Abdelbaky, M. A., X. Kong, X. Liu, and K. Y. Lee, "Optimal IOFL-based economic model predictive control technique for boiler-turbine system", ISA Transactions, vol. 153, pp. 143-154, 2024. AbstractWebsite

The optimal control design of the boiler-turbine system is vital to ensure feasibility and high responsiveness over desired load variations. Using the traditional linear control techniques realization of this task is difficult, as the boiler-turbine mechanism has strong nonlinearities. Besides, environmental and economic concerns have replaced existing tracking control ones as the primary concerns of advanced power plants. Thus, this study proposes an optimal economic model predictive controller (EMPC) scheme for this unit on the basis of the input/output feedback linearization (IOFL) method. By employing the IOFL method, this unit is decoupled into a new linearized model that is utilized for developing the suggested optimal IOFL EMPC technique. The proposed control scheme is formulated in an economic quadratic programming form that considers the input-rate and input limits of the unit for optimal economic performance. In addition, an adaptive iterative algorithm is utilized for constraints mapping with guaranteeing a feasible solution in a finite number of steps without violation of original constraints over the entire predictive horizon. The outcomes of the simulation show that the suggested optimal IOFL EMPC scheme offers an improved dynamic and economic output performance over fuzzy hierarchical MPC, fuzzy EMPC, and nonlinear EMPC techniques during various load variations.

Abdelbaky, M. A., X. Liu, and X. Kong, "Stable constrained model predictive control based on IOFL technique for boiler-turbine system", Transactions of the Institute of Measurement and Control, vol. 47, issue 6, pp. 1104-1116, 2025. AbstractWebsite

Due to the strong nonlinearities of the boiler-turbine system, feasibility and high response capability are hard to realize using traditional linear controllers. Advanced controllers that can ensure stability and feasibility without violating system constraints, and enhance the system’s dynamic output performance, are needed. Therefore, this paper proposes a stable input/output feedback linearization (IOFL) model predictive controller (MPC) technique for the boiler-turbine system. This nonlinear system is decoupled using the IOFL method into a novel linearized model, which is then used for constituting the proposed stable IOFL MPC problem. The proposed scheme uses a constraint mapping method that converts actual input limits into limits on the basis of the control output variable to ensure a feasible solution over the whole prediction horizon. Moreover, a min-max MPC technique in the form of linear matrix inequality with the realization of the input rate-of-change constraints is utilized to ensure the boiler-turbine unit’s stability. The process model and proposed control scheme are executed using MATLAB and the simulation results demonstrate that the proposed controller has an enhanced dynamic output performance compared with an advanced control scheme under various load variations.

Kong, X., W. Wang, X. Liu, L. Ma, M. A. Abdelbaky, and K. Y. Lee, "Offshore wind turbines real-time control using convex nonlinear economic MPC scheme", Ocean Engineering, vol. 297, pp. 116988, 2024. AbstractWebsite

With the rapid advancement of wind power technology, the importance of lower operating costs and improved real-time control capabilities for offshore wind turbines (OWT) has increased. Nonlinear Economic Model Predictive Control (NEMPC) has gained attention due to its effective balancing of economic objectives. However, implementing real-time control for OWTs faces challenges due to their strong nonlinearity. This study proposes a convex NEMPC (CNEMPC) by incorporating variable transformation to account for the instantaneous energy stored in OWTs. The CNEMPC includes a set of convex constraints and aims to maximize power generation while minimizing fatigue loads on system components like the tower and gearbox. A newly designed moving horizon estimator provides an initial state estimation for the CNEMPC. Real-time iteration of the CNEMPC is achieved by leveraging the similarity of nonlinear programs between adjacent sampling moments. The effectiveness of the proposed control strategy is verified using a 5 MW OWT as the simulation target.

Ma, L., X. Kong, X. Liu, M. A. Abdelbaky, A. H. Besheer, M. Wang, and K. Y. Lee, "Offshore wind power generation system control using robust economic MPC scheme", Ocean Engineering, vol. 283, pp. 115178, 2023.
Abdelbaky, M. A., A. H. Besheer, S. Fathallah, H. M. Emara, A. R. Sayed, and S. A. Zaki, "Coordinated Distributed-Predictive Control for Standalone Microgrid with Less Computational Burden", 2023 24th International Middle East Power System Conference (MEPCON), Mansoura, Egypt, 20 December, 2023.
Kong, X., M. A. Abdelbaky, X. Liu, and K. Y. Lee, "Stable feedback linearization-based economic MPC scheme for thermal power plant", Energy, vol. 268, pp. 1-13, 2023.
Kong, X., L. Ma, C. Wang, S. Guo, M. A. Abdelbaky, X. Liu, and K. Y. Lee, "Large-scale wind farm control using distributed economic model predictive scheme", Renewable Energy, vol. 181, pp. 581-591, 2022.
Kong, X., X. A. Wang, M. A. Abdelbaky, X. Liu, and K. Y. Lee, "Nonlinear MPC for DFIG-based wind power generation under unbalanced grid conditions", International Journal of Electrical Power & Energy Systems, vol. 134, pp. 107416-107431, 2022.
Jan, M. U., A. Xin, S. Iqbal, M. A. Abdelbaky, H. U. Rehman, S. Tamara Egamnazrova, SAA Rizvi, M. Aurangzeb, and S. Salman, "Frequency Regulation of an Isolated Micro-Grid Integrated with Electric Vehicles using Adaptive and Fuzzy PI Controllers", The 16th IET International Conference on AC and DC Power Transmission (ACDC 2020), Online Conference, pp. 1-6, 2020.
Rehman, H. U., X. Yan, M. A. Abdelbaky, M. U. Jan, S. Iqbal, A. Masood, T. Egamnazrova, and M. Aurangzeb, "Droop Control Design Based on Advanced Particle Swarm Optimization for Grid-Connected Multi PV-VSG", The 16th IET International Conference on AC and DC Power Transmission (ACDC 2020), Online Conference, pp. 1-6, 2020.
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