本课程分为混沌控制与复杂网络两个既相对独立又具有内在联系的部分。总的目的是希望通过本课程的学习，使学生了解这两个复杂系统研究中的新方向，向学生传授发现与把握新方向的能力。混沌控制部分：分岔与混沌是非线性动态系统的典型的复杂动力学行为，也一直是非线性科学的中心研究内容。本课程的目的是使学生掌握分岔与混沌的基本概念，熟悉分析分岔与混沌行为的基本工具，了解分岔与混沌控制及其工程应用前景。主要教学内容包括：（1）介绍动力系统的基本概念，包括吸引子，不变流形，结构稳定性，分岔等。（2）重点介绍混沌动力学的基本知识，包括混沌的判别方法等。（3）介绍混沌控制的基本原理与方法，包括OGY方法，前馈方法和各种工程反馈控制方法。（4）介绍分岔控制的基本原理与方法。（5）介绍混沌同步及其在通信中的应用。（6）介绍用反馈控制的方法产生混沌的反馈混沌化理论与方法。复杂网络部分：本部分的目的是使学生了解复杂网络研究在近几年取得的重要进展，以及所面临的许多挑战性问题。该部分将有意识地培养学生发现与把握新方向的能力。主要教学内容包括：（1）基本概念，包括平均路径长度，聚类系数和度分布等。（2）复杂网络模型，包括随机图，小世界与无尺度网络模型等及其对互联网的建模。（3）复杂网络的传播动力学。（4）复杂网络中的同步与控制。（5）复杂网络的混沌迁移。（6）复杂网络的博弈合作行为。

This course is composed of two interconnected parts: chaos control and complex networks, the goal of which is introducing these two new active research branches of complex system to students, and help them to be capable of discovering and mastering new research directions. The part of chaos control: As the two typical complex dynamic behaviors of nonlinear dynamic systems, Bifurcation and chaos are the key topic of studying nonlinear science. In this course, the students are predicted to grasp the basic definitions of bifurcation and chaos, to understand the tools of analyzing bifurcating and chaotic behaviors, and to know how to control bifurcations and chaos and their engineering applications as well. The main contents include: (1) the introduction to the basic concepts of dynamic systems, including attractors, invariant manifold, structural stability, and bifurcations; (2) the main framework of chaotic dyanmics, including the definitions of chaos; (3) the principles of methods of chaos control, including the OGY method, the feedforward method, and kinds of feedback methods in practice; (4) the principle of bifurcation control and methods; (5) chaos synchronization and its application in secure communication; (6) the theory and algorithms of feedback chaotification to generate chaos.The part of complex networks: This part is to introduce the latest progress of complex networks theory as well as those challenging problems still left open to students, who will be led to improve their capability of discovering and mastering a new branch. The main contents include: (1) Basic definitions of networks, including average path length, clustering coefficient, degree distribution, and etc. (2) the models of complex networks, including random graph, small-world models, scale-free models, and their application to model the evolving topology of the Internet; (3) the spreading dynamics on complex networks; (4) synchronization and control of complex networks; (5) chaotic transition on complex netwoks; (6) the cooperative behaviors of playing games on complex networks.