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Front. Inform. Technol. Electron. Eng.  2016, Vol. 17 Issue (1): 55-66    DOI: 10.1631/FITEE.15a0160
Original article     
Adaptive fuzzy integral sliding mode velocity control for the cutting system of a trench cutter
Qi-yan TIAN,Jian-hua WEI,Jin-hui FANG(),Kai GUO
State Key Laboratory of Fluid Power & Mechatronic Systems, Zhejiang University, Hangzhou 310027, China
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Abstract  

This paper presents a velocity controller for the cutting system of a trench cutter (TC). The cutting velocity of a cutting system is affected by the unknown load characteristics of rock and soil. In addition, geological conditions vary with time. Due to the complex load characteristics of rock and soil, the cutting load torque of a cutter is related to the geological conditions and the feeding velocity of the cutter. Moreover, a cutter’s dynamic model is subjected to uncertainties with unknown effects on its function. In this study, to deal with the particular characteristics of a cutting system, a novel adaptive fuzzy integral sliding mode control (AFISMC) is designed for controlling cutting velocity. The model combines the robust characteristics of an integral sliding mode controller with the adaptive adjusting characteristics of an adaptive fuzzy controller. The AFISMC cutting velocity controller is synthesized using the backstepping technique. The stability of the whole system including the fuzzy inference system, integral sliding mode controller, and the cutting system is proven using the Lyapunov theory. Experiments have been conducted on a TC test bench with the AFISMC under different operating conditions. The experimental results demonstrate that the proposed AFISMC cutting velocity controller gives a superior and robust velocity tracking performance.

Key words： Cutting system      Electro-hydraulic system      Cutting velocity control      Adaptive fuzzy integral sliding mode control     
Received: 01 June 2015      Published: 05 January 2016
CLC:  TP271.3  
Fund:  National Natural Science Foundation of China(No. 2012AA041801)
Corresponding Authors: Jin-hui FANG     E-mail: jhfang@zju.edu.cn
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Qi-yan TIAN
Jian-hua WEI
Jin-hui FANG
Kai GUO
Cite this article:

Qi-yan TIAN,Jian-hua WEI,Jin-hui FANG,Kai GUO. Adaptive fuzzy integral sliding mode velocity control for the cutting system of a trench cutter. Front. Inform. Technol. Electron. Eng., 2016, 17(1): 55-66.

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http://www.zjujournals.com/xueshu/fitee/10.1631/FITEE.15a0160     OR     http://www.zjujournals.com/xueshu/fitee/Y2016/V17/I1/55


Adaptive fuzzy integral sliding mode velocity control for the cutting system of a trench cutter

This paper presents a velocity controller for the cutting system of a trench cutter (TC). The cutting velocity of a cutting system is affected by the unknown load characteristics of rock and soil. In addition, geological conditions vary with time. Due to the complex load characteristics of rock and soil, the cutting load torque of a cutter is related to the geological conditions and the feeding velocity of the cutter. Moreover, a cutter’s dynamic model is subjected to uncertainties with unknown effects on its function. In this study, to deal with the particular characteristics of a cutting system, a novel adaptive fuzzy integral sliding mode control (AFISMC) is designed for controlling cutting velocity. The model combines the robust characteristics of an integral sliding mode controller with the adaptive adjusting characteristics of an adaptive fuzzy controller. The AFISMC cutting velocity controller is synthesized using the backstepping technique. The stability of the whole system including the fuzzy inference system, integral sliding mode controller, and the cutting system is proven using the Lyapunov theory. Experiments have been conducted on a TC test bench with the AFISMC under different operating conditions. The experimental results demonstrate that the proposed AFISMC cutting velocity controller gives a superior and robust velocity tracking performance.

Fig. 1 Architecture of a trench cutter (TC) (a) Photograph of a TC at a construction site; (b) A schematic diagram of a cutting system of a TC
Fig. 2 Fuzzy sets and membership functions
ω/vf Z NZ VS S M B VB
Z Z Z Z NZ VS NS S
NZ Z Z NZ VS NS S NM
VS Z NZ VS NS S NM M
S NZ VS NS S NM M NB
M VS NS S NM M NB B
B NS S NM M NB B VB
VB S NM M NB B VB VB
Table 1 Rule base for the fuzzy logic system
Fig. 3 Structure of the AFISMC for cutting velocity control
Fig. 4 Experimental test rig
Fig. 5 Structure of the test rig
Parameter Value
λ 20
k 11 500
k21 100
Φ 0.5
k11 20
k12 10-6
k21 10-6
Table 2 AFISMC control parameters
Fig. 6 Constant tracking with disturbance in soil
Fig. 7 Load torque acting on the cutting motor in soil using AFISMC
Fig. 8 Swashplate angle of the pump in soil using AFISMC
Fig. 9 The transient inlet pressure of cutting motor in soil using AFISMC
Fig. 10 Constant tracking with disturbance in hard soil
Fig. 11 Constant tracking with disturbance in limestone
Fig. 12 Constant tracking with disturbance in granite
Fig. 13 Sinusoidal tracking of the system in soil
Fig. 14 Sinusoidal tracking of the system in hard soil
Fig. 15 Sinusoidal tracking of the system in limestone
Fig. 16 Sinusoidal tracking of the system in granite
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