Control Theory is the study of how to influence the behavior of dynamical systems using feedback. This course introduces the fundamental concepts and techniques used in the analysis and design of control systems. It covers both continuous and discrete systems, emphasizing the importance of stability, performance, and robustness in practical applications. Key topics include system modeling, transfer functions, stability analysis, time-domain and frequency-domain response analysis, controllers (PID controllers, state-space models), and control system design techniques. Students will gain a deep understanding of how control theory is applied in various engineering fields, such as electrical, mechanical, aerospace, and chemical engineering, to automate and optimize systems.
Key Learning Objectives:
- Understand the principles of feedback and its role in system control.
- Learn the mathematical foundations of dynamic systems and their models.
- Analyze the stability of control systems using methods like root locus, Bode plots, and Nyquist criteria.
- Design controllers to meet desired specifications for system performance and stability.
- Apply control theory to real-world problems in automation, robotics, and other engineering fields.
Topics Covered:
- Introduction to Control Systems
- Mathematical Models of Systems
- Transfer Functions and State-Space Representation
- Stability Analysis (Routh-Hurwitz, Nyquist, Bode plots)
- Time Domain Analysis (Impulse Response, Step Response)
- Frequency Domain Analysis (Bode Plots, Nyquist Diagrams)
- Feedback and Sensitivity Functions
- Control System Design Methods (PID Control, Lead-Lag Controllers)
- State-Space Analysis and Control Design
- Control System Implementation and Real-World Applications
This course is ideal for students and professionals who seek to understand the dynamic behavior of systems and how to manipulate them to achieve specific goals. It serves as a foundation for more advanced topics in robotics, automation, and systems engineering.