zbMATH — the first resource for mathematics

Global fast terminal sliding mode controller for hydraulic turbine regulating system with actuator dead zone. (English) Zbl 1423.93073
Summary: This paper investigates the frequency change problem of hydraulic turbine regulating system based on terminal sliding mode control method. By introducing a novel terminal sliding mode surface, a global fast terminal sliding mode controller is designed for the closed loop. This controller eliminates the slow convergence problem which arises in the terminal sliding mode control when the error signal is not near the equilibrium. Meanwhile, following consideration of the error caused by the actuator dead zone, an adaptive RBF estimator based on sliding mode surface is proposed. Through the dead zone error estimation for feed-forward compensation, the composite terminal sliding mode controller has been verified to possess an excellent performance without sacrificing disturbance rejection robustness and stability. Simulations have been carried out to validate the superiority of our proposed methods in comparison with other two other kinds of sliding mode control methods and the commonly used PID and FOPID controller. It is shown that the simulation results are in good agreement with the theoretical analysis.
93B12 Variable structure systems
93C95 Application models in control theory
93C80 Frequency-response methods in control theory
93B40 Computational methods in systems theory (MSC2010)
Full Text: DOI
[1] Strah, B.; Kuljaca, O.; Vukic, Z., Speed and active power control of hydro turbine unit, IEEE Trans. Energy Convers., 20, 2, 424-434, (2005)
[2] Demello, F. P.; Koessler, R. J.; Agee, J., Hydraulic turbine and turbine control models for system dynamic studies, IEEE Trans. Power Syst., 7, 1, 167-179, (1992)
[3] Chen, Z.; Yuan, X.; Ji, B., Design of a fractional order PID controller for hydraulic turbine regulating system using chaotic non-dominated sorting genetic algorithm II, Energy Convers. Manag., 84, 390-404, (2014)
[4] Nagode, K.; Skrjanc, I., Modelling and internal fuzzy model power control of a Francis water turbine, Energies, 7, 2, 874-889, (2014)
[5] Zhang, R.; Chen, D.; Ma, X., Nonlinear predictive control of a hydropower system model, Entropy, 17, 9, 6129-6149, (2015)
[6] Yuan, X.; Chen, Z.; Yuan, Y., Design of fuzzy sliding mode controller for hydraulic turbine regulating system via input state feedback linearization method, Energy, 93, 173-187, (2015)
[7] Liang, J.; Yuan, X.; Yuan, Y., Nonlinear dynamic analysis and robust controller design for Francis hydraulic turbine regulating system with a straight-tube surge tank, Mech. Syst. Signal Process., 85, 927-946, (2017)
[8] Wang, H.; Kong, H.; Man, Z., Sliding mode control for steer-by-wire systems with AC motors in road vehicles, IEEE Trans. Ind. Electron., 61, 3, 1596-1611, (2014)
[9] Mercorelli, P., A two-stage sliding-mode high-gain observer to reduce uncertainties and disturbances effects for sensorless control in automotive applications, IEEE Trans. Ind. Electron., 62, 9, 5929-5940, (2015)
[10] Haus, B.; Mercorelli, P.; Werner, N., A robust adaptive self-tuning sliding mode control for a hybrid actuator in camless internal combustion engines, Advances and Applications in Sliding Mode Control Systems, 107-136, (2015), Springer: Springer Cham
[11] Rittenhouse, B. D.; Sinha, A., Optimal sliding mode Gaussian controller for a hydropower plant, (Proceedings of the American Control Conference, (2013), IEEE), 6535-6540
[12] Man, Z. H.; Xing, H. Y., Terminal sliding mode control of MIMO linear systems, IEEE Trans. Circuits Syst. I Fundam. Theory Appl., 44, 11, 1065-1070, (1997)
[13] Shotorbani, A. M.; Ajami, A.; Zadeh, S. G., Robust terminal sliding mode power flow controller using unified power flow controller with adaptive observer and local measurement, IET Gener. Transm. Distrib., 8, 10, 1712-1723, (2014)
[14] Wang, H.; Man, Z.; Kong, H., Design and implementation of adaptive terminal sliding-mode control on a steer-by-wire equipped road vehicle, IEEE Trans. Ind. Electron., 63, 9, 5774-5785, (2016)
[15] Yu, X. H.; Man, Z. H., Fast terminal sliding-mode control design for nonlinear dynamical systems, IEEE Trans. Circuits Syst. I Fundam. Theory Appl., 49, 2, 261-264, (2002) · Zbl 1368.93213
[16] Wu, M.; Chen, J. S., A discrete-time global quasi-sliding mode control scheme with bounded external disturbance rejection, Asian J. Control, 16, 6, 1839-1848, (2014) · Zbl 1307.93106
[17] Yang, C.; Ke, Z.; Lei, D., Research on global fast terminal sliding mode guidance law, Comput. Meas. Control, 16, 10, 1387-1389, (2013)
[18] Wang, F.; Chen, D.; Xu, B., Nonlinear dynamics of a novel fractional-order Francis hydro-turbine governing system with time delay, Chaos Solitons Fractals, 91, 329-338, (2016) · Zbl 1372.93150
[19] Haus, B.; Mercorelli, P., An extended kalman filter for time delays inspired by a fractional order model, Lecture Notes in Electrical Engineering, 496, 151-163, (2019), Springer, 233 Spring Street: Springer, 233 Spring Street New York, NY 10013, United States · Zbl 1422.93175
[20] Dehghan, M.; Abbaszadeh, M.; Mohebbi, A., The numerical solution of nonlinear high dimensional generalized Benjamin-Bona-Mahony-Burgers equation via the meshless method of radial basis functions, Comput. Math. Appl., 68, 3, 212-237, (2014) · Zbl 1369.65126
[21] Dehghan, M.; Abbaszadeh, M., The use of proper orthogonal decomposition (POD) meshless RBF-FDtechnique to simulate the shallow water equations, J. Comput. Phys., 351, 478-510, (2017) · Zbl 1380.65301
[22] Dehghan, M.; Shokri, A., A numerical method for solution of the two-dimensional sine-Gordon equation using the radial basis functions, Math. Comput. Simul., 79, 3, 700-715, (2008) · Zbl 1155.65379
[23] Dehghan, M.; Nikpour, A., Numerical solution of the system of second-order boundary value problems using the local radial basis functions based differential quadrature collocation method, Appl. Math. Model., 37, 18-19, 8578-8599, (2013) · Zbl 1426.65113
[24] Yu, S.; Guo, G.; Ma, Z., Global fast terminal sliding mode control for robotic manipulators, Int. J. Modell. Identif. Control, 1, 1, 72-79, (2006)
[25] Yuan, X.; Wang, P.; Yuan, Y., A new quantum inspired chaotic artificial bee colony algorithm for optimal power flow problem, Energy Convers. Manag., 100, 1-9, (2015)
[26] Lucero, T. L., A. Hydro Turbine and Governor Modelling, (2010), Norwegian University of Science and Technology: Norwegian University of Science and Technology Trondheim, Norwegian, Master thesis
[27] Yuan, X.; Tan, Q.; Lei, X., Wind power prediction using hybrid autoregressive fractionally integrated moving average and least square support vector machine, Energy, 129, 122-137, (2017)
[28] Chen, Z.; Yuan, Y.; Yuan, X., Application of multi-objective controller to optimal tuning of PID gains for a hydraulic turbine regulating system using adaptive grid particle swam optimization, ISA Trans., 56, 173-187, (2015)
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. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.