From the series: Making Control System Development Easier with MATLAB and Simulink
Arkadiy Turevskiy, MathWorks
Michael Carone, MathWorks
This is the third webinar of a four-part webinar series that will highlight the use of MathWorks products for designing or updating a control system by using a digital motion control case study.
This particular webinar will concentrate on controller design. Through product demonstrations MathWorks engineers will show how you can design feedback compensators and control logic. Specifically, they will show how to:
• Graphically design a notch filter
• Tune a PID compensator using optimization-based methods
• Discretize of a continuous-time controller
• Develop and test fault detection logic
The first webinar introduced how you can use dynamic simulation to model, design and verify control systems before testing on hardware. The second webinar covered plant modeling for control design. The last webinar will detail the aspects of testing the control system through real-time testing (part 4).
Through this webinar series MathWorks engineers will demonstrate how you can:
• Catch errors early in the development process where they are easier and cheaper to fix.
• Troubleshoot existing design problems systematically and effectively, without tying up actual hardware systems
• Test more thoroughly, by starting before hardware is available and by simulating conditions that would be dangerous or costly to examine with real hardware
• Try different control strategies safely and quickly
This will help you reduce development time and costs, improve quality, and deliver systems with higher performance and efficiency.
Recorded: 19 Jan 2010
Making Control System Development Easier with MATLAB and Simulink, Part 1: Introduction to Dynamic Simulation
Learn how to use dynamic simulation to model, design, and verify control systems before testing on hardware.
Making Control System Development Easier with MATLAB and Simulink, Part 2: Plant Modeling
Learn different plant modeling techniques from first-principles modeling to importing CAD assemblies to system identification.
Making Control System Development Easier with MATLAB and Simulink, Part 3: Control Design
Learn how to analyze and design control systems, using techniques such as graphical design of a notch filter, automatic PID controller tuning, discretization of continuous-time controller, and development of fault detection logic.
Making Control System Development Easier with MATLAB and Simulink, Part 4: Real-Time Testing
Learn how to build and execute real-time tests, and connect those tests to hardware, for realistic functional testing of a control system.