Finally, a numerical example is given to demonstrate the

\r\neffectiveness of the presented method.","references":"[1] W. Lucia, F. Tedesco. \u201dA networked-based receding horizon scheme for\r\nconstrained LPV systems,\u201d European Journal of Control, vol. 25, pp.\r\n69-75, 2015.\r\n[2] S. Lee, Ju H. Park, D. Ji, S. Won, \u201dRobust model predictive control for\r\nLPV systems using relaxation matrices,\u201d IET. Control Theory Appl., vol.\r\n1, no. 6, pp. 1567-1573, 2007.\r\n[3] A. Seuret, F. Gouaisbaut, Wirtinger-based integral inequality: application\r\nto time-delay systems, Automatica, vol. 49, no. 8, pp. 2860-2866, 2013.\r\n[4] S. Lee, O. Kwon, Quantised MPC for LPV systems by using new\r\nLyapunovKrasovskii functional, IET. Control Theory Appl., vol. 11, no.\r\n3, pp. 439-445, 2017.\r\n[5] D. Yue, E. Tian, Y. Zhang, and C. Peng, \u201cDelay-distribution-dependent\r\nstability and stabilization of T-S fuzzy systems with probabilistic interval\r\ndelay,\u201d IEEE Transactions on Systems, Man, and Cybernetics, Part B\r\n(Cybernetics), vol. 39, no. 2, pp. 503\u2013516, 2009.\r\n[6] C.K. Zhang, Y. He, L. Jiang, W. Lin, M. Wu, \u201dDelay-dependent stability\r\nanalysis of neural networks with time-varying delay: A generalized\r\nfree-weighting-matrix,\u201d Applied Mathematics and Computation, vol. 294,\r\nno. 1, pp. 102-120, 2017.\r\n[7] E. Fridman and M. Dambrine, \u201cControl under quantization, saturation and\r\ndelay: An LMI approach,\u201d Automatica, vol. 45, no. 10, pp. 2258\u20132264,\r\n2009.","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 124, 2017"}