This paper presents a differential evolution algorithm based on exponential smoothing (ESADE), with selfadaptive strategy and control parameters, which employs single exponential smoothing and roulette wheel selection, and adaptively selects mutation strategy for each individual from the strategy candidate pool to match different stages of the evolution according to their previous successful experience. Cauchy distribution and normal distribution are used to generate appropriate values for control parameters during the evolutionary process, and single exponential smoothing method is used to realize self-adaption. A large amount of simulation experiments are made, and experimental results show that the ESADE is better than other DE algorithms.