From the series: Improving Your Racecar Development
Christoph Hahn, Daniel Weida, MathWorks
To demonstrate the principles of control design in Simulink® and MATLAB®, Daniel Weida and Christoph Hahn, of MathWorks, show how to control a throttle. Developing a plant model in Simulink, as done with the throttle example, is a basic starting point for controlling a system. From this point, Daniel and Christoph create a robust controller capable of withstanding possible uncertainties and adjust the response to certain requirements using optimization.
In this throttle model, a PID controller (standard for linear controls) is first added to create a control loop. A signal builder block is used for flexibility, grouping of multiple signals, and simulating multiple scenarios. The simulation results can then be viewed with the Scope feature, even if there are multiple signals.
After simulating the realistic behavior of the throttle, the next step is to improve the system behavior. It can be influenced through Simulink by optimizing the controller parameters. You can tune the overall system in Simulink and see a direct comparison of performance and robustness. A workflow to overcome uncertainties can also be created to affect quality control. Uncertainties for all parameters make your simulation more realistic and Daniel uses the Robust Control Toolbox™ to show how to identify the worst case scenario. He then explores the topic of optimization and how to model a controller without violating specified restrictions. Optimization helps to define requirements in a system and is a very powerful tool in control design.
Despite a lot of mathematics, with the user-friendly tools available for control design it is very feasible. Following the Simulink control design workflows helps to create robust and stable designs. The worst-case analysis feature for uncertain systems is a great tool to mitigate problems in the future and the optimization capabilities act as a bridge between the model and the real world, ensuring that the control system behaves in a compatible manner. Further material on control design can be found in the links below.
MATLAB and Simulink Racing Lounge: Vehicle Modeling, Part 4: Simscape Multibody Ed Marquez and Christoph Hahn from MathWorks show you a Simscape Multibody model that represents vehicle dynamics with 3D visualization.
MATLAB and Simulink Racing Lounge: Vehicle Modeling, Part 3: Simscape Ed Marquez and Christoph Hahn from MathWorks show you how to create vehicle models for simulations of different powertrains using Simscape. Simscape is the language of physical modeling and it also allows users to model multi-domain systems.
MATLAB and Simulink Racing Lounge: Vehicle Modeling, Part 2: Powertrain Blockset Ed Marquez and Christoph Hahn from MathWorks show you how to create vehicle models with Powertrain Blockset for simulations of different powertrains to help you make informed decisions during the design process.
MATLAB and Simulink Racing Lounge: Vehicle Modeling, Part 1: Simulink Ed Marquez and Christoph Hahn from MathWorks show you how to create vehicle models for simulations of different powertrains to help you make informed decision during the design process.
MATLAB and Simulink Racing Lounge: Remote Control Racecar, Part 2: Integrating CAN Data into Your Simulation Use Simulink to access data directly from your vehicle’s CAN bus and then integrate it into your simulations. Increase fidelity of existing simulations by replaying test data through virtual CAN channels without the need for further data processing.
MATLAB and Simulink Racing Lounge: Remote Control Racecar, Part 1: Programming ECUs Using Simulink Hardware Support Save valuable development time by programming custom ECUs and vehicle controllers with the hardware support packages available for Simulink.
MATLAB and Simulink Racing Lounge: Importing CAD Assemblies into Simscape Multibody Christoph Hahn, of MathWorks, shows you how to import CAD assemblies into Simscape Multibody using Onshape.
MATLAB and Simulink Racing Lounge: Real-Time Simulation and Testing of a Throttle Valve Controller Learn how to use Simulink Real-Time for rapid control prototyping and hardware-in-the-loop (HIL) testing. Naga Pemmaraju and Christoph Hahn guide you through real-time testing for a throttle valve controller using the Simulink Real-Time Explorer.
MATLAB and Simulink Racing Lounge: Using Simscape for Automotive System Development - A Google Hangout Watch the recording of a live Google Hangout where Steve Miller and Christoph Hahn, of MathWorks, present ways to use Simscape for automotive system development.
MATLAB and Simulink Racing Lounge: Updates to Simscape Products in R2016a Improve your Simscape workflow by benefitting from updates to Simscape products in R2016a. Sebastian Castro and Christoph Hahn introduce you to automotive relevant updates.
MATLAB and Simulink Racing Lounge: Developing Algorithms for ADAS Systems with MATLAB and Simulink Marco Roggero and Christoph Hahn, of MathWorks, explain how MATLAB and Simulink can assist in the development of an advanced driver assistance system. They will cover lane tracking, adaptive cruise control, and sensor fusion.
MATLAB and Simulink Racing Lounge: A MicroAutoBox Workflow Frank Schmidtmeier, of dSPACE, and Christoph Hahn, of MathWorks, guide you step-by-step through the workflow from reading sensor data to your Simulink model to auto-generated C code running on the ECU.
MATLAB and Simulink Racing Lounge: Processing CFD Simulation Data Use the matrix processing capabilities of MATLAB to work with your CFD simulation data. Christoph Hahn and Nicolas Gautier from MathWorks demonstrate how to get results into MATLAB and perform analyses. Find all models on the MATLAB FileExchange.
MATLAB and Simulink Racing Lounge: What Judges Are Looking For What are judges looking for in evaluating engineering design? Learn how to persuade them by focusing on simple, coherent approaches that make your car faster, and clear communication of your core message.
MATLAB and Simulink Racing Lounge: Modeling Vehicle Dynamics Model your vehicle dynamics for lap-time simulation, prediction of energy consumption, or to tune your suspension system. Christoph Hahn, Sebastian Castro, and Swarooph Seshadri, of MathWorks
MATLAB and Simulink Racing Lounge: Virtual Test-Driving Model and validate your race car in a virtual environment. Prasanna Kannan, of IPG, and Christoph Hahn, of MathWorks, introduce you to the benefits of Simulink and the IPG CarMaker.
MATLAB and Simulink Racing Lounge: Basics of Code Generation Spend more time on algorithm development and less time manually producing code. Christoph Hahn and Andreas Uschold of MathWorks discuss how to efficiently bring algorithms to C/C++ code and hardware with code generation.
MATLAB and Simulink Racing Lounge Modeling Physical Components, Part 2: Data Driven Concepts Learn a variety of modeling methods to fit your racecar needs. We’ll demonstrate five modeling approaches and share tips on how to choose the right model. Also, find all models used in the episode on the MATLAB Central FileExchange.
MATLAB and Simulink Racing Lounge: Modeling Physical Components, Part 1: Mathematical Models Model the physical systems of your racecar and learn about the variety of modeling methods to fit your needs. Sebastian Castro and Christoph Hahn, of MathWorks, demonstrate five modeling approaches and share tips on how to choose the right model.
MATLAB and Simulink Racing Lounge: Principles of Control Design Create a robust controller with a Simulink
MATLAB and Simulink Racing Lounge: CAN Communication with Your ECUs and the Vehicle Network Toolbox Connect your Controller Area Network (CAN) to MATLAB and Simulink using the Vehicle Network Toolbox to inspect, test, and validate the operation of a vehicle before an actual dynamic event.
MATLAB and Simulink Racing Lounge: Determining Chassis Stiffness with MATLAB Christoph Hahn, technical education specialist at MathWorks, introduces you to an efficient approach to determine structural properties of a steel tube frame using the direct stiffness method.
MATLAB and Simulink Racing Lounge: Battery Modeling with Simulink Javier Gazzarri and Christoph Hahn introduce you to battery modeling using Simulink.
MATLAB and Simulink Racing Lounge: Embedded Code Generation for Your Vehicle Control Systems Tobias Kumschmider and Christoph Hahn introduce you to the MathWorks Code Generation tool chain, provide information about supported platforms, and show the capabilities in a process-in-the-loop (PIL) software demo.
MATLAB and Simulink Racing Lounge: CAD Import in SimMechanics Learn how to Import a CAD assembly into SimMechanics using SimMechanics Link via a plug-in that lets you save your CAD file as an XML file, or an API that you connect to your CAD system.
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