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Optimized Fuzzy Neural Networks Control of a Magnetic Suspension Vibration Isolation System

Active vibration isolation technology can overcome the defects of passive vibration isolation technology that the poor vibration isolation performance in low and resonant frequencies. Compared with other active vibration isolation technologies, magnetic suspension isolation technology has shown useful characteristics, such as wide response frequency range, fast response, high reliability and long-life. However, the control of MSVI is still one of the areas that require further investigation. This paper presents a Fuzzy Neural Networks(FNN) control algorithm for a magnetic suspension isolation vibration system, which is optimized by improved Genetic Algorithm(GA). The output force responses of the FNN and passive vibration isolation system under same excitation are simulated. The simulation results show that the fuzzy control system has much better performance in vibration isolation.