We may earn an affiliate commission when you visit our partners.

Control Theory

Save
May 1, 2024 Updated May 8, 2025 20 minute read

An Introduction to Control Theory

Control theory is a fascinating and vital interdisciplinary field that blends engineering and applied mathematics. It focuses on understanding and influencing the behavior of dynamical systems—systems that change over time—in engineered processes and machines. The core objective is to develop models and algorithms that apply inputs to a system to guide it to a desired state. This is done while aiming to minimize undesirable effects like delays, overshoots, or errors, and ensuring the system remains stable. Imagine trying to keep a self-driving car perfectly in its lane or maintaining a precise temperature in a chemical reactor; these are tasks where control theory is indispensable.

Working with control theory can be incredibly engaging. It allows you to design the "brains" behind automated systems, tackling complex problems that have real-world impact. From crafting the flight control systems for aircraft to optimizing energy grids for efficiency, the applications are vast and often at the forefront of technological advancement. Furthermore, the field constantly evolves, integrating new ideas from areas like artificial intelligence and machine learning, presenting continuous learning opportunities and exciting challenges.

What is Control Theory?

Share

Help others find this page about Control Theory: by sharing it with your friends and followers:

Reading list

We've selected 29 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Control Theory.
Another highly regarded textbook for a first course in control theory, particularly at the senior undergraduate or graduate level. It offers comprehensive coverage of continuous-time control systems, including classical and state-space approaches. The book is known for its clear explanations and numerous solved examples, making it a valuable resource for solidifying understanding. It standard text in many engineering departments.
This very popular and widely used textbook for undergraduate control systems courses. It covers a broad range of topics with a strong emphasis on design and practical applications. The book is known for its clear explanations and extensive examples, making it excellent for gaining a broad understanding. It is often recommended as a first book in control theory.
Provides a comprehensive treatment of optimal control. It covers a wide range of topics, from the basics of optimal control to advanced topics such as dynamic programming and Pontryagin's maximum principle.
Provides a comprehensive treatment of robust control design. It covers a wide range of topics, from the basics of robust control to advanced topics such as H-infinity control and LMI methods.
A widely recognized graduate-level textbook focusing on the analysis and control of nonlinear systems. It is essential for those looking to deepen their understanding beyond linear control and standard reference in the field. The book builds mathematical sophistication gradually and covers essential topics like Lyapunov stability and feedback linearization.
A comprehensive and in-depth treatment of dynamic programming and optimal control. This multi-volume set definitive reference for researchers and advanced graduate students in the field. It covers a wide range of topics and provides a deep theoretical understanding of optimal control techniques.
Provides a clear and concise introduction to feedback systems. It is an excellent resource for students and practitioners who want to learn about the basics of control systems.
Cornerstone for understanding the theoretical underpinnings of control theory, focusing on linear differential equations from the perspective of control and estimation. It is particularly well-suited for graduate-level students and provides the necessary background for advanced modern control design techniques. It valuable reference for deepening one's understanding of the mathematical framework.
Provides a comprehensive treatment of control theory for linear systems. It covers a wide range of topics, from the basics of control theory to advanced topics such as robust control and nonlinear control.
Provides a comprehensive treatment of process control. It covers a wide range of topics, from the basics of process control to advanced topics such as model predictive control and nonlinear control.
Provides a comprehensive treatment of control systems theory and applications. It covers a wide range of topics, from the basics of control theory to advanced topics such as robust control and nonlinear control.
Provides a comprehensive overview of control theory. It is an excellent resource for students and practitioners who want to learn about the fundamentals of control systems.
Serves as a good introduction to the principles and techniques of optimal control theory. It is suitable for advanced undergraduate or graduate students interested in optimizing the performance of control systems. It covers topics such as dynamic programming and Pontryagin's minimum principle, providing a solid foundation in this important area.
Provides a rigorous mathematical treatment of control theory, focusing on deterministic finite-dimensional systems. It is suitable for graduate students and researchers with a strong mathematical background who want to delve into the theoretical depths of the subject. It valuable reference for advanced study.
This advanced textbook focuses on the analysis and design of multivariable control systems, which are common in complex engineering applications. It is suitable for graduate students and researchers working on more advanced control problems. It builds upon the foundations of linear control theory.
Provides a rigorous mathematical treatment of the control and manipulation of robotic systems. It classic in the field and is suitable for graduate students and researchers with a strong mathematical background interested in the theoretical aspects of robotic control.
Focuses on the algorithmic and mathematical foundations of robot motion planning and control. It provides a deeper dive into the specific control challenges in robotics, complementing general control theory texts. Suitable for graduate students and researchers in robotics and control.
This collection of seminal papers offers a historical perspective on the development of control theory. It is valuable for understanding the origins of key concepts and the evolution of the field. While not a textbook for learning the fundamentals, it is excellent for gaining a deeper appreciation of the classic contributions to control theory.
Although a machine learning book, this text is relevant due to the increasing overlap between control theory and machine learning, particularly in areas like reinforcement learning and system identification. It provides a strong foundation in the probabilistic and statistical methods used in modern control and estimation. Suitable for advanced undergraduate and graduate students.
Table of Contents
Our mission

OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.

Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.

Find this site helpful? Tell a friend about us.

Affiliate disclosure

We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.

Your purchases help us maintain our catalog and keep our servers humming without ads.

Thank you for supporting OpenCourser.

© 2016 - 2025 OpenCourser