Abstract
In this paper, a novel adaptive neural network control approach is presented for a class of uncertain discrete-time nonlinear strict-feedback systems with input saturation. By combining single neural network approximation and minimal learning parameter technique, the proposed approach is able to eliminate the complexity growing problem and alleviate the explosion of learning parameters. An auxiliary design system is incorporated into the control scheme to overcome the problem of input saturation constraints. Following this approach, the designed controller contains only one actual control law and one adaptive law, the numbers of input variables and weights of neural network updated online are decreased drastically, and the number of parameter updated online for whole system is reduced to only one. Compared with the existing methods, the adaptive mechanism with much simpler controller structure and minimal learning parameterization is achieved; therefore, the computational burden is lighter. It is shown via Lyapunov theory that all signals in the closed-loop system are uniformly ultimately bounded. Finally, simulation results via two examples are employed to illustrate the effectiveness and merits of the proposed scheme.
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References
Park, J., Sandberg, I.W.: Universal approximation using radial-basis-function network. Neural Comput. 3(2), 246–257 (1991)
Polycarpou, M.M.: Stable adaptive neural control scheme for nonlinear systems. IEEE Trans. Autom. Control 41(3), 447–451 (1996)
Polycarpou, M.M., Mears, M.J.: Stable adaptive tracking of uncertain systems using nonlinearly parametrized on-line approximators. Int. J. Control 70(3), 363–384 (1998)
Zhang, T., Ge, S.S., Hang, C.C.: Adaptive neural network control for strict-feedback nonlinear systems using backstepping design. Automatica 36(7), 1835–1846 (2000)
Ge, S.S., Hang, C.C., Lee, T.H.: Stable Adaptive Neural Network Control. Kluwer, Norwell (2001)
Ge, S.S., Wang, C.: Direct adaptive NN control of a class of nonlinear systems. IEEE Trans. Neural Netw. 13(1), 214–221 (2002)
Song, Y., Grizzle, J.W.: Adaptive output-feedback control of a class of discrete time nonlinear systems. In: Proceedings of American Control Conference, pp. 1359–1364 (1993)
Yeh, P.C., Kokotovic, P.V.: Adaptive control of a class of nonlinear discrete-time systems. Int. J. Control 62(2), 303–324 (1995)
Ge, S.S., Li, G.Y., Lee, T.H.: Adaptive NN control for a class of strict-feedback discrete-time nonlinear systems. Automatica 39(5), 807–819 (2003)
Ge, S.S., Li, G.Y., Lee, T.H.: Correction to adaptive NN control for a class of strict-feedback discrete-time nonlinear systems. Automatica 44(7), 1930–1931 (2008)
Ge, S.S., Lee, T.H., Li, G.Y., Zhang, J.: Adaptive NN control for a class of discrete-time nonlinear systems. Int. J. Control 76(4), 334–354 (2003)
Ge, S.S., Zhang, J., Lee, T.H.: Adaptive neural networks control for a class of MIMO nonlinear systems with disturbances in discrete-time. IEEE Trans. Syst. Man Cybern. Part B Cybern. 34(4), 1630–1645 (2004)
Zhang, J., Ge, S.S., Lee, T.H.: Output feedback control of a class of discrete MIMO nonlinear systems with triangular form inputs. IEEE Trans. Neural Netw. 16(6), 1491–1503 (2005)
Alanis, A.Y., Sanchez, E.N., Loukianov, A.G.: Discrete-time adaptive backstepping nonlinear control via high-order neural networks. IEEE Trans. Neural Netw. 18(4), 1185–1195 (2007)
Ge, S.S., Yang, C., Lee, T.H.: Adaptive robust control of a class of nonlinear strict-feedback discrete-time systems with unknown control directions. Syst. Control Lett. 57(6), 888–995 (2008)
Yang, C.G., Ge, S.S., Xiang, C., Chai, T.Y., Lee, T.H.: Output feedback NN control for two classes of discrete-time systems with unknown control directions in a unified approach. IEEE Trans. Neural Netw. 19(6), 1873–1886 (2008)
Chen, W.: Adaptive NN control for discrete-time pure-feedback systems with unknown control direction under amplitude and rate actuator constraints. ISA Trans. 48(3), 304–311 (2009)
Liu, Y.J., Chen, C.L.P., Wen, G.X., Tong, S.C.: Adaptive neural output feedback tracking control for a class of uncertain discrete-time nonlinear systems. IEEE Trans. Neural Netw. 22(7), 1162–1167 (2011)
Wang, D., Huang, J.: Neural network based adaptive dynamic surface control for nonlinear systems in strict-feedback form. IEEE Trans. Neural Netw. 16(1), 195–202 (2005)
Zhang, T.P., Ge, S.S.: Adaptive dynamic surface control of nonlinear systems with unknown dead zone in pure feedback form. Automatica 44(7), 1895–1903 (2008)
Sun, G., Wang, D., Li, T.S., Peng, Z., Wang, H.: Single neural network approximation based adaptive control for a class of nonlinear systems in strict-feedback form. Nonlinear Dyn. 72(1), 175–184 (2013)
Sun, G., Wang, D., Peng, Z.H.: Adaptive control based on single neural network approximation for nonlinear pure-feedback systems. IET Control Theory Appl. 6(10), 2387–2396 (2012)
Wang, X., Li, T.S., Chen, C.L.P.: Adaptive robust control based on single neural network approximation for a class of uncertain strict-feedback discrete-time nonlinear systems. Neurocomputing 138, 325–331 (2014)
Chen, B., Liu, X.P., Liu, K.F., Lin, C.: Direct adaptive fuzzy control of nonlinear strict-feedback systems. Automatica 45(6), 1530–1535 (2009)
Li, T.S., Wang, D., Feng, G., Tong, S.C.: A DSC approach to robust adaptive NN tracking control for strict-feedback non-linear systems. IEEE Trans. Syst. Man Cybern. Part B Cybern. 40(3), 915–927 (2010)
Li, T.S., Tong, S.C., Feng, G.: A Novel robust adaptive-fuzzy-tracking control for a class of nonlinear multi-input/multi-output systems. IEEE Trans. Fuzzy Syst. 18(1), 150–160 (2010)
Liu, Y.J., Wen, G.X., Tong, S.C.: Direct adaptive NN control for a class of discrete-time nonlinear strict-feedback systems. Neurocomputing 73(13–15), 2498–2505 (2010)
Li, T.S., Li, R., Li, J.: Decentralized adaptive neural control of nonlinear interconnected large-scale systems with unknown time delays and input saturation. Neurocomputing 74(14–15), 2277–2283 (2011)
Li, Y.M., Tong, S.C., Li, T.S.: Direct adaptive fuzzy backstepping control of uncertain nonlinear systems in the presence of input saturation. Neural Comput. Appl. 23(5), 1207–1216 (2013)
Li, Y.M., Tong, S.C., Li, T.S.: Adaptive fuzzy output-feedback control for output constrained nonlinear systems in the presence of input saturation. Fuzzy Sets Syst. 248, 138–155 (2014)
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This work was supported in part by the National Natural Science Foundation of China (Grant No. 51309041) and Scientific Research Foundation of Graduate School of Dalian Maritime University (Grant No. 2014YB04).
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Wang, X., Liu, Z. & Cai, Y. Adaptive single neural network control for a class of uncertain discrete-time nonlinear strict-feedback systems with input saturation. Nonlinear Dyn 82, 2021–2030 (2015). https://doi.org/10.1007/s11071-015-2296-6
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DOI: https://doi.org/10.1007/s11071-015-2296-6