Leveling technology based on NN and adaptive fuzzy control of hydraulic system

In the field of modern national defense and civilian technology, we often need to precisely adjust a bearing platform. The platform with certain equipment to the horizontal position improves the system performance. Short time, high speed, high precision and well stability is required in the leveling system. However, the leveling system is a nonlinear time-varying system. “involvement coupling” problem between the hydraulic legs, legs and dip angles will appear in the process of leveling. In this paper, the “surface-adjust-surface” leveling technique is proposed by the leveling method. The method is based on the target surface with multi-point and multi-direction control by outputting control variables from leveling the relative position between surface and target surface. Use the neural network to train the motion characteristics of the switch-valve-controlled hydraulic cylinder. It combines the fuzzy control technique and the leveling method based on target surface. Forms of the intelligent algorithm are based on target surface to solve the problems of strong coupling and weak leg in the process of leveling. The method realizes multi- point control. Online application and experimental verification were in a certain type of weapon equipment and a certain type of radar vehicle. The result shows that the method not only has the advantage of simple principle and stable-reliable control performance, but also perfectly realizes precise and rapid leveling of hydraulic overloading platform. It has broad prospects for widespread application.