基于T-S模型的智能PID控制  

Fuzzy Neural Network PID Control Based on T-S Model

作　　者：李丙才[1] 叶碧成[1] 姜映红[1] 

机构地区：[1]兰州理工大学机电学院,甘肃兰州730050

出　　处：《甘肃科学学报》2007年第1期118-121,共4页Journal of Gansu Sciences

摘　　要：提出一种基于分段线性模糊模型的T-S模型,并与传统P ID控制器相结合设计了一种模糊神经网络P ID控制器,它具有模糊系统非线性、可解释性的特点,神经网络的自学习和自组织功能.对其进行非线性时变系统仿真,仿真结果表明该控制器较常规P ID控制器的调整时间可明显缩短.The PID controller has been used in a wide range of operating conditions, but it is difficult to achieve efficient control of time variables and nonlinear plants. With the development of fuzzy control, the controller combined with PID was utilized, which can improve the implementation efficiently, but it is not suitable for control of time variables because it lacks the ability of self-study and self-organization. The present design of a fuzzy neural network PID controller based on T-S model is similar to that of the conventional digital PID controller. This structure can express the nonlinear and interpret ability of fuzzy systems, and neural network implementation can make systems self-study and self-organize. The simulations demonstrate satisfactory results of these performances and implementations which are better than those of conventional PID control applied to a nonlinear plant.

关 键 词：模糊动态线性模型 模糊控制 神经网络 PID控制器 

分 类 号：TP273.3[自动化与计算机技术—检测技术与自动化装置]