多模型自适应控制,作为传统自适应控制算法的改进, 在处理具有较大不确定性系统时具有显著的性能提升,也在近二十年中吸引了越来越多的研究关注.文章首先对多模型自适应控制的研究进展做了整体简要的探讨, 然后分别针对常用的多模型自适应控制算法进行了深入讨论,从算法思想,流程和主要结论等方面作了详细的分析.最后,分析指出了多模型算法研究工作中尚存在的问题和进一步的研究方向.

Multiple model adaptive control scheme, which is developed from conventional adaptive control scheme, performs much better when the system uncertainty is large. It gains more and more research interest in the last two decades and a lot of work has been done in this area. In this paper, we first present some brief discussions about the research status of multiple model adaptive control, and then we focus on the commonly used multiple model adaptive control schemes. The details about the mains ideas, structures and conclusions are given for different multiple model schemes. At last, the potential future work of multiple model scheme is analyzed.