Research On Sliding Mode Control Based On Electro-hydraulic Servo System Modeling

With the rapid development of science and technology, electro-hydraulic servo system(EHSS) has been widely used in many automatic control systems which require both accuracy and speed, such as injection molding machines(IMMs). EHSS is a high-order nonlinear control system with time-varying parameter, cross load interference and external interference, therefore, precise mathematical model is difficult to be established. Sliding mode control(SMC) method has good robustness,fast response speed, insensitivity to parameters and disturbance, also it is easy to implement in project. Therefore, SMC can be used to solve interferences and other nonlinear time-varying parameter uncertainties in EHSS.Aiming at the nonlinear characteristics and system uncertainties, several SMC methods are designed to control the EHSS. The main contents of this paper are as follows:1. By analyzed the principle and physical structure, the mathematic model of the EHSS is established. The performance in time domain area is then analyzed.2. For the chattering problem of SMC, an adaptive SMC for EHSS is presented.Factors causing system chattering are summarized for the uncertainties of EHSS, the corresponding control and adaptive law are designed. Simulation results show that the proposed adaptive SMC for EHSS can effectively weaken the system chattering in comparison to the conventional SMC.3. For the system uncertainties, a RBF neural network based SMC is designed for EHSS. The RBF neural network is used to approximate the nonlinear functions of EHSS, the corresponding control law and adaptive law are then designed. In this way,the good robust performance is achieved.4. For the high repeatability of toggle mechanism of IMM, a novel iterative learning sliding mode control(ILSMC) is designed for EHSS. The SMC algorithm is acted as a learning law of iterative learning control(ILC), to calculate the increment of control data. Simulation results show that the ILSMC can enhance the robustness,reduce error and improve tracking accuracy. Compared to conventional ILC method,ILSMC has a better response and tracking performances.