Nonlinear modeling of an electrohydraulic actuation system via experiments and its characterization by means of neural network

Abstract

The friction and end-cushioning effects in the actuator have been taken care in consideration in the modeling of the actuation method related to an electrohydraulic system. A much simpler friction model that retains all the features of the existing models has been developed for this purpose. In addition, a systematic experimental characterization procedure has been proposed that has been utilized in a supplementary manner for the development of the elaborate nonlinear system model. An artificial neural-network model has been constructed by training with experimental data keeping in mind the variation of discharge through the proportional valve with pressure and command signal. All the nonlinear subsystem models thus obtained have been incorporated simultaneously in MATLAB/SIMULINK to monitor the actuation dynamics. The variations of the theoretical and investigated (via experiments) displacements of the piston against different command signals have been found to be quite close to each other. Keywords Electrohydraulics Á Hydraulic system modeling Á Identification Á Artificial neural network Á Simulation List of symbols A a Cross-sectional area of actuator piston, (m 2) A p Cross-sectional area of flow in pipe, (m 2) C d Coefficient of discharge C vi (i = 1-4) Main-flow coefficient corresponding to the pressure drop DPi, (m 3 /(VPa 1/2)) d b Actuator bore diameter, (m) d c Cushion rod diameter, (m) d o Cushion bush diameter, (m) d r Actuator piston rod diameter, (m) E Error between measured output value t k and the network predicted value y k e f Feed forward voltage (V) F f Frictional force (N) f RV (Q s), f NRV (Q r) Pressure-discharge characteristics for the relief valve and nonreturn valve, respectively, (Pa) K s Spring constant, (N/m) l b Inner length of actuator cylinder, (m) l c Length of cushion rod, (m) l l Lip length between cushion rod and actuator piston rod, (m) l p-s Pipe length between pump delivery and the supply port of PV, (m) l v1-a1 Pipe length between PV and chamber 1 of actuator, (m) l v2-a2 Pipe length between PV and chamber 2 of actuator, (m) l r-n Pipe length between NRV and the return port of PV, (m) m a Moving mass of the actuator, (kg) P A , P B Pressures at the two control ports A and B of the PV, respectively, (Pa) P c1 , P c2 Cushioning volume pressures in chambers 1 and 2, respectively, (Pa) P n Pressures at the return port of PV and inlet to the NRV, respectively, (Pa) P p Pressures at the pump exit and inlet to the PV, respectively, (Pa)

Practical profile tracking for a hydraulic press using sliding mode controller

“…The tracking capacity of the non-linear PID controller is assessed by sinusoidal signals. Further, Das et al, 9 addressed the friction and end cushioning effects in the actuator by a neural network model. Junbo and Xuangan 10 dealt with the position control of an asymmetric actuator controlled by an orifice and two way proportional valve.…”