Course / Course Details
By - Parthiban AK
Students should have knowledge of calculus, differential equations, and basic linear algebra to analyse dynamic systems. Prior exposure to circuits, sensors, actuators, and basic system modelling is recommended. Familiarity with programming and engineering simulation tools will help students model and evaluate control system performance. Understanding block diagrams, transfer functions, and feedback concepts is beneficial. Students should be comfortable with analytical thinking, problem solving, and teamwork. This background enables learners to effectively study control strategies, controller design, and intelligent automation techniques used in modern engineering applications.
This course introduces fundamental and advanced control system concepts used in engineering and industrial automation. Students learn the differences between open-loop and closed-loop systems and the importance of feedback in improving stability and accuracy. The course focuses on PID controller design and tuning for real-world applications. Advanced topics include adaptive control and fuzzy logic control for handling uncertainty and nonlinear behaviour. Through simulations and case studies, students explore system modelling, performance analysis, and controller implementation, preparing them to design reliable and efficient automation systems.
After completing the course, students will be able to differentiate between open-loop and closed-loop control systems and apply PID control principles to design stable automation solutions. They will implement adaptive control techniques to optimize system performance in uncertain environments and use fuzzy logic control to manage systems with imprecise data. Students will analyse and evaluate control system performance using modern tools and demonstrate the ability to design and optimize intelligent control systems that improve efficiency, reliability, and automation in engineering applications.
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