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model predictive controller Based on Online Obtaining of Softness Factor and Fusion Velocity for Automatic Train Operation

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SENSORS 2020年第6期20卷 1719-1719页

作者： Wang, Longda Wang, Xingcheng Sheng, Zhao Lu, Senkui Dalian Maritime Univ Sch Marine Elect Engn Dalian 116026 Peoples R China Beijing Jiaotong Univ Sch Elect & Informat Engn Beijing 100044 Peoples R China

This paper develops an improved model predictive controller based on the online obtaining of softness factor and fusion velocity for automatic train operation to enhance the tracking control performance. Specifically, the softness factor of the improved model predictive control algorithm is not a constant, conversely, an improved online adaptive adjusting method for softness factor based on fuzzy satisfaction of system output value and velocity distance trajectory characteristic is adopted, and an improved whale optimization algorithm has been proposed to solve the adjustable parameters;meanwhile, the system output value for automatic train operation is not sampled by a normal speed sensor, on the contrary, an improved online velocity sampled method for the system output value based on a fusion velocity model and an intelligent digital torque sensor is applied. In addition, the two improved strategies proposed take the real-time storage and calculation capacities of the core chip of the controller into account. Therefore, the proposed improved strategies (I) have good performance in tracking precision, (II) are simple and easily conducted, and (III) can ensure the accomplishing of computational tasks in real-time. Finally, to verify the effectiveness of the improved model predictive controller, the Matlab/simulink simulation and hardware-in-the-loop simulation (HILS) are adopted for automatic train operation tracking control, and the tracking control simulation results indicate that the improved model predictive controller has better tracking control effectiveness compared with the existing traditional improved model predictive controller.

关键词： model predictive controller automatic train operation softness factor fusion velocity online obtaining hardware-in-the-loop simulation

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model predictive controller for single-phase distributed generator with seamless transition between grid and off-grid modes

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IET GENERATION TRANSMISSION & DISTRIBUTION 2019年第10期13卷 1829-1837页

作者： Sekhar, Perumalla Chandra Tupakula, Ratna Rahul IIT Bhubaneshwar Sch Elect Sci Bhubaneswar India Natl Inst Technol Dept Elect Engn Warangal Andhra Pradesh India

This study develops a model predictive controller for single-phase distributed generator with seamless transition between the grid and off-grid modes of operation. In addition, a simple synchronisation mechanism is developed to achieve the smooth transition between the grid and off-grid modes, thereby avoiding the complex multi-loop controls. The voltage vectors, hence the switching pulses are generated by using space vector modulation technique based on the minimisation of the cost function of the predictive model. The two cost functions considered are instantaneous power errors and instantaneous voltage errors, respectively, for the grid and islanded operation of the single-phase generator. The performance of the developed controller for feeding the set-point powers in grid connected mode and serving the load at nominal voltage and frequency in off-grid mode is verified using simulations. The simulation results are experimentally validated on a prototype.

关键词： predictive control power grids synchronisation distributed power generation power generation control seamless transition off-grid mode model predictive controller single-phase distributed generator complex multiloop controls grid connected mode space vector modulation

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model predictive controller-based spatiotemporal path tracking method for transhumeral prostheses

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INTERNATIONAL JOURNAL OF MEDICAL ROBOTICS AND COMPUTER ASSISTED SURGERY 2019年第3期15卷 e1980-e1980页

作者： Gamage, Kanishka Madusanka Dannangoda Gopura, R. A. Ruwan C. Amarasinghe, Y. W. Ranjith Mann, George K. I. Univ Moratuwa Dept Mech Engn Bion Lab Moratuwa Sri Lanka Chinese Acad Sci Shenzhen Inst Adv Technol Med Robot & Biomech Lab Shenzhen Peoples R China Univ Moratuwa Dept Mech Engn Moratuwa Sri Lanka Mem Univ Newfoundland Fac Engn & Appl Sci St John NF Canada

BackgroundTranshumeral prostheses are worn by transhumeral amputees to replace the missing upper limb segment between shoulder and elbow. Prostheses should be able to function as a natural limb for the user to gain the full advantage of wearing a prosthesis. When performing reach-to-grasp and pointing motions by the upper limb, the hand is capable of adhering to a straight-line path with a bell-shaped velocity profile. AimAim was to develop a dynamic path-tracking method for transhumeral prostheses to gain the capability of adhering to a straight-line path. MethodProposed method uses model predictive controller (MPC) developed based on the kinematic model of the prosthesis. Moreover, a shoulder matcher is proposed to match actual shoulder pose with the predicted shoulder pose and to select the best joint angles for the prosthesis for a particular instance. Furthermore, the proposed method is capable of dynamically updating the path if the human performs shoulder motions, which are not as planned by the MPC. ResultsSeveral experiments are conducted to validate the proposed method. The proposed method is capable of taking a straight-line path similar to a natural human. ConclusionThis paper proposed a dynamic path-tracking method based on a model predictive controller. The proposed method is capable of taking the prosthetic hand on a straight-line path, which is similar to a path taken by a natural human hand.

关键词： model predictive controller path tracking reach-to-grasp path planning transhumeral prosthesis

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model predictive controller-Based Voltage and Frequency Regulation in Renewable Energy Integrated Power System Coordinated with Virtual Inertia and Redox Flow Battery

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IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY-TRANSACTIONS OF ELECTRICAL ENGINEERING 2023年第1期47卷 159-176页

作者： Kumar, Vineet Sharma, Veena Naresh, R. Natl Inst Technol Hamirpur Elect Engn Dept Hamirpur 177005 Himachal Prades India

This manuscript discusses the concurrent voltage and frequency control problem for an interconnected system having three areas, each containing thermal and diesel units in conjunction with renewable integration from a separate source. In the first case study, renewable sources like wind, solar, and geothermal have been incorporated using a static transfer function-based model without considering variability in wind and solar. In the second case study, the dynamic model of wind and solar has been considered after incorporating the deterministic drifts and stochastic fluctuations. The paper presents Harris hawks optimized model predictive controller (MPC-HHO) to curtail the frequency and voltage fluctuations caused due to the sudden change in loading pattern. Additionally, the authors have incorporated various dynamic energy storage devices like virtual inertia and redox flow battery (VI-RFB) in coordination with the MPC-HHO controller. From the obtained results, it has been validated that the transient response from the proposed MPC-HHO controller coordinated with VI-RFB has superior characteristics when compared with state-of-the-art methodologies available in the existing literature. Further, the most prevalent nonlinearities present in the realistic power system have been considered and their effects on the controller's performance have been investigated and the robustness of the proposed MPC-HHO controller coordinated with VI-RFB has been successfully validated.

关键词： Automatic voltage control Harris hawks optimization algorithm Load frequency control model predictive controller

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model predictive controller Design of a Wavelength-Based Thermo-Electrical model of a Photovoltaic (PV) Module for Optimal Output Power

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INTERNATIONAL JOURNAL OF ENGINEERING RESEARCH IN AFRICA 2020年 48卷 133-148页

作者： Gbadega, Peter Anuoluwapo Saha, Akshay Kumar Univ KwaZulu Natal Sch Engn Howard Coll Campus King George Ave ZA-4041 Durban South Africa

As it stands, in terms of environmental impact and efficiency, photovoltaic (PV) energy has appeared to be a potential renewable power source that notably contends with the traditional power generation schemes. More so, a noteworthy factor that contrariwise influences the PV module efficiency is the PV module temperature. Therefore, the more the PV module temperature increases, the lesser the PV module efficiency. More importantly, the impact of undesired spectrum wavelengths on the PV module temperature is further reduced by passive optical filters, nonetheless, active optical filters which is more superior to the passive type, based on the PV module temperature and output power during the day, dynamically changes the cut-off wavelength. Consequently, the efficiency as well as the lifecycle is both enhanced by controlling the active optical filter so as to attain optimal output power. Therefore, in this paper, a wavelength-based thermo-electrical model of a PV module was designed and simulated, the essence of this model is mainly to predict the impact of each module wavelength on both the temperature and the output power of the PV module. In view of this, since the output power is affluence by the module temperature, it is expedient to design a controller that locates the optimal cut-off spectral wavelength to lessen the module temperature whereas getting the most out of the output power over a period of time. In this vein, we designed a model predictive controller whose objective is to maximize the output power by simply controlling the input power through filtering the spectrum wavelength for a photovoltaic (PV) system. The design and simulation of the plant model as well as the MPC controller were carried-out on MATLAB/Simulink environment.

关键词： Photovoltaic (PV) cells temperature dependence model predictive controller optimum output power system linearization system identification

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model predictive controller-Based Levothyroxine Dosing Strategy for Patients Suffering from Hashimoto's Thyroiditis 12

Model Predictive Controller-Based Levothyroxine Dosing Strat...

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12th IFAC Symposium on Biological and Medical Systems (BMS)

作者： Sharma, Ravi Goede, Simon Lucas Theiler-Schwetz, Verena Reichhartinger, Markus Graz Univ Technol Inst Automat & Control Graz Austria Med Univ Graz Dept Internal Med Div Endocrinol & Diabetol Graz Austria

Hashimoto's thyroiditis is the primary cause of hypothyroidism, resulting in insufficient thyroid hormone production, mainly thyroxine and triiodothyronine. Treatment involves achieving desired hormone levels through the oral intake of thyroxine hormone, primarily levothyroxine. Achieving adequate patient-specific thyroid hormone concentrations typically requires several visits with medical professionals. In this study, a patient-specific levothyroxine dosage has been identified using a model-predictive controller-based levothyroxine dosing strategy. The proposed study demonstrates that the designed levothyroxine dosing strategy yields a reliable response and even considers variations in the patient's biological parameters. Copyright (C) 2024 The Authors. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0/)

关键词： Hashimoto's thyroiditis Set-point theory Mathematical thyroid model model predictive controller

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model predictive controller Performance Monitoring Based on Impulse Response Identification

Model Predictive Controller Performance Monitoring Based on ...

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9th Asian Control Conference (ASCC)

作者： Zhao, Zhong Song, Feng Yang, Hailiang Beijing Univ Chem Technol Coll Informat Sci & Technol Beijing 100029 Peoples R China

ISBN: (纸本)9781467357692;9781467357678

model predictive control has been applied widely recently. But many model predictive controllers cannot be operated for a long time, the main reason is that there is lacking of model predictive controller performance monitoring system, then the model predictive controller is absent from self-healing ability. Based on Haar scale transform, a method of identification of impulse response for closed-loop sensitivity function and complementary sensitivity function is proposed. Combining the principle of model predictive control and robustness analysis, a method of model predictive controller performance monitoring based on identified impulse response for closed-loop sensitivity function and complementary sensitivity function is proposed. Simulation results and industrial application results have verified the feasibility and effectiveness of the proposed method.

关键词： model predictive controller Performance monitoring Sensitivity function Complementary sensitivity function Impulse response identification Orthogonal scale transform Haar scale function

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model predictive controller Design and Perturbation Study for Magnetic Levitation System

Model Predictive Controller Design and Perturbation Study fo...

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Conference on Recent Advances in Engineering and Computational Sciences (RAECS)

作者： Chauhan, Shailendra Nigam, M. J. IIT Roorkee Dept Elect & Commun Engn Roorkee Uttar Pradesh India

ISBN: (纸本)9781479922918

This paper presents a model predictive controller design structure for the magnetic levitation control system based on prediction theory which gives an optimum performance under external disturbances. The conventional controller like PID gets failed to control the system effectively under such disturbances, so an accurate model and complex algorithm are required to design a self tuned PID controller. It uses receding horizon principle in which controller checks and optimizes the control problem at each sampling instant. Only the first value of optimized solution is applied to the plant and rest values are discarded. This process gets repeated.

关键词： model predictive controller magnetic levitation system MATLAB receding horizon

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Tuning a model predictive controller for doubly fed induction generator employing a constrained genetic algorithm

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IET ELECTRIC POWER APPLICATIONS 2019年第6期13卷 819-826页

作者： Rodrigues, Lucas L. Potts, Alain S. Vilcanqui, Omar A. C. Sguarezi Filho, Alfeu J. Fed Univ ABC UFABC Santo Andre SP Brazil Fed Univ Acre UFAC Rio Branco AC Brazil

This study presents a model predictive control (MPC) for a doubly fed induction generator (DFIG) power control using a state-space prediction model. Genetic algorithms (GAs) have demonstrated their potential in finding good solutions for complex problems. However, GA in its original form lacks a mechanism for handling constraints. In this way, a method for tuning the MPC based on a novel constrained GA is proposed. In this way, the method permits a good solution for the weighing matrices with predetermined maximum requirements, such as maximum overshoot, just using the DFIG control simulation. Finally, experimental results are presented to endorse the proposed theory.

关键词： genetic algorithms predictive control asynchronous generators power control state-space methods machine control model predictive controller doubly fed induction generator constrained genetic algorithm model predictive control MPC power control state-space prediction model genetic algorithms GA DFIG control simulation

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Optimal electrical vehicle-to-grid integration: three-phase three-level AC/DC converter with model predictive controller based bidirectional power management scheme

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ELECTRICAL ENGINEERING 2024年 1-23页

作者： Srivastava, Abhinav Manas, Munish Dubey, Rajesh Kumar Cent Univ Haryana Dept Elect Engn Mahendragarh Haryana India

The control and modeling of an electric vehicle charging station with a three-level converter are discussed in this study from both the grid side and the EV side. The primary subject of discussion is the control systems for charging stations with a bidirectional DC/DC charging regulator and a three-level AC/DC power conversion. In order to manage the duty cycle of the converter during the AC-to-DC conversion stage, three alternative controller techniques-proportional-integral, proportional-integral-derivative, and model predictive controller-are developed in this study. The goal of the study is to understand how these controller techniques impact the battery's charging and discharging processes in a bidirectional charging system. To evaluate and compare the different controller schemes, the simulation results and assesses their performance based on various criteria including charging/discharging efficiency, voltage and current, battery state-of-charge regulation, and response time. The simulation results show that in terms of peak overshoot and settling time, the MPC controller performs better than the conventional proportional-integral and proportional-integral-derivative controllers. Also, an experimental validations were carried out on a laboratory-scale three-phase two-stage bidirectional electric vehicle (EV) charger, featuring a 48 V 4 kW Li-ion battery, under the control of a dSPACE controller. These experiments show that the method achieves rapid dynamics and robust steady-state performance. The significance of the controller selection in bidirectional charging systems, emphasizing the benefits of using model predictive control for better battery charging and discharging outcomes.

关键词： Electric vehicles model predictive controller PI and PID controller AC and DC converter

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