scholarly journals A Modified Model Predictive Power Control for Grid-Connected T-Type Inverter with Reduced Computational Complexity

Electronics ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 217 ◽  
Author(s):  
Van-Quang-Binh Ngo ◽  
Minh-Khai Nguyen ◽  
Tan-Tai Tran ◽  
Joon-Ho Choi ◽  
Young-Cheol Lim
Keyword(s):  
Model Predictive Control ◽  
Power Control ◽  
Predictive Control ◽  
High Performance ◽  
Harmonic Distortion ◽  
Absolute Error ◽  
Switching Frequency ◽  
Voltage Reference ◽  
Grid Current ◽  
Control Objective

This study proposed a modified power strategy based on model predictive control for a grid-connected three-level T-type inverter. The controller utilizes the mathematical model to forecast the performance of the grid current, the balance of DC-bus capacitor voltages and switching frequency. The proposed method outlines a new technique to formulate a control objective. The control objective includes the absolute error of the inverter voltage reference and its possible values instead of the grid current error. By using the modified equivalent transformations in the cost function, the execution time was reduced 22% compared to the traditional model predictive control while maintaining the high dynamic performances of the power and low total harmonic distortion of the current. A comparative investigation showed that the proposed method obtains a high-performance control compared with the classical power control scheme with linear PI controllers and space vector modulation. The feasibility of the proposed method was verified by the simulation and experimental results.

scholarly journals High-power modular multilevel converters: Modeling, modulation and control

2021 ◽  
Author(s):  
Apparao Dekka
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Harmonic Distortion ◽  
Switching Frequency ◽  
Multilevel Converters ◽  
Direct Model ◽  
Modular Multilevel Converters ◽  
Dual Stage ◽  
And Control ◽  
Circulating Currents

THIS dissertation addresses the technical challenges associated with the operation and control of high-power modular multilevel converters. To improve the performance of modular multilevel converter (MMC), a generalized three-phase mathematical model with common-mode voltage (CMV) is proposed. By using the proposed mathematical model, the magnitude of circulating currents, capacitors voltage ripple, and the ripple in DC-link current during balanced and unbalanced operating conditions can be minimized. The modulation scheme and switching frequency are directly affected the output power quality and the performance of the converter and control method. In this dissertation, a novel sampled average and space vector modulation scheme is proposed. These modulation schemes are suitable to control the MMC with any number of submodules (without modifications), operates at low switching frequency, minimizes the ripple in output current and voltage harmonic distortion, and reduces the output filter size. For reliable operation of MMC, the voltage balancing among submodules is mandatory. This dissertation proposes a generalized single-stage balancing approach with reduced current sensors to control the MMC. The proposed balancing approach is suitable to implement with both phase-shifted and level-shifted pulse width modulation schemes. With the proposed approach, it is also possible to control the MMC with half-bridge and three level flying capacitor submodules. Also, an improved balancing approach often referred as the dual-stage balancing approach is proposed to minimize the voltage harmonic distortion and device power losses. This dissertation also proposes a direct model predictive control (D-MPC) approach to minimize the ripple in submodule capacitors voltage. To implement D-MPC approach, a discrete-time model of MMC with CMV is proposed. With the use of proposed model, the D-MPC approach does not require a cost function to minimize the circulating currents. The computational complexity is one of the major issues in the implementation of D-MPC approach for MMC. In this dissertation, a novel reduced computational MPC approaches named as dual-stage D-MPC and indirect model predictive control (I-MPC) approach are proposed. These approaches significantly minimize the computational complexity and, improve the voltage and current waveform quality while operating at the low switching frequency. Finally, the simulation and experimental studies are presented to validate the dynamic and steady-state performance of proposed methodologies. Index Terms • Modular Multilevel Converters. • Capacitors Voltage Balancing. • Pulse Width Modulation Schemes. • Circulating Currents. • Capacitors Voltage Ripple • Direct Model Predictive Control. • Dual-Stage Direct Model Predictive Control. • Indirect Model Predictive Control. • Total Harmonic Distortion.

scholarly journals Position Control of Pneumatic Actuators Using Three-Mode Discrete-Valued Model Predictive Control

Actuators ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 56 ◽  
Author(s):  
Haitao Qi ◽  
Gary M. Bone ◽  
Yile Zhang
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Pulse Width Modulation ◽  
Performance Metrics ◽  
Position Control ◽  
Sliding Mode ◽  
Absolute Error ◽  
Switching Frequency ◽  
Pneumatic Actuators ◽  
Clear Winner

A novel discrete-valued model-predictive control (DVMPC) algorithm termed DVMPC2 for the position control of pneumatic actuators using inexpensive on/off valves is presented. DVMPC2 includes a more flexible cost function, an improved prediction strategy, and other improvements. The actuator is a double-acting cylinder with two on/off solenoid poppet valves connected to each chamber. To reduce the switching frequency and prolong the valve life, DVMPC2 directly switches the valves when necessary, instead of using relatively high-frequency pulse-width modulation. Experimental comparisons are made with the state-of-the-art sliding-mode control (SMC) algorithm and the previous DVMPC algorithm. The comparisons are based on the five performance metrics: integral of time-weighted absolute error (ITAE), root mean square error (RMSE), overshoot (OS), steady-state error (SSE), and valve switches per second (SPS). The robustness is evaluated by increasing and decreasing the total mass of the moving components while keeping the controller parameters constant. The experimental results show that the proposed algorithm is superior to the previous DVMPC and outperformed SMC by a wide margin. Specifically, DVMPC2 reduced ITAE by 80%, RMSE by 52%, OS by 43%, and SPS by 20% relative to SMC. There was no clear winner in terms of SSE.

scholarly journals High-power modular multilevel converters: Modeling, modulation and control

2021 ◽  
Author(s):  
Apparao Dekka
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Harmonic Distortion ◽  
Switching Frequency ◽  
Multilevel Converters ◽  
Direct Model ◽  
Modular Multilevel Converters ◽  
Dual Stage ◽  
And Control ◽  
Circulating Currents

THIS dissertation addresses the technical challenges associated with the operation and control of high-power modular multilevel converters. To improve the performance of modular multilevel converter (MMC), a generalized three-phase mathematical model with common-mode voltage (CMV) is proposed. By using the proposed mathematical model, the magnitude of circulating currents, capacitors voltage ripple, and the ripple in DC-link current during balanced and unbalanced operating conditions can be minimized. The modulation scheme and switching frequency are directly affected the output power quality and the performance of the converter and control method. In this dissertation, a novel sampled average and space vector modulation scheme is proposed. These modulation schemes are suitable to control the MMC with any number of submodules (without modifications), operates at low switching frequency, minimizes the ripple in output current and voltage harmonic distortion, and reduces the output filter size. For reliable operation of MMC, the voltage balancing among submodules is mandatory. This dissertation proposes a generalized single-stage balancing approach with reduced current sensors to control the MMC. The proposed balancing approach is suitable to implement with both phase-shifted and level-shifted pulse width modulation schemes. With the proposed approach, it is also possible to control the MMC with half-bridge and three level flying capacitor submodules. Also, an improved balancing approach often referred as the dual-stage balancing approach is proposed to minimize the voltage harmonic distortion and device power losses. This dissertation also proposes a direct model predictive control (D-MPC) approach to minimize the ripple in submodule capacitors voltage. To implement D-MPC approach, a discrete-time model of MMC with CMV is proposed. With the use of proposed model, the D-MPC approach does not require a cost function to minimize the circulating currents. The computational complexity is one of the major issues in the implementation of D-MPC approach for MMC. In this dissertation, a novel reduced computational MPC approaches named as dual-stage D-MPC and indirect model predictive control (I-MPC) approach are proposed. These approaches significantly minimize the computational complexity and, improve the voltage and current waveform quality while operating at the low switching frequency. Finally, the simulation and experimental studies are presented to validate the dynamic and steady-state performance of proposed methodologies. Index Terms • Modular Multilevel Converters. • Capacitors Voltage Balancing. • Pulse Width Modulation Schemes. • Circulating Currents. • Capacitors Voltage Ripple • Direct Model Predictive Control. • Dual-Stage Direct Model Predictive Control. • Indirect Model Predictive Control. • Total Harmonic Distortion.

scholarly journals Model predictive control for autonomous ground vehicles: a review

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Shuyou Yu ◽  
Matthias Hirche ◽  
Yanjun Huang ◽  
Hong Chen ◽  
Frank Allgöwer
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
High Performance ◽  
Control Method ◽  
Theoretical Background ◽  
Future Research ◽  
Centralized Control ◽  
Ground Vehicles ◽  
Uncertain Environments ◽  
Autonomous Ground Vehicles

AbstractThis paper reviews model predictive control (MPC) and its wide applications to both single and multiple autonomous ground vehicles (AGVs). On one hand, MPC is a well-established optimal control method, which uses the predicted future information to optimize the control actions while explicitly considering constraints. On the other hand, AGVs are able to make forecasts and adapt their decisions in uncertain environments. Therefore, because of the nature of MPC and the requirements of AGVs, it is intuitive to apply MPC algorithms to AGVs. AGVs are interesting not only for considering them alone, which requires centralized control approaches, but also as groups of AGVs that interact and communicate with each other and have their own controller onboard. This calls for distributed control solutions. First, a short introduction into the basic theoretical background of centralized and distributed MPC is given. Then, it comprehensively reviews MPC applications for both single and multiple AGVs. Finally, the paper highlights existing issues and future research directions, which will promote the development of MPC schemes with high performance in AGVs.

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