It adopts a three-layer recurrent neural network(RNN)as a nonlinear smith predictor,to model a 1-joint pneumatic artificial muscle(PAM)manipulator,and to predict the d-step ahead output of the PAM manipulator.The difference between the desired output and the feedback variable,which is the d-step ahead predict output,is taken as the input of the PID controller.And the Smith prediction PID control is realized.At every sampling step,the weights of the RNN are adjusted by using the criterion of the square of the difference between the present output of the RNN model and the present actual output of the PAM manipulator so as to handle the uncertainty and time-variety of the PAM manipulator.Through a serial port and two ADAM modules,this paper uses a Matlab program to control the PAM manipulator.The operation results of the PAM manipulator show that the proposed method is effective and feasible compared with the traditional PID control.
Measurements of the electrospinned polymer nanofibers showed that the fibers are not quite circular in section shape,they tend to be slightly flattened out at the top due to the effects of gravity and the surface viscosity between nanofiler and substrate,especially for the soft polymer nanofihers.Defining the diameter measured by AFM as vertical diameter,and that by SEM as horizontal diameter,the effects of two main parameters,applied electric voltage and polymer solution concentration,on the average diameter of the electrospinned PCL nanofiber were studied.The quantitative relations between the horizontal and vertical diameters of the nanofibers electropinned by the PCL solution with the concentration of 10% were obtained,and the empirical formulas were derived.The results showed that the horizotal diameter of this fiber is about 1.5 times as the vertical diameter.
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