Vision-Based Model Predictive Control of Wheeled Mobile Robot

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

Khonsarian R.; FARROKHI M.

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: Modares Mechanical Engineering Year:2019 | Volume:19 | Issue:7 Page(s): 1767-1777

Download Full-Text

Persian Verion

View:

567

Download:

Cites:

Information Journal Paper

Title

Vision-Based Model Predictive Control of Wheeled Mobile Robot

Author(s)

Khonsarian R. | FARROKHI M. | Issue Writer Certificate

Keywords

Model Predictive ControlQ1

OptimizationQ1

Projection Recurrent Neural NetworkQ1

Nonholonomic Mobile RobotQ2

Fuzzy SystemQ2

Abstract

In this article, a novel control of wheeled mobile robot based on machine vision is considered. One of the common methods for controlling such systems is the use of Model Predictive Control (MPC) algorithms. In these systems, the response speed of the control algorithm and the optimality of these are two basic factors for achieving the optimal performance. Also, the impossibility of achieving precise values of the robot parameters and their variation during the operation of the robot is an important challenge in the implementation of the controller, therefore, this paper focuses on real-time and robust MPC, so that it can ensure the system against uncertainties and environmental disturbances in addition to the optimal and real-time response. Hence, the Optimization based on Projection Recurrent Neural Network (PRNN) has been used as an optimizer to reduce the calculation time cost. The combination of PRNN Optimization with MPC leads to new formulation and constraints that are considered to be the article innovations. Finally, in order to verify the validity of the proposed algorithm, the robot passes through the corridor with the presence of obstacles, which is simulated in the V-REP software. The results show that the optimum control input speed has been increased in comparison with similar methods, and the optimal path selection by the Fuzzy System in the presence of obstacles has been well suited.

Cites

No record.

References

No record.

Cite

APA: Copy

Khonsarian, R., & FARROKHI, M.. (2019). Vision-Based Model Predictive Control of Wheeled Mobile Robot. MODARES MECHANICAL ENGINEERING, 19(7 ), 1767-1777. SID. https://sid.ir/paper/178000/en

Vancouver: Copy

Khonsarian R., FARROKHI M.. Vision-Based Model Predictive Control of Wheeled Mobile Robot. MODARES MECHANICAL ENGINEERING[Internet]. 2019;19(7 ):1767-1777. Available from: https://sid.ir/paper/178000/en

IEEE: Copy

R. Khonsarian, and M. FARROKHI, “Vision-Based Model Predictive Control of Wheeled Mobile Robot,” MODARES MECHANICAL ENGINEERING, vol. 19, no. 7 , pp. 1767–1777, 2019, [Online]. Available: https://sid.ir/paper/178000/en

Related Journal Papers