ABOUT THE COURSE: In practice, achieving 100% control objective is not the aim and allows bandwidth to achieve multiple objectives using well-known PID controller design. However, it is important to understand where is the possibility of satisfying control objectives using PID control. The course connects modern control techniques with the classical PID control approach wherever possible. This approach recognizes the strength of PID control design and suggests that it should be the preferred choice when the control objectives are not overly stringent. The systematic approach of learning applicability and limitations of PID control and their advanced variants through this course makes it beneficial for the students/professionals developing controllers for practical applications.INTENDED AUDIENCE: Community interested in learning advanced control design concepts with strong basis in practical problems.PREREQUISITES: Control engineering topics covering transfer function, state-space model and stabilityINDUSTRY SUPPORT: Control and automation, process, automobile, robotics
Overview
Syllabus
Week 1: Standard approach for practical controller design: PID structure and tuning methods; when to apply which tuning method.
Week 2:Conventional practical controller design for complex systems: The emphasis is to simplify the system model using standard methods of decoupling. The emphasis is to simplify the system model using standard methods of decoupling for designing PID controllers with feasible control objectives.
Week 3:Feedback and Control design for large-scale system: Controller designs for simplified and minimized system models
Week 4:Machine learning method for PID tuning: Data-driven methods for PID tuning, especially when the system is unmodeled
Week 2:Conventional practical controller design for complex systems: The emphasis is to simplify the system model using standard methods of decoupling. The emphasis is to simplify the system model using standard methods of decoupling for designing PID controllers with feasible control objectives.
Week 3:Feedback and Control design for large-scale system: Controller designs for simplified and minimized system models
Week 4:Machine learning method for PID tuning: Data-driven methods for PID tuning, especially when the system is unmodeled
Taught by
Prof. Leena Vachhani
