Control of electro-hydraulic servo system for a material test system using fuzzy nerual network

This paper deals with the problem of the controller design for the electro-hydraulic servo position control system in a material test system of rock mechanics using fuzzy neural network. Because rock mass is a nonlinear elastic and heterogeneous medium with the ubiquitous micro-holes and micro-cracks and easily broken, its stiffness and damping coefficients are variable during the experimental process. In this paper, the resistant force of the rock specimen is treated as to be a function of time-varying stiffness, which can be estimated during the experimental process. A fuzzy neural network controller with the inputs of the position error and its derivative, and the time-varying stiffness is designed to control the electro-hydraulic position servo system, which is trained by computer simulation of the system with the known parameters. The experimental results of a compressive test on a rock specimen with six loading-unloading cycles show the effectiveness of the proposed method.

[1]  Clarence W. de Silva,et al.  Comparison of two inference methods for P-type fuzzy logic control through experimental investigation using a hydraulic manipulator , 2001 .

[2]  Wei Sun,et al.  An Adaptive Control for AC Servo System Using Recurrent Fuzzy Neural Network , 2005, ICNC.

[3]  Song Zhanping ACOUSTIC EMISSION OF ROCKS UNDER DIRECT TENSION,BRAZILIAN AND UNIAXIAL COMPRESSION , 2007 .

[4]  Jie Zhang,et al.  Recurrent neuro-fuzzy networks for nonlinear process modeling , 1999, IEEE Trans. Neural Networks.

[5]  Chin-Wen Chuang,et al.  CPLD based DIVSC of hydraulic position control systems , 2004, Comput. Electr. Eng..

[6]  Zhou Di Fuzzy controller parameters optimization by using symbiotic evolution algorithm , 2003 .

[7]  Hyungsuck Cho,et al.  A fuzzy controller for an electro-hydraulic fin actuator using phase plane method , 2003 .

[8]  E. Alonso,et al.  Considerations of the dilatancy angle in rocks and rock masses , 2005 .

[9]  Xu Han,et al.  Neural identification of rock parameters using fuzzy adaptive learning parameters , 2003 .

[10]  Heinz Unbehauen,et al.  Adaptive position control of electrohydraulic servo systems using ANN , 2000 .

[11]  Kenzo Nonami,et al.  Optimal two-degree-of-freedom fuzzy control for locomotion control of a hydraulically actuated hexapod robot , 2007, Inf. Sci..

[12]  Yijia Cao,et al.  Generating Extended Fuzzy Basis Function Networks Using Hybrid Algorithm , 2005, FSKD.

[13]  Lanru Jing,et al.  A review of techniques, advances and outstanding issues in numerical modelling for rock mechanics and rock engineering , 2003 .

[14]  Heikki Handroos,et al.  Technical note Sliding mode control for a class of hydraulic position servo , 1999 .