Improving Control System Performance with Nonlinear and Data-Driven Control

Overview

Traditional control methods often face challenges in handling complex systems with unknown dynamics and disturbances, prevalent in fields such as aerospace systems, manufacturing processes, and robotics. This webinar focuses on nonlinear and data-driven control methods that offer a solution to the challenges posed by complex systems. We will introduce various techniques such as sliding mode control (SMC) and iterative learning control (ILC). We will discuss the basics of these methods, their benefits, and drawbacks. Additionally, we will showcase practical demonstrations of these control methods in various applications with MATLAB and Simulink.

Highlights

• Introduction to nonlinear and data-driven control
• Algorithm fundamentals and demonstrations of nonlinear and data-driven control techniques including
  • Sliding mode control
    
  • Iterative learning control

About the Presenters

Siddharth Jawahar is a Product Manager for MathWorks with a focus on Control System Toolbox, Simulink Control Design, and Robust Control Toolbox. Siddharth has a M.S. in Electrical and Computer Engineering form Georgia Institute of Technology, specializing in control systems.

Mahaveer Satra has a MS in Mechanical Engineering from Ohio State University and B. Tech form Veermata Jijabai Technological Institute (VJTI), India. He specializes in the areas of control systems, system dynamics and robotics. In 2020, he joined Technical Support at MathWorks and later moved to the Application Engineering Group in 2021. He works with customers in industrial automation, semiconductor manufacturing, medical device, energy production and automotive industries specifically supporting workflows that involve modeling physical systems, designing controls, integrating AI workflows and PLC code generation.