Adaptive neural network preset time control method for electromechanical transducer with memristor

The invention relates to an adaptive neural network preset time control method for an electromechanical transducer with a memristor, and belongs to the technical field of adaptive control. The method comprises the following steps: S1, carrying out system modeling on an electromechanical transducer with a memristor; s2, kinetic analysis; s3, designing a controller of a preset time of the adaptive neural network, including applying a delay constraint function to a tracking error starting from any position; processing parameter disturbance and system uncertain items by using a type 2 fuzzy wavelet neural network; a second-order fractional order tracking differentiator is used; constructing fault control input; and S4, stability analysis. According to the method, the fractional characteristics of the dielectric and the relation between the magnetic flux and the charges are fully represented, chaotic oscillation is converted into regular motion, and the preset tracking precision is achieved on the premise that the