scholarly journals A Multilevel Inverter Bridge Control Structure with Energy Storage Using Model Predictive Control for Flat Systems

2013 ◽  
Vol 2013 ◽  
pp. 1-15 ◽  
Author(s):  
Paolo Mercorelli
Keyword(s):  
Energy Storage ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Control Structure ◽  
Control Technique ◽  
Switching Frequency ◽  
Optimal Current ◽  
Electromagnetic Linear Actuator ◽  
New Generation ◽  
Hysteresis Control

The paper presents a novel technique to control the current of an electromagnetic linear actuator fed by a multilevel IGBT voltage inverter with dynamic energy storage. The technique uses a “cascade model predictive control (MPC),” which consists of two MPCs. A predictive control of the trajectory position predicts the optimal current, which is considered to be the desired current for the second MPC controller in which a hysteresis control technique is also integrated. Energy is stored in a capacitor using energy recovery. The current MPC can handle a capacitor voltage higher than the source voltage to guarantee high dynamic current and disturbance compensation. The main contribution of this paper is the design of an optimal control structure that guarantees a capacitor recharge. In this context, the approach is quite new and can represent a general emerging approach allowing to reduce the complexity of the new generation of inverters and, in the meantime, to guarantee precision and acceptable switching frequency. The proposed technique shows very promising results through simulations with real actuator data in an innovative transportation technology.

scholarly journals Design and Development of Experimental Based Phase Modulated Model Predictive Control for Torque Ripple Reduction of MMC Fed BLDC Motor

2021 ◽  
Author(s):  
Rahul Jaiswal ◽  
◽  
Anshul Agarwal ◽  
Richa Negi ◽  
Abhishek Vikram ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Control Method ◽  
Torque Ripple ◽  
Current Control ◽  
Experimental Result ◽  
Control Technique ◽  
Switching Frequency ◽  
Bldc Motor ◽  
Brushless Dc

This article represents the torque ripple performance of modular multilevel converter (MMC) fed brushless dc (BLDC) motor using different current control technique. For reducing the ripple current in BLDC motor, a phase-modulated model predictive control (PMMPC) technique has been proposed. The stator ripple current is almost negligible using PMMPC. This PMMPC current control method is a significant minimization of torque ripple in BLDC motor. A comparative torque ripple behaviour of MMC fed BLDC motor has been done using phase-modulated model predictive control, model predictive control (MPC) and proportional integral (PI) control at different switching frequency. It has been observed that a PMMPC current control technique is more efficient as compared to the MPC as well as PI current control technique. It has also been observed that the torque ripple performance is improved while using PMMPC as compared to the MPC and PI controller. Simulation results have been verified with the help of experimental result and these results are obtained in good agreement to the simulated results.

scholarly journals A novel predictive control strategy for neutral-point clamped converter with harmonic spectrum shaping

2021 ◽  
Author(s):  
Jaksa Rubinic
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Control Strategy ◽  
Sampling Frequency ◽  
Harmonic Spectrum ◽  
Neutral Point ◽  
Control Technique ◽  
Switching Frequency ◽  
Finite Control ◽  
Control Set

This thesis proposes a new predictive control strategy to achieve fixed-switching frequency operation for a neutral-point clamped (NPC) inverter. The classical fixed-sampling frequency finite control-set model predictive control (FSF-FCS-MPC) operates with variable switching frequency, and thus produces spread-spectrum in an output current. The classical method also suffers from high computational complexity as the number of converter voltage levels increases. To overcome these issues, a high performance variable sampling frequency finite control-set model predictive control (VSF-FCS-MPC) strategy is proposed to control the power converters. The proposed control technique combines the advantages of space vector modulation (SVM) with a newly introduced mechanics to determine the appropriate sampling frequency. With these features the major requirements such as balancing of DC-link capacitor voltages, switching frequency minimization and common-mode voltage mitigation have been achieved with simultaneous elimination of even-order and inter-harmonics in the load current harmonic spectrum. The VSF-FCS-MPC strategy for current control with decoupled active/reactive power regulation of grid-connected multilevel converter was also analyzed. Moreover, a novel DC-link voltage balancing technique is presented which eliminates the need for balancing the capacitor voltages through cost function, and thus alleviates the weighting factor design. An introduction of SVM highly reduces the calculation time by considering only adjacent vectors, rendering FCS-MPC more suitable for implementation with multi-level converters with a number of voltage levels higher than three. Finally, the proposed control technique has been validated through simulation and experimental verification and a detailed comparison of VSF-FCS-MPC with FSF-FCS-MPC and SVM is presented

scholarly journals A novel predictive control strategy for neutral-point clamped converter with harmonic spectrum shaping

2021 ◽  
Author(s):  
Jaksa Rubinic
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Control Strategy ◽  
Sampling Frequency ◽  
Harmonic Spectrum ◽  
Neutral Point ◽  
Control Technique ◽  
Switching Frequency ◽  
Finite Control ◽  
Control Set

This thesis proposes a new predictive control strategy to achieve fixed-switching frequency operation for a neutral-point clamped (NPC) inverter. The classical fixed-sampling frequency finite control-set model predictive control (FSF-FCS-MPC) operates with variable switching frequency, and thus produces spread-spectrum in an output current. The classical method also suffers from high computational complexity as the number of converter voltage levels increases. To overcome these issues, a high performance variable sampling frequency finite control-set model predictive control (VSF-FCS-MPC) strategy is proposed to control the power converters. The proposed control technique combines the advantages of space vector modulation (SVM) with a newly introduced mechanics to determine the appropriate sampling frequency. With these features the major requirements such as balancing of DC-link capacitor voltages, switching frequency minimization and common-mode voltage mitigation have been achieved with simultaneous elimination of even-order and inter-harmonics in the load current harmonic spectrum. The VSF-FCS-MPC strategy for current control with decoupled active/reactive power regulation of grid-connected multilevel converter was also analyzed. Moreover, a novel DC-link voltage balancing technique is presented which eliminates the need for balancing the capacitor voltages through cost function, and thus alleviates the weighting factor design. An introduction of SVM highly reduces the calculation time by considering only adjacent vectors, rendering FCS-MPC more suitable for implementation with multi-level converters with a number of voltage levels higher than three. Finally, the proposed control technique has been validated through simulation and experimental verification and a detailed comparison of VSF-FCS-MPC with FSF-FCS-MPC and SVM is presented

scholarly journals Model Predictive Control Method of hybrid Battery energy storage system for Smoothing Wind Power Fluctuation

2020 ◽  
Vol 194 ◽  
pp. 02003
Author(s):  
Li Jianlin ◽  
Tan Yuliang
Keyword(s):  
Energy Storage ◽  
Model Predictive Control ◽  
Wind Power ◽  
Predictive Control ◽  
Wind Farm ◽  
Control Method ◽  
Switching Frequency ◽  
Power Fluctuation ◽  
Hybrid Energy ◽  
Hybrid Energy Storage

In a large-scale wind power generation system, active power fluctuation caused by random wind speed will have a serious impact on the power grid. In order to limit the power fluctuation that wind farm transmits to the power grid and protect the energy storage battery, this paper has proposed a model predictive control method of hybrid energy storage by optimizing the objective function and constraint conditions. Firstly, the mathematical model of predictive control method has been established in a wind power system with hybrid energy storage. Then, with the goal of minimum energy storage output and maximum charging-discharging capacity of the super-capacitor, the predictive control process has been optimized. Meanwhile, the constraint on the output power of the battery has been dynamically changed to reduce its charging-discharging switching frequency, and the model predictive control strategy of the hybrid energy storage has been formed. Finally, compared with the model prediction control method of single energy storage, based on a wind farm data, the simulation results show that the proposed method can smooth wind power fluctuation, reduce the time that the power does not satisfy the fluctuation requirements, ensure the capability of the super-capacitor, and reduce the charging-discharging switching frequency of the energy storage battery.

Wide-area Power System Oscillation Damping using Model Predictive Control Technique

2011 ◽  
Vol 131 (7) ◽  
pp. 536-541 ◽  
Author(s):  
Tarek Hassan Mohamed ◽  
Abdel-Moamen Mohammed Abdel-Rahim ◽  
Ahmed Abd-Eltawwab Hassan ◽  
Takashi Hiyama
Keyword(s):  
Model Predictive Control ◽  
Power System ◽  
Predictive Control ◽  
Wide Area ◽  
Control Technique ◽  
Oscillation Damping

scholarly journals Passive Model Predictive Control on a Two-Body Self-Referenced Point Absorber Wave Energy Converter

Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1731
Author(s):  
Dan Montoya ◽  
Elisabetta Tedeschi ◽  
Luca Castellini ◽  
Tiago Martins
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Wave Energy ◽  
Power Flow ◽  
Linear Constraints ◽  
Wave Energy Converter ◽  
Control Technique ◽  
Computational Time ◽  
Energy Converter ◽  
Point Absorber

Wave energy is nowadays one of the most promising renewable energy sources; however, wave energy technology has not reached the fully-commercial stage, yet. One key aspect to achieve this goal is to identify an effective control strategy for each selected Wave Energy Converter (WEC), in order to extract the maximum energy from the waves, while respecting the physical constraints of the device. Model Predictive Control (MPC) can inherently satisfy these requirements. Generally, MPC is formulated as a quadratic programming problem with linear constraints (e.g., on position, speed and Power Take-Off (PTO) force). Since, in the most general case, this control technique requires bidirectional power flow between the PTO system and the grid, it has similar characteristics as reactive control. This means that, under some operating conditions, the energy losses may be equivalent, or even larger, than the energy yielded. As many WECs are designed to only allow unidirectional power flow, it is necessary to set nonlinear constraints. This makes the optimization problem significantly more expensive in terms of computational time. This work proposes two MPC control strategies applied to a two-body point absorber that address this issue from two different perspectives: (a) adapting the MPC formulation to passive loading strategy; and (b) adapting linear constraints in the MPC in order to only allow an unidirectional power flow. The results show that the two alternative proposals have similar performance in terms of computational time compared to the regular MPC and obtain considerably more power than the linear passive control, thus proving to be a good option for unidirectional PTO systems.

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