Broad learning system(BLS), which has characteristics of fast and accuracy, is an efficient incremental learning systems based on random vector function-link network(RVFLN). In order to realize the precise prediction of time-series, a broad learning system based on reservoir computing reservoir computing broad learning systems(RCBLS) is proposed combined with the reservoir structure of echo state network(ESN). A simple circle reservoir connection is introduced in the RCBLS's enhancement layer to replace the feedforward connection of BLS, which makes the RCBLS have certain echo state characteristics and convenient for design. At the same time, incremental learning is applied to ensure RCBLS's real-time performance. Based on themultiple superimposed oscillator(MSO) time series prediction problems, the performance of the RCBLS with different reservoir structures under different scales of data sample is studied respectively. The results show that the RCBLS with multi-reservoir structure improves the generalization performance and stability greatly.