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| Title: | Model predictive DC voltage control for all-electric ships | | | Authors: | A. Haseltalab, M. Ayala Botto, R.R. Negenborn |
| | Journal: | Control Engineering Practice | | |
| | Abstract: | It is believed that with the advent of on-board Direct Current (DC) power and propulsion systems, the transmission and delivery of energy on board of ships can be carried out more efficiently as it is being done using conventional direct diesel or Alternative Current (AC) power and propulsion systems. However, the stability of DC voltage on-board of all-electric ships with a DC power and propulsion architecture is a critical issue that has drawn attention over the last few years. In this paper, a novel Model Predictive Control (MPC) approach is proposed for the diesel-generator shaft speed control and DC voltage regulation on-board of all-electric ships. While in the literature most of the proposed solutions for stabilization of DC power systems turn around the adoption of active rectification with different control strategies, in this paper, the focus is on uncontrolled rectification at the voltage conversion stage. In this research, the prime mover is a Diesel-Generator-Rectifier (DGR) set which feeds propulsive asynchronous motors through a DC-link. First, a dynamical model is developed for the DGR set and the DC-link, and the overall system is represented in state space format. Then, the MPC-based approach is presented. Input-Output Feedback Linearization (IOFL) as well as an approach for linearizing the constraints are adopted to enable the use of quadratic programming schemes for solving the MPC's optimization problem. To increase the robustness of the MPC approach, a tube-based technique is also utilized. Different analyses are carried out to show that the proposed control strategy is capable of handling sudden changes in load conditions as well as adverse effects of Constant Power Loads (CPL). |
| | Reference: | Model predictive DC voltage control for all-electric ships. A. Haseltalab, M. Ayala Botto, R.R. Negenborn. Control Engineering Practice, vol. 90, pp. 133-147, September 2019. | | | Request: | A
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