Industrial Automation Applications
Simulink® enables industrial equipment makers to create executable specifications in the form of models that provide clear design direction to diverse engineering groups. These example models illustrate industrial automation applications.
Featured Examples
Model and Control Robot Dynamics to Automate Virtual Assembly Line
Extends the Smart4i virtual commissioning applications to accommodate robot dynamics in the system framework to automate assembly line operation. This example models and controls the dynamics of robots in the assembly line, which helps develop a more realistic simulation environment. The virtual assembly line consists of four components: two robotic workcells, connected by a shuttle track and a conveyor belt. The first robot, Robot 1, is a Comau Racer V3 and places cups onto the shuttle. The second robot, Robot 2, is a Mitsubishi RV-4F and places balls in the cups. The shuttle track system consists of four shuttles which continuously move to Robot 1, then to Robot 2, followed by a slider. A slider then delivers those cups containing balls to a container. For a detailed system overview, see Automate Virtual Assembly Line with Two Robotic Workcells.
- Since R2024a
- Open Live Script
Anti-Windup Control Using PID Controller Block
Use anti-windup schemes to prevent integration wind-up in PID controllers when the actuators are saturated. The PID Controller block in Simulink® features two built-in anti-windup methods, back-calculation
and clamping
, as well as a tracking mode to handle more complex industrial scenarios. The PID Controller block supports several features that allow it to handle controller windup issues under commonly encountered industrial scenarios.
Bumpless Control Transfer Between Manual and PID Control
Achieve bumpless control transfer when switching from manual control to proportional integral derivative (PID) control. The model uses the PID Controller block in Simulink® to control a first-order process with dead-time.
Two Degree-of-Freedom PID Control for Setpoint Tracking
Regulate the speed of an electric motor using two degree-of-freedom PID control with set-point weighting. This model uses the PID Controller (2DOF) block. The model changes the setpoint values between 60 and 30 rpm. To convert the units to rad/s for use in the PID controller, the model uses a Signal Conversion block.
Job Scheduling and Resource Estimation for a Manufacturing Plant
Model a manufacturing plant. The plant consists of an assembly line that processes jobs based on a pre-determined schedule. This example walks you through a workflow for:
(SimEvents)
Generate Automated ros_control Plugin for 3-D Shape Tracing Manipulator
Configure Simulink® model as a 3-D shape tracing controller, and generate and deploy C++ code for the ros_control package.
(Robotics System Toolbox)
- Since R2024a
MATLAB Command
You clicked a link that corresponds to this MATLAB command:
Run the command by entering it in the MATLAB Command Window. Web browsers do not support MATLAB commands.
Select a Web Site
Choose a web site to get translated content where available and see local events and offers. Based on your location, we recommend that you select: .
You can also select a web site from the following list:
How to Get Best Site Performance
Select the China site (in Chinese or English) for best site performance. Other MathWorks country sites are not optimized for visits from your location.
Americas
- América Latina (Español)
- Canada (English)
- United States (English)
Europe
- Belgium (English)
- Denmark (English)
- Deutschland (Deutsch)
- España (Español)
- Finland (English)
- France (Français)
- Ireland (English)
- Italia (Italiano)
- Luxembourg (English)
- Netherlands (English)
- Norway (English)
- Österreich (Deutsch)
- Portugal (English)
- Sweden (English)
- Switzerland
- United Kingdom (English)