light of operation affected by friction, parameter identification of a continuous differentiable friction model is introduced based on an improved cuckoo search algorithm (ICSA) to precisely control electric load simulators. First, the experimental prototype of an electric load simulator is set up, and the dynamic mathematical model is established in the way of a continuous friction model instead of the discontinuous common one. Second, the traditional CSA algorithm is improved by adjusting the values of the decision probability and the step size during the identification process, which accelerates the convergence speed and increases the accuracy. Then, the friction-velocity data with the speed range of ［－1, 1］ rad/s is obtained by the point-by-point experiment method, and six parameters of the friction model are identified using the ICSA. Finally, verification experiments are conducted. The results show that the six parameters of the friction model are identified correctly and quickly by ICSA. The convergence speed and accuracy are improved compared with that of the traditional CSA, and the value of the cost function ICSA algorithm is reduced by 45.2% when the number of iterations reaches the maximum value.