

FOLLOWUS
State Key Laboratory of Fluid Power & Mechatronic Systems, Zhejiang University, Hangzhou 310027, China
E-mail:jhfang@zju.edu.cn
Received:01 June 2015,
Accepted:26 October 2015,
Published:2016-01
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Qi-yan TIAN, Jian-hua WEI, Jin-hui FANG, et al. 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.
Qi-yan TIAN, Jian-hua WEI, Jin-hui FANG, et al. 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. DOI: 10.1631/FITEE.15a0160.
目的
2
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
2
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
2
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
2
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。
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.
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