An Improved Sequential Model Predictive Control Strategy for T-Type Three-Level Inverter System
Tian Yazhuo1, Liu Chenwei1, Zhang Yongjun1,2, Xiao Xiong1,2
1. National Engineering Research Center for Advanced Rolling and Intelligent Manufacturing University of Science and Technology Beijing Beijing 100083 China; 2. Institute of Engineering Technology University of Science and Technology Beijing Beijing 100083 China
Abstract The T-type three-level inverter is known for its good output waveform, high efficiency, and ability to provide high voltage and power outputs, which can meet the requirements of control strategies. One common strategy of T-type three-level inverter systems is predictive direct torque control. The unified cost function can directly describe the constraint conditions of multiple control objectives and select the optimal space voltage vector for the next control cycle acting on the inverter through traversal. The approach offers good control performance and simple control strategies. However, when dealing with multiple control objectives, appropriate weighting factors must be designed to adjust the contribution of each objective. The design of weighting factors has become a research hotspot. Sequential model predictive control adopts a sequential structure to evaluate the cost function of each control objective, avoiding the weighting factor design. However, the control performance for low-priority objectives is limited and cannot meet the equal weight control requirements of similar priority objectives. Therefore, this paper proposes an improved sequential model predictive control based on a sequential-parallel hybrid structure for coordinate control of multiple objectives. Firstly, this paper proposes an enhanced multi-objective cost function of a T-type three-level inverter system based on model predictive direct torque control. The cost function includes electromagnetic torque, stator flux, common-mode voltage, and switching frequency. Secondly, the priorities of each control objective are considered. The electromagnetic torque and stator flux, which have similar priorities, are classified as the primary set. The common-mode voltage and switching frequency, which optimize system performance, are classified as the secondary set. Herein, the primary set takes priority over the secondary set, and the control objectives within the same set have similar priorities. A proposed sequential-parallel hybrid structure improves the sequential model predictive control. The parallel synchronously optimizes objectives with similar priorities, and the sequential structure sequentially controls objectives with different priorities. Thus, multi-objective predictive control of the system is achieved while maintaining the weighting factor design, improving system performance. An experimental platform is built using a high-speed DSP (TMS320F28335) and FPGA as core components. The experimental results show that the proposed strategy can effectively suppress the common-mode voltage and reduce the switching frequency, thus reducing system power loss. Meanwhile, the system’s high-performance steady-state and dynamic responses are maintained. The computational burden is moderate and can meet the real-time requirements. The proposed strategy has the advantages of simple structure and easy implementation.
Tian Yazhuo,Liu Chenwei,Zhang Yongjun等. An Improved Sequential Model Predictive Control Strategy for T-Type Three-Level Inverter System[J]. Transactions of China Electrotechnical Society, 2024, 39(24): 7821-7832.
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2024, Vol. 39 
