scholarly journals Adaptive Predictive Control with Neuro-Fuzzy Parameter Estimation for Microgrid Grid-Forming Converters

2021 ◽  
Vol 13 (13) ◽  
pp. 7038
Author(s):  
Oluleke Babayomi ◽  
Zhenbin Zhang ◽  
Yu Li ◽  
Ralph Kennel
Keyword(s):  
Parameter Estimation ◽  
Predictive Control ◽  
Dynamic Performance ◽  
Harmonic Distortion ◽  
State Parameter ◽  
Operating Conditions ◽  
Control Technique ◽  
Estimation Accuracy ◽  
Filter Parameter ◽  
Neuro Fuzzy

Model predictive control (MPC) is a flexible and multivariable control technique with better dynamic performance than linear control. However, MPC is sensitive to parametric mismatches that reduce its control capabilities. In this paper, we present a new method of improving the robustness of MPC to filter parameter variations/mismatches by easily implementable parameter estimation. Furthermore, we extend the proposed technique for wider operating conditions by novel neuro-fuzzy estimation. The results, which are demonstrated by both simulations and real-time hardware-in-the-loop tests, show a steady-state parameter estimation accuracy of 95%, and at least 20% improvement in total harmonic distortion (THD) than conventional non-adaptive MPC under parameter mismatches up to 50% of the nominal values.

scholarly journals Simplified Sensorless Current Predictive Control of Synchronous Reluctance Motor Using Online Parameter Estimation

Energies ◽  
2020 ◽  
Vol 13 (2) ◽  
pp. 492 ◽  
Author(s):  
Ahmed Farhan ◽  
Mohamed Abdelrahem ◽  
Amr Saleh ◽  
Adel Shaltout ◽  
Ralph Kennel
Keyword(s):  
Parameter Estimation ◽  
Predictive Control ◽  
Operating Conditions ◽  
Parameter Mismatch ◽  
Speed Controller ◽  
Synchronous Reluctance Motor ◽  
Reluctance Motor ◽  
Finite Set ◽  
Insufficient Response ◽  
The Cost

In this paper, a simplified efficient method for sensorless finite set current predictive control (FSCPC) for synchronous reluctance motor (SynRM) based on extended Kalman filter (EKF) is proposed. The proposed FSCPC is based on reducing the computation burden of the conventional FSCPC by using the commanded reference currents to directly calculate the reference voltage vector (RVV). Therefore, the cost function is calculated for only three times and the necessity to test all possible voltage vectors will be avoided. For sensorless control, EKF is composed to estimate the position and speed of the rotor. Whereas the performance of the proposed FSCPC essentially necessitates the full knowledge of SynRM parameters and provides an insufficient response under the parameter mismatch between the controller and the motor, online parameter estimation based on EKF is combined in the proposed control strategy to estimate all parameters of the machine. Furthermore, for simplicity, the parameters of PI speed controller and initial values of EKF covariance matrices are tuned offline using Particle Swarm Optimization (PSO). To demonstrate the feasibility of the proposed control, it is implemented in MATLAB/Simulink and tested under different operating conditions. Simulation results show high robustness and reliability of the proposed drive.

Recurrent ANFIS-Coordinated Controller Design for Multimachine Power System with FACTS Devices

2016 ◽  
Vol 26 (02) ◽  
pp. 1750034 ◽  
Author(s):  
J. Sangeetha ◽  
P. Renuga
Keyword(s):  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Controller Design ◽  
Test System ◽  
Operating Conditions ◽  
Superior Performance ◽  
Control Technique ◽  
Inference System ◽  
Neuro Fuzzy ◽  
Oscillation Damping

This paper proposes the design of auxiliary-coordinated controller for static VAR compensator (SVC) and thyristor-controlled series capacitor (TCSC) devices by adaptive fuzzy optimized technique for oscillation damping in multimachine power systems. The performance of the coordinated control of SVC and TCSC devices based on feedforward adaptive neuro fuzzy inference system (F-ANFIS) is compared with that of the adaptive neuro fuzzy inference system (ANFIS) structure based on recurrent adaptive neuro fuzzy inference system (R-ANFIS) network architecture. The objective of the coordinated controller design is to tune the parameters of SVC and TCSC fuzzy lead lag compensator simultaneously to minimize the deviation of rotor angle and rotor speed of the generators. The performance of the system is enhanced by optimally tuning the membership functions of fuzzy lead lag controller parameter of the flexible AC transmission system (FACTS) by R-ANFIS controller. The training data for F-ANFIS and R-ANFIS are generated by conventional linear control technique under various operating conditions. The offline trained controller tunes the parameter of lead lag controller in online. The oscillation damping ability of the system is analyzed for three-machine test system by calculating the standard deviation and cost function. The superior performance of R-ANFIS controller is compared with various particle swarm optimization-based feedforward ANFIS controllers available in literature.

An improved predictive control for parallel grid-connected doubly fed induction generator-based wind systems under unbalanced grid conditions

2019 ◽  
Vol 43 (4) ◽  
pp. 377-391
Author(s):  
Meriem Ghodbane-Cherif ◽  
Sondes Skander-Mustapha ◽  
Ilhem Slama-Belkhodja
Keyword(s):  
Predictive Control ◽  
Operating Conditions ◽  
Control Technique ◽  
Induction Generator ◽  
Doubly Fed Induction Generator ◽  
Wind System ◽  
Deadbeat Control ◽  
Doubly Fed ◽  
The Impact ◽  
Unbalanced Grid

Recently, the massive integration of renewable energy sources, especially wind and solar ones, has attracted researchers to new issues such as power quality. In this context, this article deals with an improved deadbeat predictive control for parallel grid-connected doubly fed induction generator-based wind systems under unbalanced grid conditions. The impact of an asymmetrical voltage sag has been treated for a doubly fed induction generator- wind system with emphasis on the occurrence of the negative current. In the case of a micro-grid based on wind systems, the effect of this current increases with the line impedance and thereby the system location. An improved predictive deadbeat control technique is proposed for the rotor side converter to enhance the behaviour of the wind system. A dynamic modelling of the doubly fed induction generator in both positive and negative reference frames has been proposed to focus on the behaviour of the system for these various operating conditions. Results of different simulation scenarios prove the effectiveness of the proposed improved predictive deadbeat control.

scholarly journals Brayton-Moser Passivity Based Controller for Electric Vehicle Battery Charger

2021 ◽  
Vol 6 (1) ◽  
pp. 40-51
Author(s):  
Kumari Shipra ◽  
Keyword(s):  
Electric Vehicle ◽  
Power Quality ◽  
Dynamic Performance ◽  
Pi Controller ◽  
Operating Conditions ◽  
Control Technique ◽  
Prototype Model ◽  
Battery Charger ◽  
Source Current ◽  
Energy Balance Approach

In this paper Brayton-Moser passivity-based control (BM-PBC) methodology is developed for an on-board battery charger for plug-in electric vehicles(PHEVs). The main features of this electric vehicle (EV) charger include improved power quality, reduced filter size and voltage stress across the switches and fast dynamic response. In this paper, a dynamic model of the three-level (TL) boost power factor correction (PFC) converter is developed using the Brayton-Moser formulation. Then, the Brayton-Moser based control technique is designed by injecting a virtual resistor in series with the input inductor. Further, the stability analysis of the proposed controller is also carried out using energy balance approach. To improve the dynamic performance and reduce the steady state error, a PI controller is integrated with the aforesaid controller. Therefore, the controller comprises of BM-PBC and the PI controller is implemented for the TL boost PFC converter as a battery charger and its performances are investigated under various operating modes with the help of MATLAB/Simulink. Furthermore, power quality of charger is assessed by monitoring source current total harmonic distortion (THD) under different operating conditions. It is also observed that the proposed system provides THD less than 5% in source current which satisfies IEC 61000-3-2 Class C standard. The performance of the aforesaid controller is also compared with the conventional PI controller. In order to validate the proposed controller, a prototype model of same specifications is tested in hardware in loop and obtained test results are also presented.

Sensor placement and moving horizon state/parameter estimation for flexible hypersonic vehicles

2019 ◽  
Vol 233 (13) ◽  
pp. 4765-4778
Author(s):  
Erkang Chen ◽  
Wuxing Jing ◽  
Changsheng Gao
Keyword(s):  
Parameter Estimation ◽  
Sensor Placement ◽  
State Parameter ◽  
Qr Decomposition ◽  
Joint Estimation ◽  
Estimation Accuracy ◽  
Hypersonic Vehicles ◽  
Moving Horizon Estimation ◽  
Qr Algorithm ◽  
Update Strategy

Considering the nonlinearity, uncertainty, and rigid/elastic coupling, a state/parameter joint estimation method is essential for control system design or fault diagnosis of flexible hypersonic vehicles. With the goal of improving state/parameter estimation accuracy, this paper proposes a sensor placement strategy and a moving horizon estimation algorithm with a QR-decomposition-based arrival cost update strategy (MHE-QR). To enhance observability, a novel double sensor placement strategy, in which the sensor positions are obtained via solving a constrained nonlinear optimization problem, is developed. The MHE-QR algorithm transforms the arrival cost update problem into a least square problem and solves it utilizing QR decomposition. With this QR-decomposition-based arrival update strategy, the state/parameter estimation problem is solved as a nonlinear programming problem in the framework of moving horizon estimation. Finally, the performance of sensor placement strategy and MHE-QR is evaluated by Monte Carlo simulations in 10 different scenarios. Simulation results demonstrate that the sensor placement strategy and MHE-QR algorithm can effectively improve the estimation accuracy, convergence speed and computation rate. Additionally, the CPU time of MHE-QR validates its real-time applicability.

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

Power Test System Development and Dynamic Performance State Estimation Based on Hub Motor Vehicle

2020 ◽  
Vol 13 (2) ◽  
pp. 126-140
Author(s):  
Jing Gan ◽  
Xiaobin Fan ◽  
Zeng Song ◽  
Mingyue Zhang ◽  
Bin Zhao
Keyword(s):  
Real Time ◽  
Dynamic Performance ◽  
Test System ◽  
Operating Conditions ◽  
Motor Vehicles ◽  
Maximum Speed ◽  
Performance Parameters ◽  
Power Performance ◽  
Power Test ◽  
The Real

Background: The power performance of an electric vehicle is the basic parameter. Traditional test equipment, such as the expensive chassis dynamometer, not only increases the cost of testing but also makes it impossible to measure all the performance parameters of an electric vehicle. Objective: A set of convenient, efficient and sensitive power measurement system for electric vehicles is developed to obtain the real-time power changes of hub-motor vehicles under various operating conditions, and the dynamic performance parameters of hub-motor vehicles are obtained through the system. Methods: Firstly, a set of on-board power test system is developed by using virtual instrument (Lab- VIEW). This test system can obtain the power changes of hub-motor vehicles under various operating conditions in real-time and save data in real-time. Then, the driving resistance of hub-motor vehicles is analyzed, and the power performance of hub-motor vehicles is studied in depth. The power testing system is proposed to test the input power of both ends of the driving motor, and the chassis dynamometer is combined to test so that the output efficiency of the driving motor can be easily obtained without disassembly. Finally, this method is used to carry out the road test and obtain the vehicle dynamic performance parameters. Results: The real-time current, voltage and power, maximum power, acceleration time and maximum speed of the vehicle can be obtained accurately by using the power test system in the real road experiment. Conclusion: The maximum power required by the two motors reaches about 9KW, and it takes about 20 seconds to reach the maximum speed. The total power required to maintain the maximum speed is about 7.8kw, and the maximum speed is 62km/h. In this article, various patents have been discussed.

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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