摘要
提出了一种新型的粗糙模糊控制器的设计方法,该方法将粗糙逻辑与模糊推理结合起来,利用粗糙集寻求输入输出空间的最小规则集,通过对粗糙规则输出控制信息的补充,建立起T-S型粗糙模糊控制系统。此方法能有效地从输入输出数据中获取控制规则,同时能够解决规则数目随系统变量呈指数增长的“规则爆炸”问题。对变杆长倒立摆控制的仿真结果表明,该方法能够以较少的规则实现高精度、非线性控制。
A new type of rough fuzzy controller is proposed. The design of the controller combines the rough logic with fuzzy inference. In this approach, rough set theory is used to find the minimal set of rules of input-output space, and by complementing the information of output control corresponding to the rough reduced rules, a T-S type of rough fuzzy control system is constructed, which can derive control rules from input-output data effectively and can solve the problem that the number of rules in a fuzzy controller increases exponentially with the number of variables involved. The simulation for controlling the inverted pendulum with a varying length of pole shows that a highly precise nonlinear control is achieved.
出处
《系统仿真学报》
CAS
CSCD
2004年第3期480-484,共5页
Journal of System Simulation
基金
国家自然科学基金资助课题(50138010)
