Full Text:   <7902>

Summary:  <1875>

CLC number: TP271.3

On-line Access: 2024-08-27

Received: 2023-10-17

Revision Accepted: 2024-05-08

Crosschecked: 2015-12-09

Cited: 1

Clicked: 7728

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Qi-yan Tian

http://orcid.org/0000-0002-8392-7252

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Frontiers of Information Technology & Electronic Engineering  2016 Vol.17 No.1 P.55-66

http://doi.org/10.1631/FITEE.15a0160


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


Author(s):  Qi-yan Tian, Jian-hua Wei, Jin-hui Fang, Kai Guo

Affiliation(s):  State Key Laboratory of Fluid Power & Mechatronic Systems, Zhejiang University, Hangzhou 310027, China

Corresponding email(s):   jhfang@zju.edu.cn

Key Words:  Cutting system, Electro-hydraulic system, Cutting velocity control, Adaptive fuzzy integral sliding mode control


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[J]. Frontiers of Information Technology & Electronic Engineering, 2016, 17(1): 55-66.

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journal="Frontiers of Information Technology & Electronic Engineering",
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publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.15a0160"
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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.

This is an interesting work of the application of AFISMC to a practical system. It contains both theoretical analysis and experimental validation. The paper was generally well written and the derivation seems correct.

双轮铣槽机铣削系统自适应模糊积分滑模转速控制

目的:随着地下连续墙施工工法和双轮铣槽机技术不断发展,实现对双轮铣槽机铣削系统铣轮工作转速的快速精确控制具有重要意义。在负载特性未知、扰动复杂的情况下,本文基于自适应模糊积分滑模(AFISMC)控制算法,实现对铣削系统铣轮转速的良好控制。
创新点:在双轮铣槽机铣轮铣削过程中,铣轮转速控制受到岩石和土壤未知负载特性的影响,同时地质条件不断变化。由于岩石和土壤复杂的负载特性,铣轮的切削扭矩与地质条件、铣轮进给速度等均存在耦合关系,而且其动态特性复杂未知,无法建立准确的数学模型。本文针对以上难点,设计新型自适应模糊积分滑模转速控制器。
方法:针对双轮铣槽机铣削系统的特性,提出一种基于自适应模糊积分滑模控制(AFISMC)的铣轮转速控制方案。该控制方案将自适应控制的参数自整定特性、积分滑模控制的鲁棒性以及模糊系统独立于数学模型的特性结合起来。通过自适应模糊系统对被控对象未知模型有效逼近,使用反步法对控制器进行设计,采用Lyapunov理论证明整个闭环系统(包括自适应模糊推理系统、积分滑模控制器和被控对象)的稳定性。
结论:在双轮铣槽机液压模拟实验台对不同工况下的铣轮转速控制进行实验,分别采用PI、ISMC和AFISMC三种控制方法进行对比。实验结果表明AFISMC控制算法在跟踪和抗干扰方面均表现出良好的控制性能。

关键词:铣削系统;电液系统;铣削转速控制;自适应模糊积分滑模控制

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

[1]Ahn, K.K., Chau, N.H.T., Truong, D.Q., 2007. Robust force control of a hybrid actuator using quantitative feedback theory. J. Mech. Sci. Technol., 21(12):2048-2058.

[2]Busquets, E., Ivantysynova, M., 2015. Discontinuous projection-based adaptive robust control for displacement-controlled actuators. J. Dyn. Syst. Meas. Contr., 137(8):081007.

[3]Cerman, O., 2013. Fuzzy model reference control with adaptation mechanism. Expert Syst. Appl., 40(13):5181-5187.

[4]Chen, C.Y., Liu, L.Q., Cheng, C.C., et al., 2008. Fuzzy controller design for synchronous motion in a dual-cylinder electro-hydraulic system. Contr. Eng. Pract., 16(6):658-673.

[5]Chiang, M.H., Lee, L.W., Tsai, J.J., 2004. The concurrent implementation of high velocity control performance and high energy efficiency for hydraulic injection moulding machines. Int. J. Adv. Manuf. Technol., 23(3):256-262.

[6]Chiang, M.H., Yeh, Y.P., Yang, F.L., et al., 2005. Integrated control of clamping force and energy-saving in hydraulic injection moulding machines using decoupling fuzzy sliding-mode control. Int. J. Adv. Manuf. Technol., 27(1):53-62.

[7]Daher, N., Ivantysynova, M., 2013. System synthesis and controller design of a novel pump controlled steer-by-wire system employing modern control techniques. Proc. ASME/BATH Symp. on Fluid Power and Motion Control, p.1-10.

[8]Daher, N., Ivantysynova, M., 2014. An indirect adaptive velocity controller for a novel steer-by-wire system. J. Dyn. Syst. Meas. Contr., 136(5):051012.

[9]Guo, K., Wei, J.H., Fang, J.H., et al., 2015. Position tracking control of electro-hydraulic single-rod actuator based on an extended disturbance observer. Mechatronics, 27:47-56.

[10]Kalyoncu, M., Haydim, M., 2009. Mathematical modelling and fuzzy logic based position control of an electrohydraulic servosystem with internal leakage. Mechatronics, 19(6):847-858.

[11]Lin, J., Huang, Z.Z., 2007. A hierarchical fuzzy approach to supervisory control of robot manipulators with oscillatory bases. Mechatronics, 17(10):589-600.

[12]Lin, Y., Shi, Y., Burton, R., 2013. Modeling and robust discrete-time sliding-mode control design for a fluid power electrohydraulic actuator (EHA) system. IEEE/ASME Trans. Mech., 18(1):1-10.

[13]Merritt, H.E., 1967. Hydraulic Control Systems. John Wiley & Sons, New York, USA.

[14]Minav, T.A., Laurila, L.I.E., Pyrhönen, J.J., 2013. Analysis of electro-hydraulic lifting system’s energy efficiency with direct electric drive pump control. Autom. Constr., 30:144-150.

[15]Sha, D.H., Bajic, V.B., Yang, H.Y., 2002. New model and sliding mode control of hydraulic elevator velocity tracking system. Simul. Practice Theory, 9(6-8):365-385.

[16]Shi, Y., Huang, J., Yu, B., 2013. Robust tracking control of networked control systems: application to a networked DC motor. IEEE Trans. Ind. Electron., 60(12):5864-5874.

[17]Truong, D.Q., Ahn, K.K., 2009. Force control for hydraulic load simulator using self-tuning grey predictor—fuzzy PID. Mechatronics, 19(2):233-246.

[18]Truong, D.Q., Ahn, K.K., 2011. Force control for press machines using an online smart tuning fuzzy PID based on a robust extended Kalman filter. Expert Syst. Appl., 38(5):5879-5894.

[19]Wang, D.Y., Lin, X., Zhang, Y., 2011. Fuzzy logic control for a parallel hybrid hydraulic excavator using genetic algorithm. Autom. Constr., 20(5):581-587.

[20]Wang, L.K., Book, W.J., Huggins, J.D., 2012. Application of singular perturbation theory to hydraulic pump controlled systems. IEEE/ASME Trans. Mech., 17(2):251-259.

[21]Wang, X.J., Wang, S.P., Zhao, P., 2012. Adaptive fuzzy torque control of passive torque servo systems based on small gain theorem and input-to-state stability. Chin. J. Aeronaut., 25(6):906-916.

[22]Wei, J.H., Guo, K., Fang, J.H., et al., 2015. Nonlinear supply pressure control for a variable displacement axial piston pump. Proc. Inst. Mech. Eng. Part I: J. Syst. Contr. Eng., 229(7):614-624.

[23]Wei, L., Fang, F., Shi, Y., 2014. Adaptive backstepping-based composite nonlinear feedback water level control for the nuclear U-tube steam generator. IEEE Trans. Contr. Syst. Technol., 22(1):369-377.

[24]Wu, H.W., Lee, C.B., 1995. Self-tuning adaptive speed control of a pump/inverter-controlled hydraulic motor system. Proc. Inst. Mech. Eng. Part I: J. Syst. Contr. Eng., 209(29):101-114.

[25]Zhang, H., Shi, Y., Mu, B.X., 2013. Optimal H-based linear-quadratic regulator tracking control for discrete-time Takagi-Sugeno fuzzy systems with preview actions. J. Dyn. Syst. Meas. Contr., 135(4):044501.

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