中文摘要：

DeGroot 模型一个经典模型到意见的学习一致在里面一组个人(代理人) 。一致能在一些情形下面被完成。但是什么时候这个组到达一致与一条会聚的意见珍视哪个不是我们期望什么，怎么罐头我们干涉系统和变化会聚的价值？在这糊机制命名软控制首先在意见动力学被介绍当人口被给，进化统治时，指导组意见不被允许变化。根据软控制的想法，一或几个特殊代理人，叫的党羽，被增加并且与在原版的代理人组织的或几正常连接了。党羽行动并且被当作正常代理人。作者证明会聚的意见价值的变化被起始的意见和党羽的有影响的价值决定，以及党羽怎么与正常连接代理人。有趣、违反直觉的现象被发现：与更小的起始的意见价值增加一个党羽(或更大) 与比原版会聚的意见价值剂量未必减少(或增加) 在一些条件下面的会聚的意见价值。这些条件通过数学分析被给，他们被数字测试验证。当一个党羽被连接到不同正常时，作者也发现系统的集中速度变化代理人。我们的模拟证明它是断然与连接正常的度有关在没有规模的网络的代理人。

英文摘要：

The DeGroot model is a classic model to study consensus of opinion in a group of indi- viduals （agents）. Consensus can be achieved under some circumstances. But when the group reach consensus with a convergent opinion value which is not what we expect, how can we intervene the system and change the convergent value？ In this paper a mechanism named soft control is first intro- duced in opinion dynamics to guide the group＇s opinion when the population are given and evolution rules are not allowed to change. According to the idea of soft control, one or several special agents, called shills, are added and connected to one or several normal agents in the original group. Shills act and are treated as normal agents. The authors prove that the change of convergent opinion value is decided by the initial opinion and influential value of the shill, as well as how the shill connects to normal agents. An interesting and counterintuitive phenomenon is discovered： Adding a shill with an initial opinion value which is smaller （or larger） than the original convergent opinion value dose not necessarily decrease （or increase） the convergent opinion value under some conditions. These conditions are given through mathematical analysis and they are verified by the numerical tests. The authors also find out that the convergence speed of the system varies when a shill is connected to different normal agents. Our simulations show that it is positively related to the degree of the connected normal agent in scale-free networks.