مشروع البحث: ROBUST IMPLEMENTATION OF THE MODEL PREDICTIVE CONTROL FOR DCDC POWER CONVERTERS AND INDUSTRIAL CONTROL APPLICATIONS
| dc.contributor.advisor | Dr. Mohamed Zohdy | |
| dc.date.accessioned | 2026-06-14T10:11:42Z | |
| dc.date.available | 2026-06-14T10:11:42Z | |
| dc.description | Model Predictive Control (MPC) is an optimal control technique that uses the optimization at each sampling time 𝑇𝑠 over a predicted decision interval 𝑁𝑝 to calculate the system's future optimal solution. MPC was first funded in the late 70s by Richalet et al., then get developed by Cutler and Ramaker for the oil and chemical process industries [4]. However, many applications currently use MPC to control their functionalities. | |
| dc.description.abstract | The base requirements of the control systems are concerned with the system’s stability, dynamic behaviors, and robustness of the closed-loop system. Many control schemes have been extensively studied to work for the power converters and the industrial applications, such as the hysteresis control and linear control with the pulse width modulation [1]. In addition to the aforementioned control schemes, there are more efficient control systems such as Sliding Mode Control, Fuzzy Logic Control, and Model Predictive Control (MPC) systems. Although they are computationally complex, they can be implemented using the developed powerful microprocessors or field Programmable Gate Arrays (FPGA). | |
| dc.identifier | 1339 | |
| dc.identifier.uri | https://dspace.academy.edu.ly/handle/123456789/2309 | |
| dc.subject | ONTROL FOR DCDC POWER CONVERTERS | |
| dc.title | ROBUST IMPLEMENTATION OF THE MODEL PREDICTIVE CONTROL FOR DCDC POWER CONVERTERS AND INDUSTRIAL CONTROL APPLICATIONS | |
| dspace.entity.type | Project | |
| project.endDate | 2022 | |
| project.funder.name | هندسة كهربائية | |
| project.investigator | محمد امحمد محمد البيرة | |
| project.startDate | 2021 |