Intelligent Control Strategy Based On Fuzzy Logic And Artificial Emotion

This thesis focuses on the intelligent control strategies based on fuzzy logic and artificial emotions. As an important part of the advanced control methods, intelligent control has been well researched and developed in recent years, and a number of approaches to the application of intelligent control have been introduced. This thesis first presents the fundamentals of fuzzy logic, neural networks and learning control, and then introduces the concepts and research achievements of artificial emotions. Moreover, this thesis proposes two novel strategies: the weighted fuzzy control strategy for multi objects and the behavior control strategy based on emotion evaluation and associative learning, and these two strategies are applied on an invert-pendulum system and a simulative agent system, respectively. And theexperiment and simulation results prove the validity of these two strategies.Chapter 1 briefly introduces the backgrounds, main contents and new ideas of this thesis.Chapter 2 presents the theories of fuzzy sets and fuzzy logic.Chapter 3 browses the history, and introduces the fundamentals and typical instances of neural networks. Meanwhile, the NN-based approaches to the application of intelligent control are presented in this chapter.Chapter 4 proposes the concepts and the current research situations of artificial emotions.Chapter 5 introduces a novel fuzzy control strategy and then applied it on an invert-pendulum system. Moreover, the experiment result analysis is also presented.Chapter 6 presents an emotion-based behavior control strategy in details, and then analyzes the simulation results.Chapter 7 summarizes the work of this thesis, and then gives the conclusions.