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目前，已经实用化了的模糊控制几乎都是Ｍａｍｄａｎｉ提出的Ｍａｘ－Ｍｉｎ－重心法。当控制性能达不到要求时，需增设人工神经网络等附加功能。然而这会加大模糊控制的成本，尤其是会失掉模糊控制的易理解、易干预、易修正的长处。为此，从理论上证明Ｍａｍｄａｎｉ控制法的缺陷，提出以贡献度最大值为中心的模糊控制方法，并通过实例验证本方法的有效性及实用价值。
At present, almost all the fuzzy control that has been put into practical use is the Max-Min-center of gravity method proposed by Mamdani. When the control performance can not reach the requirement, additional functions such as artificial neural network need to be added. However, this will increase the cost of fuzzy control, in particular, will lose the fuzzy control of easy to understand, easy to intervene, easy to amend the strengths. Therefore, theoretically prove the shortcomings of the Mamdani control law, put forward the fuzzy control method centering on the maximum contribution degree, and verify the effectiveness and practical value of this method through examples.