Terminal sliding mode fuzzy control based on multiple sliding surfaces for nonlinear ship autopilot systems

Abstract

A terminal sliding mode fuzzy control based on multiple sliding surfaces was proposed for ship course tracking steering, which takes account of rudder characteristics and parameter uncertainty. In order to solve the problem, the controller was designed by employing the universal approximation property of fuzzy logic system, the advantage of Nussbaum function, and using multiple sliding mode control algorithm based on the recursive technique. In the last step of designing, a nonsingular terminal sliding mode was utilized to drive the last state of the system to converge in a finite period of time, and high-order sliding mode control law was designed to eliminate the chattering and make the system robust. The simulation results showed that the controller designed here could track a desired course fast and accurately. It also exhibited strong robustness peculiarly to system, and had better adaptive ability than traditional PID control algorithms.

Keywords

ship course control / unmatched uncertainty / multiple sliding mode control / nonsingular terminal sliding mode control / robustness

References

[1] Cheng G., Wang S. Robust and adaptive backstepping control for nonlinear systems using fuzzy logic systems. Lecture Notes in Artificial Intelligence, 2005, 36(14): 452-461

[2] Du J.L., Guo C. Simulation studies on adaptive nonlinear control of ship motion course. Journal of System Simulation, 2005, 17(6): 1445-1448

[3] Du JL and Chen G (2004). Nonlinear adaptive ship course tracking control based on backstepping and Nussbaum gain. IEEE Proceeding of Control Conference, America, 3845–3850.

[4] Feng Y., Yu X., Man Z. Non-singular adaptive terminal sliding mode control of rigid manipulators. Automatica, 2002, 38(12): 2159-2167

[5] Guan C., Zhu S.A. Multiple sliding control: theory and application sliding mode robust adaptive control of an electro-hydraulic servo system. Journal of Control & Application, 2005, 22(6): 931-938

[6] Ge S.S., Hong F., Lee T.H. Adaptive neural control of nonlinear time-delay systems with unknown virtual control coefficients. IEEE Tran on Systems, Man and Cybernetics-Part B: Cybernetics (S1083-4419), 2004, 34(1): 499-516

[7] Hedrick J.K., Yip P.P. Multiple sliding control: theory and application. Journal of Dynamic Systems. Measurement and Control, 2000, 12(2): 586-593

[8] Huang J.Q. Adaptive control theories and its applications in ship system, 1992, Beijing: National Defense Industry Press, 1-4

[9] Jeffery R.L. Fuzzy model reference learning control for cargo ship steering. IEEE Control System, 1993, 13(5): 23-34

[10] Jia X. L., Yang Y.S. Ship motion mathematic Model, 1998, Dalian: Dalian Maritime University Press, 63-68

[11] Lin F.J., Shen P.H., Hsu S.P. Adaptive backstepping sliding mode control for linear induction motor. IEEE Proceeding Electric Power Application, 2002, 14(9): 184-194

[12] Liu Y., Guo C., Lv J. Sliding-mode control of ship course tracking based on backstepping. J.Cent.South Univ. (Science and Technology), 2005, 38(1): 278-282

[13] Li W.L., Lin W.X., Liu S.R. Application of robust adaptive output tracking control in ship maneuvering autopilot. Journal of System Simulation, 2006, 18(11): 3250-3254

[14] Nussbaum R.D. Some remarks on the conjecture in parameter adaptive control. Systems and Control Letters, 1983, 3(3): 243-246

[15] Yang YS (1994). Neural network adaptive control for ship automatic steering Computer and Control. Proceeding of International Conference of Young Investigations on Information, Beijing, 231–236.

[16] Yao Q. H., Huang J.Q., Wu H.S. Variable Structure control System, 1997, Chongqing: Chongqing University Press, 31-34

[17] Yuan L., Wu H.S., Song L.Z. Application of fuzzy sliding mode control in nonlinear ship autopilot system. Navigation of China, 2010, 33(1): 61-64