This course mainly focuses on linear system theory of state-space models, including four parts,

1. State-space representations and solutions,

2. Controllability and observability, State feedback and state observers,

3. Lyapunov stability theory,

4. Linear quadratic control

Through the study of the course, we can understand the basic concepts and analysis methods for linear multivariable control systems, and firmly grasp the design methods for linear time-invariant systems.

The primary aim of this course is to train the undergraduates from college of automation and some other related disciplines with modern control tools. After ending of this course, the undergraduates of automation field and other related disciplines should be able to have a better understanding of the basic techniques of analysis and synthesis of linear multivariable control systems and satisfy some basic requirements such as methods of modeling using state space, controllability and observability of linear multivariable control systems and design of state observer, optimal control of such systems.

Some prerequisites are needed for studying the course, they are:

1. Linear Algebra

2. Differential Equations

3. Theory of Matrix

4. Principles of Automatic Control.

Here we also list two reference books:

[1] 蒋国平，丁洁，吴冬梅. Modern Control Theory [M]. 北京邮电大学出版社, 2021.

[2] Ogata, K., & Yang, Y. (2002). Modern Control Engineering [M]. Prentice Hall.

[3] Hespanha, J. P. (2018). Linear Systems Theory [M]. Princeton University Press.