simulink student challenge -凯发k8网页登录
mathworks announces the winners of the 2017 simulink student challenge. congratulations and thanks to all the students who entered.
1st place
industrial robot control using matlab and simulink
far eastern federal university - boris notkin
the robopendulum project demonstrates how to control the dynamics of an industrial robot in real time using data obtained from various sensors. to visualize and investigate the kinematics of the robot, simscape multibody is used. the position and angle of the robot’s pendulum is controlled using model-based predictive control combined with artificial neural networks and a kalman filter. simulink desktop real-time is then used to incorporate measurements from a force-torque sensor into the control system for the robot using udp to implement disturbance suppression and oscillation reduction. additionally, the computer vision toolbox and image acquisition toolbox are used to control the position of the robot using colored balls. this project is an example of how to utilize real-world data to design and implement the models that can control intricate robotic systems.
2nd place
spacecraft dynamics and control simulator
the university of the basque country/basque center for applied mathematics - abolfazl shirazi
this flight simulator allows the user to model many aspects of spacecraft design, including a vehicle's structure, propulsion system, and guidance and control system. the spacecraft dynamics and control simulator then takes your vehicle into orbit, giving impressive 3d visualizations of orbital path and vehicle orientation in an impressive simulation of space flight.
3rd place
real-time bubble measurement
technical university of kaiserslautern - johannes mader
the real-time bubble measurement project uses simulink to optically measure the size of bubbles in real-time. knowledge of bubble volume and surface area is important for applications including multi-phase reactions between liquid and gaseous compounds, and this technique provides a method to rapidly measure these bubble parameters. for this project, a simulink model was used to acquire camera data, process the images, calculate bubble parameters, and save data for further analysis. this video demonstrates how the powerful image processing algorithms in matlab and simulink can be used to create an elegant measurement tool.