The use of electro-hydraulic cylinders in industry has been becoming increasingly popular. A Fuzzy Logic Controller (FLC), which consists of the linguistic defined fuzzy sets and the control rules, is designed to control of the electro-hydraulic cylinder. Using the triangle shaped membership function; the position of the servo cylinder was successfully controlled. When the system working condition is altered, the control algorithm is shown to be more robust compared to the PID controller.

In this paper, a new Intelligent system based on neurofuzzy for detecting and diagnostics the wear and damage of the milling cutter is presented. The compatibility between the computer vision and neurofuzzy techniques is introduced. The proposed approaches consists of capturing the milling cutter image, Fuzzy edge detection, Chain code technique for feature extraction and finally, apply the neural network on the feature. The results of the study are three different diagnostics models, The first is diagnostic model for the original profile of the perfect cutter, the second is model for the wearied profile and the third is model for the damage profile. Experimental test results show that the proposed system is reliable, practical and can be used for the easy distinguish between the wear and damage automatically.