×

Funnel-based adaptive fuzzy finite-time control for non-affine nonlinear systems preceded by unknown actuators. (English) Zbl 1501.93081

Summary: In this paper, an adaptive finite-time funnel control for non-affine strict-feedback nonlinear systems preceded by unknown non-smooth input nonlinearities is proposed. The input nonlinearities include backlash-like hysteresis and dead-zone. Unknown nonlinear functions are handled using fuzzy logic systems (FLS), based on the universal approximation theorem. An improved funnel error surface is utilized to guarantee the steady-state and transient predetermined performances while the differentiability problem in the controller design is averted. Using the Lyapunov approach, all the adaptive laws are extracted. In addition, an adaptive continuous robust term is added to the control input to relax the assumption of knowing the bounds of uncertainties. All the signals in the closed-loop system are shown to be semi-globally practically finite-time bounded with predetermined performance for output tracking error. Finally, comparative numerical and practical examples are provided to authenticate the efficacy and applicability of the proposed scheme.

MSC:

93C40 Adaptive control/observation systems
93C42 Fuzzy control/observation systems
93D40 Finite-time stability
93C10 Nonlinear systems in control theory
93B52 Feedback control
Full Text: DOI

References:

[1] Tong, S.; Li, Y.; Sui, S., Adaptive fuzzy tracking control design for SISO uncertain nonstrict feedback nonlinear systems, IEEE Trans. Fuzzy Syst., 24, 6, 1441-1454 (2016)
[2] Yang, H.; Wang, H., Robust adaptive fault-tolerant control for uncertain nonlinear system with unmodeled dynamics based on fuzzy approximation, Neurocomputing, 173, 1660-1670 (2016)
[3] Du, X.-K.; Zhao, H.; Chang, X.-H., Unknown input observer design for fuzzy systems with uncertainties, Appl. Math. Comput., 266, 108-118 (2015) · Zbl 1410.93069
[4] Du, X.-K.; Zhao, H.; Chang, X.-H., Two novel approaches of UIF design for TS fuzzy system, Neurocomputing, 186, 195-199 (2016)
[5] Ren, H.; Chen, L.; Zhou, Q., Fuzzy control for uncertain electric vehicle systems with sensor failures and actuator saturation, Int. J. Fuzzy Syst., 22, 5, 1444-1453 (2020)
[6] Yu, Q.; Wang, X.; Zong, G.; Zhao, X., Adaptive neural tracking control for a class of uncertain nonstrict-feedback nonlinear systems, J. Frankl. Inst., 354, 15, 6503-6519 (2017) · Zbl 1373.93184
[7] Yin, S.; Yang, H.; Gao, H.; Qiu, J.; Kaynak, O., An adaptive NN-based approach for fault-tolerant control of nonlinear time-varying delay systems with unmodeled dynamics, IEEE Trans. Neural Netw. Learn. Syst., 28, 8, 1902-1913 (2016)
[8] Wang, Y.; Xu, N.; Liu, Y.; Zhao, X., Adaptive fault-tolerant control for switched nonlinear systems based on command filter technique, Appl. Math. Comput., 392, 125725 (2021) · Zbl 1508.93180
[9] Ma, H.; Ren, H.; Zhou, Q.; Lu, R.; Li, H., Approximation-based Nussbaum gain adaptive control of nonlinear systems with periodic disturbances, IEEE Trans. Syst. Man. Cybern. Syst., 52, 4, 2591-2600 (2022)
[10] Jin, X.; Xu, J.-X., Iterative learning control for output-constrained systems with both parametric and nonparametric uncertainties, Automatica, 49, 8, 2508-2516 (2013) · Zbl 1364.93242
[11] Kostarigka, A. K.; Rovithakis, G. A., Adaptive dynamic output feedback neural network control of uncertain MIMO nonlinear systems with prescribed performance, IEEE Trans. Neural Netw. Learn. Syst., 23, 1, 138-149 (2011)
[12] Liu, Y.; Liu, X.; Jing, Y., Adaptive neural networks finite-time tracking control for non-strict feedback systems via prescribed performance, Inf. Sci., 468, 29-46 (2018) · Zbl 1448.93285
[13] Sui, S.; Chen, C. P.; Tong, S., A novel adaptive NN prescribed performance control for stochastic nonlinear systems, IEEE Trans. Neural Netw. Learn. Syst., 32, 7, 3196-3205 (2021)
[14] Liu, Y.-J.; Tong, S., Barrier Lyapunov functions for Nussbaum gain adaptive control of full state constrained nonlinear systems, Automatica, 76, 143-152 (2017) · Zbl 1352.93062
[15] Kim, B. S.; Yoo, S. J., Approximation-based adaptive control of uncertain non-linear pure-feedback systems with full state constraints, IET Control Theory Appl., 8, 17, 2070-2081 (2014)
[16] Bechlioulis, C. P.; Rovithakis, G. A., Robust adaptive control of feedback linearizable MIMO nonlinear systems with prescribed performance, IEEE Trans. Automat. Control, 53, 9, 2090-2099 (2008) · Zbl 1367.93298
[17] Liu, Y.; Liu, X.; Jing, Y., Adaptive fuzzy finite-time stability of uncertain nonlinear systems based on prescribed performance, Fuzzy Sets Syst., 374, 23-39 (2019) · Zbl 1423.93308
[18] Psomopoulou, E.; Theodorakopoulos, A.; Doulgeri, Z.; Rovithakis, G. A., Prescribed performance tracking of a variable stiffness actuated robot, IEEE Trans. Control Syst. Technol., 23, 5, 1914-1926 (2015)
[19] Theodorakopoulos, A.; Rovithakis, G. A., A simplified adaptive neural network prescribed performance controller for uncertain MIMO feedback linearizable systems, IEEE Trans. Neural Netw. Learn. Syst., 26, 3, 589-600 (2014)
[20] Dimanidis, I. S.; Bechlioulis, C. P.; Rovithakis, G. A., Output feedback approximation-free prescribed performance tracking control for uncertain MIMO nonlinear systems, IEEE Trans. Automat. Control (2020) · Zbl 1536.93255
[21] Han, S. I.; Lee, J. M., Fuzzy echo state neural networks and funnel dynamic surface control for prescribed performance of a nonlinear dynamic system, IEEE Trans. Ind. Electron., 61, 2, 1099-1112 (2013)
[22] Tee, K. P.; Ge, S. S.; Tay, E. H., Barrier Lyapunov functions for the control of output-constrained nonlinear systems, Automatica, 45, 4, 918-927 (2009) · Zbl 1162.93346
[23] Li, S.; Ding, L.; Gao, H.; Liu, Y.-J.; Huang, L.; Deng, Z., Adaptive fuzzy finite-time tracking control for nonstrict full states constrained nonlinear system with coupled dead-zone input, IEEE Trans. Cybern. (2020)
[24] Liu, Y.-J.; Tong, S., Barrier Lyapunov functions-based adaptive control for a class of nonlinear pure-feedback systems with full state constraints, Automatica, 64, 70-75 (2016) · Zbl 1329.93088
[25] Yang, Z.; Zhang, X.; Zong, X.; Wang, G., Adaptive fuzzy control for non-strict feedback nonlinear systems with input delay and full state constraints, J. Frankl. Inst. (2020) · Zbl 1447.93184
[26] Han, S.-I.; Lee, J.-M., Recurrent fuzzy neural network backstepping control for the prescribed output tracking performance of nonlinear dynamic systems, ISA Trans., 53, 1, 33-43 (2014)
[27] Ilchmann, A.; Ryan, E. P.; Sangwin, C. J., Tracking with prescribed transient behaviour, ESAIM Control Optim. Calc. Var., 7, 471-493 (2002) · Zbl 1044.93022
[28] Ilchmann, A.; Ryan, E. P., Asymptotic tracking with prescribed transient behaviour for linear systems, Int. J. Control, 79, 8, 910-917 (2006) · Zbl 1103.93033
[29] Ilchmann, A.; Ryan, E. P., High-gain control without identification: a survey, GAMM Mitteilungen, 31, 1, 115-125 (2008) · Zbl 1196.93036
[30] Ilchmann, A.; Ryan, E. P.; Trenn, S., Tracking control: performance funnels and prescribed transient behaviour, Syst. Control Lett., 54, 7, 655-670 (2005) · Zbl 1129.93503
[31] Hackl, C. M., Non-Identifier based Adaptive Control in Mechatronics: Theory and Application, volume 466 (2017), Springer · Zbl 1371.93002
[32] Liu, X.; Wang, H.; Gao, C.; Chen, M., Adaptive fuzzy funnel control for a class of strict feedback nonlinear systems, Neurocomputing, 241, 71-80 (2017)
[33] Wang, H.; Zou, Y.; Liu, P. X.; Liu, X., Robust fuzzy adaptive funnel control of nonlinear systems with dynamic uncertainties, Neurocomputing, 314, 299-309 (2018)
[34] Liu, C.; Liu, X.; Wang, H.; Zhou, Y.; Lu, S., Observer-based adaptive fuzzy funnel control for strict-feedback nonlinear systems with unknown control coefficients, Neurocomputing, 358, 467-478 (2019)
[35] Wang, K.; Liu, Y.; Liu, X.; Jing, Y.; Zhang, S., Adaptive fuzzy funnel congestion control for TCP/AQM network, ISA Trans., 95, 11-17 (2019)
[36] Li, Z.; Chen, X.; Ding, S.; Liu, Y.; Qiu, J., TCP/AWM network congestion algorithm with funnel control and arbitrary setting time, Appl. Math. Comput., 385, 125410 (2020) · Zbl 1508.93172
[37] Wang, S.; Ren, X.; Na, J.; Zeng, T., Extended-state-observer-based funnel control for nonlinear servomechanisms with prescribed tracking performance, IEEE Trans. Autom. Sci. Eng., 14, 1, 98-108 (2016)
[38] Berger, T.; Lê, H. H.; Reis, T., Funnel control for nonlinear systems with higher relative degree, PAMM, 18, 1, e201800059 (2018)
[39] Berger, T.; Lê, H. H.; Reis, T., Funnel control for overhead crane model, PAMM, 18, 1, e201800041 (2018)
[40] Wang, S.; Yu, H.; Yu, J.; Gao, X., Adaptive neural funnel control for nonlinear two-inertia servo mechanisms with backlash, IEEE Access, 7, 33338-33345 (2019)
[41] Wang, S.; Chen, Q.; Ren, X.; Yu, H., Neural network-based adaptive funnel sliding mode control for servo mechanisms with friction compensation, Neurocomputing, 377, 16-26 (2020)
[42] Shao, S.; Zhang, K.; Li, J.; Wang, J., Adaptive predefined performance neural control for robotic manipulators with unknown dead zone, Math. Prob. Eng., 2020 (2020) · Zbl 07348394
[43] Bao, J.; Wang, H.; Xiaoping Liu, P., Adaptive finite-time tracking control for robotic manipulators with funnel boundary, Int. J. Adapt. Control Signal Process., 34, 5, 575-589 (2020) · Zbl 1467.93171
[44] Wang, S.; Na, J.; Ren, X.; Yu, H.; Yu, J., Unknown input observer-based robust adaptive funnel motion control for nonlinear servomechanisms, Int. J. Robust Nonlinear Control, 28, 18, 6163-6179 (2018) · Zbl 1405.93068
[45] Chen, Q.; Tang, X.; Nan, Y.; Ren, X., Finite-time neural funnel control for motor servo systems with unknown input constraint, J. Syst. Sci. Complex., 30, 3, 579-594 (2017) · Zbl 1368.93447
[46] Shi, W.; Luo, R.; Li, B., Adaptive fuzzy prescribed performance control for MIMO nonlinear systems with unknown control direction and unknown dead-zone inputs, ISA Trans., 66, 86-95 (2017)
[47] Malek, S. A.; Shahrokhi, M.; Vafa, E.; Moradvandi, A., Adaptive prescribed performance control of switched MIMO uncertain nonlinear systems subject to unmodeled dynamics and input nonlinearities, Int. J. Robust Nonlinear Control, 28, 18, 5981-5996 (2018) · Zbl 1405.93131
[48] Wang, S.; Yu, H.; Yu, J.; Na, J.; Ren, X., Neural-network-based adaptive funnel control for servo mechanisms with unknown dead-zone, IEEE Trans. Cybern. (2018)
[49] Tang, X.; Chen, Q.; Nan, Y.; Na, J., Backstepping funnel control for prescribed performance of robotic manipulators with unknown dead zone, Proceedings of the 27th Chinese Control and Decision Conference (CCDC), 1508-1513 (2015), IEEE
[50] Liu, C.; Wang, H.; Liu, X.; Zhou, Y., Adaptive fuzzy funnel control for nonlinear systems with input deadzone and saturation, Int. J. Syst. Sci., 1-14 (2020)
[51] Wang, M.; Chai, Y.; Luo, J., A novel prescribed performance controller with unknown dead-zone and impactive disturbance, IEEE Access, 8, 17160-17169 (2020)
[52] Li, H.; Sun, H.; Hou, L., Adaptive fuzzy PI prescribed performance tracking control for switched nonlinear systems with dead-zone input and external disturbances, IEEE Access, 8, 143938-143949 (2020)
[53] Bu, X.; Xiao, Y.; Lei, H., An adaptive critic design-based fuzzy neural controller for hypersonic vehicles: predefined behavioral nonaffine control, IEEE/ASME Trans. Mechatron., 24, 4, 1871-1881 (2019)
[54] Na, J.; Mahyuddin, M. N.; Herrmann, G.; Ren, X.; Barber, P., Robust adaptive finite-time parameter estimation and control for robotic systems, Int. J. Robust Nonlinear Control, 25, 16, 3045-3071 (2015) · Zbl 1327.93285
[55] Ge, S.; Hang, C.; Zhang, T., Nonlinear adaptive control using neural networks and its application to CSTR systems, J. Process Control, 9, 4, 313-323 (1999)
[56] Bu, X., Air-breathing hypersonic vehicles funnel control using neural approximation of non-affine dynamics, IEEE/ASME Trans. Mechatron., 23, 5, 2099-2108 (2018)
[57] Gao, C.; Liu, X.-P.; Wang, H.-Q.; Zhao, N.-N.; Wu, L.-B., Adaptive neural funnel control for a class of pure-feedback nonlinear systems with event-trigger strategy, Int. J. Syst. Sci., 51, 13, 2307-2325 (2020) · Zbl 1483.93272
[58] Chang, Y.; Zhang, S.; Alotaibi, N. D.; Alkhateeb, A. F., Observer-based adaptive finite-time tracking control for a class of switched nonlinear systems with unmodeled dynamics, IEEE Access, 8, 204782-204790 (2020)
[59] Sun, K.; Qiu, J.; Karimi, H. R.; Fu, Y., Event-triggered robust fuzzy adaptive finite-time control of nonlinear systems with prescribed performance, IEEE Trans. Fuzzy Syst., 29, 6, 1460-1471 (2020)
[60] Li, K.; Tong, S.; Li, Y., Finite-time adaptive fuzzy decentralized control for nonstrict-feedback nonlinear systems with output-constraint, IEEE Trans. Syst. Man Cybern. Syst., 50, 12, 5271-5284 (2020)
[61] Sui, S.; Chen, C. P.; Tong, S., Event-trigger-based finite-time fuzzy adaptive control for stochastic nonlinear system with unmodeled dynamics, IEEE Trans. Fuzzy Syst., 29, 7, 1914-1926 (2021)
[62] Liu, C.; Wang, H.; Liu, X.; Zhou, Y., Adaptive finite-time fuzzy funnel control for nonaffine nonlinear systems, IEEE Trans. Syst. Man Cybern. Syst. (2019)
[63] Wang, K.; Jing, Y.; Liu, Y.; Liu, X.; Dimirovski, G. M., Adaptive finite-time congestion controller design of TCP/AQM systems based on neural network and funnel control, Neural Comput. Appl., 1-8 (2019)
[64] 1687814019845464
[65] Chowdhury, D.; Khalil, H. K., Funnel control for nonlinear systems with arbitrary relative degree using high-gain observers, Automatica, 105, 107-116 (2019) · Zbl 1429.93123
[66] Berger, T., Tracking with prescribed performance for linear non-minimum phase systems, Automatica, 115, 108909 (2020) · Zbl 1436.93069
[67] Ilchmann, A.; Ryan, E. P.; Townsend, P., Tracking control with prescribed transient behaviour for systems of known relative degree, Syst. Control Lett., 55, 5, 396-406 (2006) · Zbl 1129.93502
[68] Wang, L.-X., Fuzzy systems are universal approximators, Proceedings of the IEEE International Conference on Fuzzy Systems, 1163-1170 (1992)
[69] Wang, L.-X.; Mendel, J., Fuzzy basis functions, universal approximation, and orthogonal least-squares learning, IEEE Trans. Neural Netw., 3, 5, 807-814 (1992)
[70] Stone, M. H., The generalized weierstrass approximation theorem, Math. Mag., 21, 5, 237-254 (1948)
[71] Guo, Q.; Wang, Q.; Li, X., Finite-time convergent control of electrohydraulic velocity servo system under uncertain parameter and external load, IEEE Trans. Ind. Electron., 66, 6, 4513-4523 (2018)
[72] Shahnazi, R.; Wang, W., Distributed adaptive FBC of uncertain nonaffine multiagent systems preceded by unknown input nonlinearities with unknown gain sign, IEEE Trans. Syst. Man Cybern. Syst. (2018)
[73] Tong, S.; Li, Y., Adaptive fuzzy output feedback control of MIMO nonlinear systems with unknown dead-zone inputs, IEEE Trans. Fuzzy Syst., 21, 1, 134-146 (2012)
[74] Shahnazi, R.; Pariz, N.; Kamyad, A. V., Adaptive fuzzy output feedback control for a class of uncertain nonlinear systems with unknown backlash-like hysteresis, Commun. Nonlinear Sci. Numer. Simul., 15, 8, 2206-2221 (2010) · Zbl 1222.93125
[75] Su, C.-Y.; Stepanenko, Y.; Svoboda, J.; Leung, T.-P., Robust adaptive control of a class of nonlinear systems with unknown backlash-like hysteresis, IEEE Trans. Automat. Control, 45, 12, 2427-2432 (2000) · Zbl 0990.93118
[76] Li, Z.; Li, T.; Feng, G., Adaptive neural control for a class of stochastic nonlinear time-delay systems with unknown dead zone using dynamic surface technique, Int. J. Robust Nonlinear Control, 26, 4, 759-781 (2016) · Zbl 1333.93222
[77] Wang, Y.; Niu, B.; Wang, H.; Alotaibi, N.; Abozinadah, E., Neural network-based adaptive tracking control for switched nonlinear systems with prescribed performance: an average dwell time switching approach, Neurocomputing, 435, 295-306 (2021)
[78] Ge, S. S.; Wang, C., Adaptive NN control of uncertain nonlinear pure-feedback systems, Automatica, 38, 4, 671-682 (2002) · Zbl 0998.93025
[79] Lv, W.; Wang, F., Finite-time adaptive fuzzy tracking control for a class of nonlinear systems with unknown hysteresis, Int. J. Fuzzy Syst., 20, 3, 782-790 (2018)
[80] Polycarpou, M. M.; Ioannou, P. A., A robust adaptive nonlinear control design, Proceedings of the American Control Conference, 1365-1369 (1993), IEEE
[81] Chang, Y.-C.; Chen, B.-S., Robust tracking designs for both holonomic and nonholonomic constrained mechanical systems: adaptive fuzzy approach, IEEE Trans. Fuzzy Syst., 8, 1, 46-66 (2000)
[82] Li, J.; Kumar, K. D., Fault tolerant attitude synchronization control during formation flying, J. Aerosp. Eng., 24, 3, 251-263 (2011)
[83] Bechlioulis, C. P.; Rovithakis, G. A., Robust adaptive fuzzy control of nonaffine systems guaranteeing transient and steady state error bounds, Int. J. Adapt. Control Signal Process., 26, 7, 576-591 (2012) · Zbl 1250.93073
[84] Li, Y.; Tong, S., Adaptive fuzzy output-feedback control of pure-feedback uncertain nonlinear systems with unknown dead zone, IEEE Trans. Fuzzy Syst., 22, 5, 1341-1347 (2013)
[85] Dawson, D. M.; Carroll, J. J.; Schneider, M., Integrator backstepping control of a brush DC motor turning a robotic load, IEEE Trans. Control Syst. Technol., 2, 3, 233-244 (1994)
[86] Wang, Y.; Hu, J.; Wang, J.; Xing, X., Adaptive neural novel prescribed performance control for non-affine pure-feedback systems with input saturation, Nonlinear Dyn., 93, 3, 1241-1259 (2018) · Zbl 1398.93173
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.