The payload mass and the cable length are always different/uncertain for various transportation tasks and external disturbances that accompany industrial overhead crane systems. In addition, existing control methods can obtain merely asymptotic results. To solve the aforementioned problems, an accurate model-free trajectory tracking controller subject to finite time convergence for overhead crane systems is proposed based on the suitably defined non-singular terminal sliding vector. Moreover, the proposed controller is absolutely continuous, addressing the limitations and shortcomings of the traditional sliding mode control. Lyapunov techniques are used to prove that the proposed controller guarantees finite-time tracking result and the finite time T is calculated. Simulation and experimental results are included to demonstrate the robustness of the proposed controller with respect to model uncertainties, parameter variations and external disturbances.
BartoliniGPisanoAUsaiE (2002) Second-order sliding-mode control of container cranes. Automatica38(10): 1783–1790.
2.
BlackburnDSinghoseWKitchenJet al. (2010) Command shaping for nonlinear crane dynamics. Journal of Vibration and Control16(4): 477–501.
3.
BlajerWKolodziejczykK (2007). Motion planning and control of gantry cranes in cluttered work environment. IET Control Theory and Applications1(5): 1370–1379.
4.
ChenHFangYSunN (2016) A swing constraint guaranteed MPC algorithm for underactuated overhead cranes. IEEE/ASME Transactions on Mechatronics21(5): 2543–2555.
5.
ChwaD (2009) Nonlinear tracking control of 3-D overhead cranes against the initial swing angle and the variation of payload weight. IEEE Transactions on Control Systems Technology17(4): 876–883.
6.
FangYDixonWEDawsonDMZergerogluE (2003) Nonlinear coupling control laws for an underactuated overhead crane system. IEEE/ASME Transactions on Mechatronics8(3): 418–423.
7.
FangYMaBWangPZhangX (2012) A motion planning-based adaptive control method for an underactuated crane system. IEEE Transactions on Control Systems Technology20(1): 241–248.
8.
FujiokaDSinghoseW (2015) Input-shaped model reference control of a nonlinear time-varying double-pendulum crane. In: Proceedings of 10th Asian Control Conference, Kota Kinabalu, 10 September 2015, Sabah, Malaysia, pp. 1–6. IEEE.
9.
GalickiM (2015) Finite-time control of robotic manipulators. Automatica51(2015): 49–54.
10.
GalickiM (2016) Finite-time trajectory tracking control in a task space of robotic manipulators. Automatica67(2016): 165–170.
11.
GarridoSAbderrahimMGiménezAet al. (2008) Anti-swing input shaping control of an automatic construction crane. IEEE Transactions on Automation Science and Engineering5(3): 549–557.
12.
GeussMChoiCLohmannB (2004), Control of parameter-dependent high-order systems using parametric model reduction. AT-Automatisierungstechnik62(7):523–533.
13.
HuangJLiangZZangQ (2015) Dynamics and swing control of double-pendulum bridge cranes with distributed-mass beams. Mechanical Systems and Signal Processing24–25(54–55): 357–366.
14.
LebanFADíaz-GonzalezJParkerGGZhaoW (2015) Inverse kinematic control of a dual crane system experiencing base motion. IEEE Transactions on Control Systems Technology23(1): 331–339.
15.
LeeHH (2004) A new design approach for the anti-swing trajectory control of overhead cranes with high-speed hoisting. International Journal of Control77(10): 931–940.
16.
LeeLHHuangPHPanSTet al. (2015) Applying vision feedback to crane controller. International Journal of Systems Science46(2): 294–302.
17.
LeTAKimGHKimKYLeeSG (2012) Partial feedback linearization control of overhead cranes with varying cable lengths. International Journal of Precision Engineering and Manufacturing13(4): 501–507.
18.
MaghsoudiMJMohamedZHusainARTokhiMO (2016) An optimal performance control scheme for a 3D crane. Mechanical Systems and Signal Processing66–67(2016): 756–768.
19.
NaiduDS (2003) Optimal Control Systems. Boca Raton, London, New York, Washington: CRC Press.
20.
NgoQHHongKS (2012) Adaptive sliding mode control of container cranes. IET Control Theory and Applications6(5): 662–668.
21.
ParkMSChwaDHongSK (2008) Antisway tracking control of overhead cranes with system uncertainty and actuator nonlinearity using an adaptive fuzzy sliding-mode control. IEEE Transactions on Industrial Electronics55(11): 3972–3984.
SinghoseW (2009) Command shaping for flexible systems: the review of the first 50 years. International Journal of Precision Engineering and Manufacturing10(4): 153–168.
24.
SmoczekJ (2014) Fuzzy crane control with sensorless payload deflection feedback for vibration reduction. Mechanical Systems and Signal Processing46(1): 82–90.
25.
SolihinMIWahyudiLegowoA (2010) Fuzzy-tuned PID anti-swing control of automatic gantry crane. Journal of Vibration and Control16(1): 127–145.
26.
SpongMWVidyasagarM (1989) Robot Dynamics and Control. New York: Wiley.
27.
SunNFangY (2014) An efficient online trajectory generating method for underactuated crane systems. International Journal of Robust and Nonlinear Control24(11): 1653–1663.
28.
SunNFangYChenHLuB (2017) Amplitude-saturated nonlinear output feedback antiswing control for underactuated cranes with double-pendulum cargo dynamics. IEEE Transactions on Industrial Electronics64(3): 2135–2146.
29.
SunNFangYWuX (2014) An enhanced coupling nonlinear control method for bridge cranes. IET Control Theory and Applications8(13): 1215–1223.
30.
SunNWuYFangYChenH (2018b) Nonlinear antiswing control for crane systems with double-pendulum swing effects and uncertain parameters: Design and experiments. IEEE Transactions on Automation Science and Engineering15(3): 1413–1422.
31.
SunNYangTChenHet al. (2018c) Adaptive anti-swing and positioning control for 4-DOF rotary cranes subject to uncertain/unknown parameters with hardware experiments. IEEE Transactions on Systems, Man, and Cybernetics: Systems, in press. DOI: 10.1109/TSMC.2017.2765183.
32.
SunNYangTFangYet al. (2018a) Transportation control of double-pendulum cranes with a nonlinear quasi-PID scheme: Design and experiments. IEEE Transactions on Systems, Man, and Cybernetics: Systems, in press. DOI: 10.1109/TSMC.2018.2871627.
33.
Van den BroeckLDiehlMSweversJ (2011) A model predictive control approach for time optimal point-to-point motion control. Mechatronics21(7): 1203–1212.
34.
WuTSKarkoubMYuWSet al. (2016). Anti-sway tracking control of tower cranes with delayed uncertainty using a robust adaptive fuzzy control. Fuzzy Sets and Systems 293(2016): 118–137.
35.
WuZXiaX (2014) Optimal motion planning for overhead cranes. IET Control Theory and Applications8(17): 1833–1842.
36.
ZhangMMaXChaiHet al. (2016a) A novel online motion planning method for double-pendulum overhead cranes. Nonlinear Dynamics85(2): 1079–1090.
37.
ZhangMMaXRongXet al. (2016b) Adaptive tracking control for double-pendulum overhead cranes subject to tracking error limitation, parametric uncertainties and external disturbances. Mechanical Systems and Signal Processing76–77(2016): 15–32.
38.
ZhangMMaXRongXet al. (2018) Nonlinear coupling control method for underactuated three-dimensional overhead crane systems under initial input constraints. Transactions of the Institute of Measurement and Control40(2): 413–424.
39.
ZhangZWuYHuangJ (2016) Robust adaptive antiswing control of underactuated crane systems with two parallel payloads and rail length constraint. ISA Transactions65(2016): 275–283.
40.
ZhangZWuYHuangJ (2017) Differential-flatness-based finite-time anti-swing control of underactuated crane systems. Nonlinear Dynamics87(3): 1749–1761.
41.
ZhaoYGaoH (2012) Fuzzy-model-based control of an overhead crane with input delay and actuator saturation. IEEE Transactions on Fuzzy Systems20(1): 181–186.
