Research On Aircraft Anti-Skid Braking Control System Based On Fuzzy Neural Network

Aircraft anti-skid brake control system is an important equipment of an aircraft, which have an important impact on the safety of aircraft taking-off and landing. The purpose of anti-skid brake control is to ensure that during the process of wheels braking there is no danger of tire sliding. And by running advanced control strategies, the optimum braking efficiency can be achieved, so as to enhance the security of aircraft taking-off and landing. The study of advanced anti-skid control algorithm is of great significance. This paper presents a combined neural network fuzzy adaptive anti-skid control strategy, and researches the hardware design of digital anti-skid brake control box based on digital signal processor TMS320LF2407.Paper first analyzes the development and status of the domestic and international anti-skid brake system, and compares several existing control methods, selects the control method based on the slip rate. By analyzing the working principle of aircraft brake system, each model of all aspects of the aircraft brake system are set up. According to characteristics of anti-skid control, the control algorithm based on fuzzy reasoning is researched, and then a fuzzy controller is designed. The defect is that the law of fuzzy control is mainly designed by experts, and it is difficult to study and draw laws by itself. In this paper, by absorbing the advantages of self-learning of RBF neural networks, a fuzzy anti-skid control system based on ANN is presented to improve adaptive capacity. Results of simulation show the feasibility of design in this paper.Finally, this paper studies hardware design of digital anti-skid brake control box based on the high performance digital signal processor core TMS320LF2407, analyses and designs the circuits of command sensor, wheel speed sensors and switches and signal conditioning circuit and so on.