基于T-S模型的模糊神经网络PID控制

针对在非线性、时变不确定系统中，常规PID控制器难以获得满意效果的问题，仿照传统PID控制器结构，设计了一种基于T-S模型的模糊神经网络PID控制器。该控制器基于T-S模糊模型，将PID结构融入模糊控制中，充分发挥了模糊系统非线性、可解释性的特点；然后又利用神经网络的学习算法，实现了对模糊控制器的参数调整，使控制器具有了适应时变、不确定系统的自学习和自组织能力。针对非线性、时变系统，将此控制器与传统PID控制器对比进行了仿真研究，并应用于啤酒发酵领域，其结果表明，该控制器取得了令人满意的效果。

Fuzzy Neural Network PID Control Based on T-S Model

To the problem that PID controller is difficult to achieve efficient control of time variable and nonlinear plants, a fuzzy neural network PID controller based on T-S model is designed by imitating the structure of the conventional digital PID controller. This structure with T-S fuzzy, model takes a good use of characteristics of nonlinear and interpretation of fuzzy theory. The abilities of self-study and self-organlze of neural network can regulate parameters of fuzzy structure. Simulations results of beer fementation shows that these performances and implementations can be applied to time variable and nonlinear plants.