多值逻辑学习控制

本文提出一种由多个既关联又独立的子网络构成的用于逼近非线性函数的多值学习网络（ＫＬＮ），并在此基础上，研究了具有自学习功能的多值逻辑控制。网络运算主要为整数的加法和逻辑判断。仿真结果表明，基于ＫＬＮ的多值逻辑控制系统对复杂非线性系统具有良好的学习控制性能，且具有计算简单和省时的特点。

Multi-Valued Logic Learning Control

Constructed by a set of distributively associated subnets, a multi-valued learning network (KLN) is proposed in this paper for approximating nonlinear function. Based on the proposed netword, the multivalued logic control is further studied. Network operations are mainly integer addition and logic judgment. Simulation results show that the KLN-based multi-valued control system is strong in self-learning and simple in computation, and has good learning control performance for complex nonlinear systems.