Experimental investigation on intelligent control of active lap based on CMAC neural network
A new way to control the active lap by CMAC(cerebellar model articulation controller) neural network is put forward,based on the controlling system features of nonlinear and muti-variables.Using parameters of lap surface as input variables,pulse voltages of servo control unit as output variables,the function between input and output variables could be fitted by CMAC neural network.To testify this intelligent controlling idea,an experimental platform is constructed,which is composed of an active lap and lap testing system.The lap is controlled by 3 actuate motors with its available changing caliber 420 mm,and the change of lap surface could be measured by 60 micro displacement sensor matrix.The active lap is actuated by a single motor,two motors and three motors respectively,and the errors between experimental and theoretical surface are measured.The peak-valley value are 0.99 μm,2.34 μm and 2.68 μm,and the root mean square value are 0.19 μm,0.59 μm and 0.57 μm respectively.These results testify the feasibility of active lap controlled by CMAC neural networks.