Next Article in Journal
Effects of Supply Angle on Thermal Environment of Residential Space with Hybrid Desiccant Cooling System for Multi-Room Control
Previous Article in Journal
Transient and Harmonic Unipolar Hysteresis Model of Piezoelectric Actuators Using a System-Level Approach
Previous Article in Special Issue
A Multicriteria Motion Planning Approach for Combining Smoothness and Speed in Collaborative Assembly Systems
Open AccessArticle

Modeling, Simulation, and Vision-/MPC-Based Control of a PowerCube Serial Robot

Institute of Engineering and Computational Mechanics, University of Stuttgart, Pfaffenwaldring 9, 70569 Stuttgart, Germany
*
Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(20), 7270; https://doi.org/10.3390/app10207270
Received: 21 September 2020 / Revised: 9 October 2020 / Accepted: 12 October 2020 / Published: 17 October 2020
(This article belongs to the Special Issue Robotics and Vibration Mechanics)
A model predictive control (MPC) scheme for a Schunk PowerCube robot is derived in a structured step-by-step procedure. Neweul-M2 provides the necessary nonlinear model in symbolical and numerical form. To handle the heavy online computational burden concerning the derived nonlinear model, a linear time-varying MPC scheme is developed based on linearizing the nonlinear system concerning the desired trajectory and the a priori known corresponding feed-forward controller. Camera-based systems allow sensing of the robot on the one hand and monitoring the environments on the other hand. Therefore, a vision-based MPC is realized to show the effects of vision-based control feedback on control performance. A semi-automatic trajectory planning is used to perform two meaningful experimental studies in which the advantages and restrictions of the proposed (vision-based) linear time-varying MPC scheme are pointed out. Everything is implemented on a slim, low-cost control system with a standard laptop PC. View Full-Text
Keywords: experimental studies; model predictive control; vision; automated systems; real-time control experimental studies; model predictive control; vision; automated systems; real-time control
Show Figures

Figure 1

MDPI and ACS Style

Fehr, J.; Schmid, P.; Schneider, G.; Eberhard, P. Modeling, Simulation, and Vision-/MPC-Based Control of a PowerCube Serial Robot. Appl. Sci. 2020, 10, 7270.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop