Abstract: Multi-model adaptive control, as an improved method of classical adaptive control, can effectively solve the control performance issues for the complex systems with large parameter uncertainties. It has attracted increasing attention from scholars, and a vast array of research results have been achieved in theory and practice. According to the different synthesis methods of multiple local controllers corresponding to the multiple local models, the multi-model adaptive control scheme can be divided into different categories. This paper provides a survey of weighted multi-model adaptive control (WMMAC). The basic idea of the WMMAC is to adopt the method of “divide and conquer”; multiple local models and corresponding multiple local controllers are established offline, and the control outputs of local controllers are integrated online, such that the global control law can be formed. The WMMAC is a promising method to achieve strong robustness and a self-adaptive ability for control systems. First, we presented the development process and the main problems of the WMMAC. Then, the research status of control systems and the latest progress were shown, including model set construction and weighting algorithm design. To improve the rationality of model set construction, WMMACs with self-tuning model and even a dynamic model set have been developed. Meanwhile, to reduce the calculation burden, a new weighting algorithm has been designed, which is based on the model output errors of the multi-model adaptive control system. Especially for system stability analysis, which has always been a recognized problem in the WMMAC system, some research results have been obtained. The proof of system stability in the general sense has been given preliminarily by introducing the theory of virtual equivalent system. This paper gave a review of WMMAC in the order of the variation on the structure, the development of algorithms and its applications. Furthermore, the main problems in the control system were analyzed, and some potential research directions, which are the difficulties and emphases of future research including model set, weight calculation, disturbance rejection, stability, were pointed out.