Abstract
This paper considers the yaw-moment control issue for uncertain electric vehicle systems with sensor failures and actuator saturation. By employing the interval type-2 (IT2) fuzzy approach, the uncertain electric vehicle systems are constructed as an IT2 fuzzy model. In this model, the parameter uncertainties are described through the membership functions (MFs) with lower and upper bounds. Then, an IT2 fuzzy state-feedback controller, which can share different MFs with the IT2 fuzzy model, is designed. The sensor failures can be quantified by a variable varying in a given interval. Meanwhile, the saturation nonlinearities can be handled by employing a norm-bounded strategy. By means of the Lyapunov stability approach, sufficient conditions of the controller design are derived to achieve the desired performance. Finally, simulation results based on the electric vehicle systems are presented to demonstrate the effectiveness of the proposed control scheme.
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References
Chan, C.C., Bouscayrol, A., Chen, K.: Electric, hybrid, and fuel-cell vehicles: architectures and modeling. IEEE Trans. Veh. Technol. 59(2), 589–598 (2010)
Jing, H., Wang, R., Wang, J., Nan, C.: Robust \(H_{\infty }\) dynamic output-feedback control for four-wheel independently actuated electric ground vehicles through integrated AFS/DYC. J. Frankl. Inst. 355(18), 9321–9350 (2018)
Zhao, X., Mo, H., Yan, K., Li, L.: Type-2 fuzzy control for driving state and behavioral decisions of unmanned vehicle. IEEE/CAA J. Autom. Sinica. 7(1), 178–186 (2019)
Liu, Q., Zhang, H., Leng, J., Chen, X.: Digital twin-driven rapid individualised designing of automated flow-shop manufacturing system. Int. J. Prod. Res. 57(12), 3903–3919 (2019)
Leng, J., Zhang, H., Yan, D., Liu, Q., Chen, X., Zhang, D.: Digital twin-driven manufacturing cyber-physical system for parallel controlling of smart workshop. J. Ambient. Intell. Humanized. Comput. 10(3), 1155–1166 (2019)
Wang, J., Longoria, R.G.: Coordinated and reconfigurable vehicle dynamics control. IEEE Trans. Control. Syst. Technol. 17(3), 723–732 (2009)
Boada, B.L., Boada, M.J.L., Diaz, V.: Fuzzy-logic applied to yaw moment control for vehicle stability. Veh. Syst. Dyn. 43(10), 753–770 (2005)
Yang, X., Wang, Z., Peng, W.: Coordinated control of AFS and DYC for vehicle handling and stability based on optimal guaranteed cost theory. Veh Syst Dyn 47(1), 57–79 (2009)
Esmailzadeh, E., Goodarzi, A., Vossoughi, G.R.: Optimal yaw moment control law for improved vehicle handling. Mechatronics 13(7), 659–675 (2003)
Chen, L., Li, X., Xiao, W., Li, P., Zhou, Q.: Fault-tolerant control for uncertain vehicle active steering systems with time-delay and actuator fault. Int. J. Control. Autom. Syst. 17(9), 2234–2241 (2019)
Wang, R., Jing, H., Hu, C., Chadli, M., Yan, F.: Robust \(H_{\infty }\) output-feedback yaw control for in-wheel motor driven electric vehicles with differential steering. Neurocomputing 173(3), 676–684 (2016)
Kazemi, R., Janbakhsh, A.A.: Nonlinear adaptive sliding mode control for vehicle handling improvement via steer-by-wire. Int. J. Autom. Technol. 11(3), 345–354 (2010)
Chao, H., Naghdy, F., Du, H.: Observer-based fault tolerant controller for uncertain steer-by-wire systems using the delta operator. IEEE/ASME Trans. Mechatron. 23(6), 2587–2598 (2018)
Mirzaei, M.: A new strategy for minimum usage of external yaw moment in vehicle dynamic control system. Trans. Res. Part C 18(2), 213–224 (2010)
Wang, W., Liang, H., Pan, Y., Li, T.: Prescribed performance adaptive fuzzy containment control for nonlinear multi-agent systems using disturbance observer. IEEE Trans. Cybern. (2020). https://doi.org/10.1109/TCYB.2020.2969499
Zhou, Q., Du, P., Li, H., Lu, R., Yang, J.: Adaptive fixed-time control of error-constrained pure-feedback interconnected nonlinear systems. IEEE Trans. Syst. Man Cybern. Syst. (2019). https://doi.org/10.1109/TSMC.2019.2961371
Commault, C., Dion, J.M., Trinh, D.H.: Observability preservation under sensor failure. IEEE Trans. Autom. Control 53(6), 1554–1559 (2008)
Zhang, Z., Liang, H., Ma, H., Pan, Y.: Reliable fuzzy control for uncertain vehicle suspension systems with random incomplete transmission signals and sensor failure. Mech. Syst. Signal Process. 130, 776–789 (2019)
Su, X., Shi, P., Wu, L., Basin, M.V.: Reliable filtering with strict dissipativity for T-S fuzzy time-delay systems. IEEE Trans. Cybern. 44(12), 2470–2483 (2014)
Tian, E., Yue, D., Yang, T.C., Gu, Z., Lu, G.: T-S fuzzy model-based robust stabilization for networked control systems with probabilistic sensor and actuator failure. IEEE Trans. Fuzzy Syst. 19(3), 553–561 (2011)
Li, Y., Tong, S.: Fuzzy adaptive backstepping decentralized control for switched nonlinear large-scale systems with switching jumps. Int. J. Fuzzy Syst. 17(1), 12–21 (2015)
Lv, Y., Hu, Q., Ma, G., Zhou, J.: 6 DOF synchronized control for spacecraft formation flying with input constraint and parameter uncertainties. ISA Transact. 50(4), 573–580 (2011)
Zhou, Q., Wang, W., Ma, H., Li, H.: Event-triggered fuzzy adaptive containment control for nonlinear multi-agent systems with unknown bouc-wen hysteresis input. IEEE Trans. Fuzzy Syst. (2019). https://doi.org/10.1109/TFUZZ.2019.2961642
Bai, W., Zhou, Q., Li, T., Li, H.: Adaptive reinforcement learning neural network control for uncertain nonlinear system with input saturation. IEEE Trans. Cybern. (2019). https://doi.org/10.1109/TCYB.2019.292105
Du, H., Zhang, N., Dong, G.: Stabilizing vehicle lateral dynamics with considerations of parameter uncertainties and control saturation through robust yaw control. IEEE Trans. Veh. Technol. 59(5), 2593–2597 (2010)
Li, H., Wang, J., Shi, P.: Output-feedback based sliding mode control for fuzzy systems with actuator saturation. IEEE Trans. Fuzzy Syst. 24(6), 1282–1293 (2016)
Sun, W., Zhao, Z., Gao, H.: Saturated adaptive robust control for active suspension systems. IEEE Trans. Ind. Electron. 60(9), 3889–3896 (2013)
Chen, L., Li, P., Lin, W., Zhou, Q.: Observer-based fuzzy control for four-wheel independently driven electric vehicles with active steering systems. Int. J. Fuzzy Syst. 22(1), 89–100 (2020)
Wang, N., Sun, Z., Su, S.F., Wang, Y.: Fuzzy uncertainty observer-based path-following control of underactuated marine vehicles with unmodeled dynamics and disturbances. Int. J. Fuzzy Syst. 20(8), 2593–2604 (2018)
Zhou, Q., Wang, W., Liang, H., Basin, M., Wang, B.: Observer-based event-triggered fuzzy adaptive bipartite containment control of multi-agent systems with input quantization. IEEE Trans. Fuzzy Syst. (2019). https://doi.org/10.1109/TFUZZ.2019.2953573
Tong, M., Lin, W., Huo, X., Jin, Z., Miao, C., Wang, B.: A model-free fuzzy adaptive trajectory tracking control algorithm based on dynamic surface control. Int. J. Adv. Robot. Syst. (2020). https://doi.org/10.1177/1729881419894417
Linda, O., Manic, M.: Uncertainty-robust design of interval type-2 fuzzy logic controller for delta parallel robot. IEEE Trans. Ind. Inform. 7(4), 661–670 (2011)
Pan, Y., Yang, G.H.: Event-triggered fuzzy control for nonlinear networked control systems. Fuzzy Sets Syst. 329(15), 91–107 (2017)
Wang, H., Kang, S., Feng, Z.: Finite-time adaptive fuzzy command filtered backstepping control for a class of nonlinear systems. Int. J. Fuzzy Syst. 21(8), 2575–2587 (2019)
Wang, N., Sun, Z., Zheng, Z., Zhao, H.: Finite-time sideslip observer-based adaptive fuzzy path-following control of underactuated marine vehicles with time-varying large sideslip. Int. J. Fuzzy Syst. 20(6), 1767–1778 (2018)
Xie, G., Sun, L., Wen, T., Hei, X., Qian, F.: Adaptive transition probability matrix-based parallel IMM algorithm. IEEE Trans. Syst. Man Cybern. Syst. (2019). https://doi.org/10.1109/TSMC.2019.2922305
Lam, H.K., Li, H., Deters, C., Secco, E.L., Wurdemann, H.A., Althoefer, K.: Control design for interval type-2 fuzzy systems under imperfect premise matching. IEEE Trans. Ind. Electron. 61(2), 956–968 (2014)
Pan, Y., Yang, G.H.: Event-triggered fault detection filter design for nonlinear networked systems. IEEE Trans. Syst. Man. Cybern. Syst. 48(11), 1851–1862 (2018)
Li, H., Sun, X., Wu, L., Lam, H.K.: State and output feedback control of a class of fuzzy systems with mismatched membership functions. IEEE Trans. Fuzzy Syst. 23(6), 1943–1957 (2015)
Lam, H.K., Seneviratne, L.D.: Stability analysis of interval type-2 fuzzy-model-based control systems. IEEE Trans. Syst. Man Cybern. 38(3), 617–628 (2008)
Hagras, H.A.: A hierarchical type-2 fuzzy logic control architecture for autonomous mobile robots. IEEE Trans. Fuzzy Syst. 12(4), 524–539 (2004)
Zhang, Z., Niu, Y., Song, J.: Input-to-state stabilization of interval type-2 fuzzy systems subject to cyberattacks: an observer-based adaptive sliding mode approach. IEEE Trans. Fuzzy Syst. 28(1), 190–203 (2020)
Zhao, Yue, Wang, J., Yan, Fei, Shen, Yi: Adaptive sliding mode fault-tolerant control for type-2 fuzzy systems with distributed delays. Inform. Sci. 473, 227–238 (2019)
Du, H., Zhang, N., Samali, B., Naghdy, F.: Robust sampled-data control of structures subject to parameter uncertainties and actuator saturation. Eng. Struct. 36, 39–48 (2012)
Wang, R., Zhang, H., Wang, J.: Linear parameter-varying controller design for four-wheel independently actuated electric ground vehicles with active steering systems. IEEE Trans. Control Syst. Technol. 22(4), 1281–1296 (2014)
Du, H., Zhang, N.: Fuzzy control for nonlinear uncertain electrohydraulic active suspensions with input constraint. IEEE Trans. Fuzzy Syst. 17(2), 343–356 (2009)
Zhang, Z., Li, H., Wu, C., Zhou, Q.: Finite frequency fuzzy \(H_{\infty }\) control for uncertain active suspension systems with sensor failure. IEEE/CAA J. Autom. Sinica. 5(4), 777–786 (2018)
Cao, Y.Y., Lin, Z.: Robust stability analysis and fuzzy-scheduling control for nonlinear systems subject to actuator saturation. IEEE Trans. Fuzzy Syst. 11(1), 57–67 (2003)
Yao, D., Li, H., Lu, R., Shi, Y.: Distributed sliding mode tracking control of second-order nonlinear multi-agent systems: an event-triggered approach. IEEE Trans. Cybern. (2019). https://doi.org/10.1109/TCYB.2019.2963087
Liu, Y., Liu, X., Jing, Y., Wang, H., Li, X.: Annular domain finite-time connective control for large-scale systems with expanding construction. IEEE Trans. Syst. Man Cybern. Syst. (2019). https://doi.org/10.1109/TSMC.2019.2960009
Wen, S., Chen, M.Z.Q., Zeng, Z., Yu, X., Huang, T.: Fuzzy control for uncertain vehicle active suspension systems via dynamic sliding-mode approach. IEEE Trans. Syst. Man Cybern. Syst. 47(1), 24–32 (2017)
Wu, C., Wu, L., Liu, J., Jiang, Z.-P.: Active defense-based resilient sliding mode control under denial-of-service attacks. IEEE Trans. Inf. Forensics Security. 15, 237–249 (2019)
Wu, C., Hu, Z., Liu, J., Wu, L.: Secure estimation for cyber-physical systems via sliding mode. IEEE Trans. Cybern. 48(12), 3420–3431 (2018)
Acknowledgements
This work was partially supported by the National Natural Science Foundation of China (61973091), the Guangdong Natural Science Funds for Distinguished Young Scholar (2017A030306014), the Local Innovative and Research Teams Project of Guangdong Special Support Program of 2019, the Innovative Research Team Program of Guangdong Province Science Foundation (2018B030312006) and the Science and Technology Program of Guangzhou (201904020006).
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Ren, H., Chen, L. & Zhou, Q. Fuzzy Control for Uncertain Electric Vehicle Systems with Sensor Failures and Actuator Saturation. Int. J. Fuzzy Syst. 22, 1444–1453 (2020). https://doi.org/10.1007/s40815-020-00869-y
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DOI: https://doi.org/10.1007/s40815-020-00869-y