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This paper proposes a new approach to improve the control precision of shaking table control system, in which the fuzzy neural network (FNN) technique and iterative learn control (ILC) are combined and developed a new control technique. A FNN inverse model is built and is identified through a white noise with appropriate peak values and frequency range. Then better control effect is obtained by ILC than Remote Parameter Control (RPC). This proposed technique is capable of improving the system precision and adaptability, and reducing the effect of structural load’s dynamic characteristic.

Application Study of ILC with Fuzzy Neural Network in Shaking Table Control System