From the series: Making Control System Development Easier with MATLAB and Simulink
Doug Eastman, MathWorks
This is the second 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 plant modeling for control design. MathWorks engineers will present several approaches for creating plant models in Simulink. Through product demonstrations they will show how you can create and refine plant models by:
• Using first-principles modeling
• Using experimental test data for system identification
• Importing existing CAD assemblies
• Using test data to estimate model parameters
The first webinar in this series introduced how you can use dynamic simulation to model, design and verify control systems before testing on hardware. The remaining two webinars will detail the aspects of designing the control system (part 3), and testing the control system through simulation and 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.