Torque-Flux linkage Recurrent Neural Network Adaptive Inversion Control of Torque for Switched Reluctance Motor

[1]  Yihua Hu,et al.  A Review on Machine Topologies and Control Techniques for Low-Noise Switched Reluctance Motors in Electric Vehicle Applications , 2018, IEEE Access.

[2]  Jian Liu,et al.  A Novel Method for Modeling the Electromagnetic Characteristics of Switched Reluctance Motors , 2018 .

[3]  Shahram Jadid,et al.  An expert system to improve power system contingency analysis , 1997 .

[4]  Amir Reza Zare Bidaki,et al.  Stability of Feedback Error Learning for Linear Systems , 2011 .

[5]  Levente Kovács,et al.  Simulation and control for telerobots in space medicine , 2012 .

[6]  Carlos Sagues,et al.  Real-Time Electromagnetic Estimation for Reluctance Actuators , 2019, IEEE Transactions on Industrial Electronics.

[7]  Man Zhang,et al.  A New Fast Method for Obtaining Flux-Linkage Characteristics of SRM , 2015, IEEE Transactions on Industrial Electronics.

[8]  K Khorasani,et al.  An ensemble of dynamic neural network identifiers for fault detection and isolation of gas turbine engines , 2016, Neural Networks.

[9]  Der-Fa Chen,et al.  Nonlinear Backstepping Control of SynRM Drive Systems Using Reformed Recurrent Hermite Polynomial Neural Networks with Adaptive Law and Error Estimated Law , 2018 .

[10]  Zhao Xianchao,et al.  Torque-ripple reduction of SRM using optimised voltage vector in DTC , 2018 .

[11]  Shun-Yuan Wang,et al.  Adaptive TSK fuzzy sliding mode control design for switched reluctance motor DTC drive systems with torque sensorless strategy , 2018, Appl. Soft Comput..

[12]  Chih-Hong Lin,et al.  Novel Nonlinear Backstepping Control of Synchronous Reluctance Motor Drive System for Position Tracking of Periodic Reference Inputs with Torque Ripple Consideration , 2019 .

[13]  Usha Nair,et al.  Fuzzy Sliding Mode Control of a Switched Reluctance Motor , 2016 .

[14]  Ali Elrayyah,et al.  Flux-Weakening Control of Switched Reluctance Machines in Rotating Reference Frame , 2016, IEEE Transactions on Industry Applications.

[15]  Noriyasu Homma,et al.  An Approach to Stable Gradient-Descent Adaptation of Higher Order Neural Units , 2016, IEEE Transactions on Neural Networks and Learning Systems.

[16]  Eyyup Oksuztepe.  In-Wheel Switched Reluctance Motor Design for Electric Vehicles by Using a Pareto-Based Multiobjective Differential Evolution Algorithm , 2017, IEEE Trans. Veh. Technol..

[17]  Jianjun Wang.  Position tracking control of switched reluctance motor with adaptive linear element based on current-sharing method , 2016, Neurocomputing.

[18]  Jia-Jun Wang.  A common sharing method for current and flux-linkage control of switched reluctance motor , 2016 .

[19]  Jia-Jun Wang,et al.  Adaptive inverse position control of switched reluctance motor , 2017, Appl. Soft Comput..

[20]  Shengdun Zhao,et al.  A Sliding Mode Flux-Linkage Controller With Integral Compensation for Switched Reluctance Motor , 2009, IEEE Transactions on Magnetics.

[21]  Saso Blazic,et al.  On Periodic Control Laws for Mobile Robots , 2014, IEEE Transactions on Industrial Electronics.

[22]  J. G. Ziegler,et al.  Optimum Settings for Automatic Controllers , 1942, Journal of Fluids Engineering.

[23]  Kwang Y. Lee,et al.  Diagonal recurrent neural networks for dynamic systems control , 1995, IEEE Trans. Neural Networks.

[24]  Wen Ding,et al.  Characteristics Assessment and Comparative Study of a Segmented-Stator Permanent-Magnet Hybrid-Excitation SRM Drive With High-Torque Capability , 2018, IEEE Transactions on Power Electronics.

[25]  Siamak Masoudi,et al.  Adaptive fuzzy control method for a linear switched reluctance motor , 2018, IET Electric Power Applications.

[26]  T. Anzai,et al.  Removal of Humic Acid in Water by Rice Hull Magnetic Activated Carbon and Magnetic Separation , 2016, IEEE Transactions on Applied Superconductivity.

[27]  Ehsan Rahmanian,et al.  Maximum Power Point Tracking in Grid Connected Wind Plant by Using Intelligent Controller and Switched Reluctance Generator , 2017, IEEE Transactions on Sustainable Energy.

[28]  P. J. Costa Branco,et al.  Sliding mode angular position control for an 8/6 Switched Reluctance Machine: Theoretical concept, design and experimental results , 2015 .

[29]  Cunhe Li,et al.  Robust adaptive neural network control for switched reluctance motor drives , 2018 .

[30]  Yu Wang,et al.  Research on Rotor Position Model for Switched Reluctance Motor Using Neural Network , 2018, IEEE/ASME Transactions on Mechatronics.

[31]  Yun Li,et al.  PID control system analysis, design, and technology , 2005, IEEE Transactions on Control Systems Technology.

[32]  Yan Li,et al.  Direct adaptive neural network control for switched reluctance motors with input saturation , 2018, IEEJ Transactions on Electrical and Electronic Engineering.

[33]  Richard Martin,et al.  Design and Development of Low Torque Ripple Variable-Speed Drive System With Six-Phase Switched Reluctance Motors , 2018, IEEE Transactions on Energy Conversion.

[34]  Mojtaba Ahmadieh Khanesar,et al.  Feedback Error Learning Control of Magnetic Satellites Using Type-2 Fuzzy Neural Networks With Elliptic Membership Functions , 2015, IEEE Transactions on Cybernetics.