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The DSpace digital repository system captures, stores, indexes, preserves, and distributes digital research material.Fri, 20 Sep 2019 07:34:25 GMT2019-09-20T07:34:25ZReal-time validation of a cascaded model predictive control technique for a five-phase permanent magnet synchronous machine under current and voltage limits
http://hdl.handle.net/10985/13805
Real-time validation of a cascaded model predictive control technique for a five-phase permanent magnet synchronous machine under current and voltage limits
BERMUDEZ GUZMAN, Mario; GOMOZOV, Oleg; KESTELYN, Xavier; NGUYEN, Ngac Ky; SEMAIL, Eric; BARRERO, Federico
Multiphase machines have recently gained importance in the research community for their use in applications where high power density, wide speed range and fault-tolerant capabilities are needed. The optimal control of such drives requires to consider voltage and current constraints imposed by the power converter and the machine itself. If classical three-phase drives have been optimally controlled under such limits for a long time, the same cannot be said in the case of multiphase drives. This paper deals with this issue, where an optimal control technique based on Cascaded Model Predictive Controls (MPC) is presented for a five-phase permanent magnet synchronous machine (PMSM). A Continuous-Control-Set MPC (CCSMPC) numerically computes optimal current references in real-time in order to exploit the maximum performance for given DC bus voltage and current limits. Then, a Finite-Control-Set MPC (FCS-MPC) is used to carry out the current control in the machine, directly applying the switching state that minimizes a cost function related to the current tracking. Obtained mixed microprocessor-based and FPGAbased real-time simulations prove the interest of the proposal, which ensures the optimal control of the multiphase drive operating under current and voltage constraints.
Sun, 01 Jan 2017 00:00:00 GMThttp://hdl.handle.net/10985/138052017-01-01T00:00:00ZBERMUDEZ GUZMAN, MarioGOMOZOV, OlegKESTELYN, XavierNGUYEN, Ngac KySEMAIL, EricBARRERO, FedericoMultiphase machines have recently gained importance in the research community for their use in applications where high power density, wide speed range and fault-tolerant capabilities are needed. The optimal control of such drives requires to consider voltage and current constraints imposed by the power converter and the machine itself. If classical three-phase drives have been optimally controlled under such limits for a long time, the same cannot be said in the case of multiphase drives. This paper deals with this issue, where an optimal control technique based on Cascaded Model Predictive Controls (MPC) is presented for a five-phase permanent magnet synchronous machine (PMSM). A Continuous-Control-Set MPC (CCSMPC) numerically computes optimal current references in real-time in order to exploit the maximum performance for given DC bus voltage and current limits. Then, a Finite-Control-Set MPC (FCS-MPC) is used to carry out the current control in the machine, directly applying the switching state that minimizes a cost function related to the current tracking. Obtained mixed microprocessor-based and FPGAbased real-time simulations prove the interest of the proposal, which ensures the optimal control of the multiphase drive operating under current and voltage constraints.Investigation on Model Predictive Control of a Five-Phase Permanent Magnet Synchronous Machine under Voltage and Current limits
http://hdl.handle.net/10985/9946
Investigation on Model Predictive Control of a Five-Phase Permanent Magnet Synchronous Machine under Voltage and Current limits
KESTELYN, Xavier; GOMOZOV, Oleg; BUIRE, Jerome; COLAS, Frédéric; NGUYEN, Ngac Ky; SEMAIL, Eric
The optimal control of electrical drives necessitates to take into account current and voltage limits that are imposed by the power electronics and the electrical machines. Let’s cite for example the flux-weakening operation of electrical drives for propulsion. If the control of classical three-phase drives Under voltage and current limits are known for a long time, the specific characteristics of multiphase drives open the way to researches on their control under such constraints. This paper aims to explain what are the main differences between three-phase and multiphase drives when they run under voltage and current constraints and try to show what are the scientific and technical problems to be solved. Some first results are given in order to show that Model Predictive Control (MPC) is expected to be a good candidate to answer the proposed challenge.
Thu, 01 Jan 2015 00:00:00 GMThttp://hdl.handle.net/10985/99462015-01-01T00:00:00ZKESTELYN, XavierGOMOZOV, OlegBUIRE, JeromeCOLAS, FrédéricNGUYEN, Ngac KySEMAIL, EricThe optimal control of electrical drives necessitates to take into account current and voltage limits that are imposed by the power electronics and the electrical machines. Let’s cite for example the flux-weakening operation of electrical drives for propulsion. If the control of classical three-phase drives Under voltage and current limits are known for a long time, the specific characteristics of multiphase drives open the way to researches on their control under such constraints. This paper aims to explain what are the main differences between three-phase and multiphase drives when they run under voltage and current constraints and try to show what are the scientific and technical problems to be solved. Some first results are given in order to show that Model Predictive Control (MPC) is expected to be a good candidate to answer the proposed challenge.Model predictive optimal control considering current and voltage limitations: Real-time validation using OPAL-RT technologies and five-phase permanent magnet synchronous machines
http://hdl.handle.net/10985/14556
Model predictive optimal control considering current and voltage limitations: Real-time validation using OPAL-RT technologies and five-phase permanent magnet synchronous machines
BERMUDEZ GUZMAN, Mario; GOMOZOV, Oleg; KESTELYN, Xavier; BARRERO, Federico; NGUYEN, Ngac Ky; SEMAIL, Eric
Multiphase machines have recently gained interest in the research community for their use in applications where high power density, wide speed range and fault-tolerant capabilities are required. The optimal control of such drives requires the consideration of voltage and current limits imposed by the power converter and the machine. While conventional three-phase drives have been extensively analyzed taking into account such limits, the same cannot be said in the multiphase drives’ case. This paper deals with this issue, where a novel two-stage Model Predictive optimal Control (2S-MPC) technique is presented, and a five-phase permanent magnet synchronous multiphase machine (PMSM) is used as a case example. The proposed method first applies a Continuous-Control-Set Model Predictive Control (CCS-MPC) stage to obtain the optimal real-time stator current reference for given DC-link voltage and stator current limits, exploiting the maximum performance characteristics of the multiphase drive. Then, a Finite-Control-Set Model Predictive Control (FCS-MPC) stage is utilized to generate the switching state in the power converter and force the stator current tracking. An experimental validation of the proposed controller is finally provided using a real-time simulation environment based on OPAL-RT technologies.
Tue, 01 Jan 2019 00:00:00 GMThttp://hdl.handle.net/10985/145562019-01-01T00:00:00ZBERMUDEZ GUZMAN, MarioGOMOZOV, OlegKESTELYN, XavierBARRERO, FedericoNGUYEN, Ngac KySEMAIL, EricMultiphase machines have recently gained interest in the research community for their use in applications where high power density, wide speed range and fault-tolerant capabilities are required. The optimal control of such drives requires the consideration of voltage and current limits imposed by the power converter and the machine. While conventional three-phase drives have been extensively analyzed taking into account such limits, the same cannot be said in the multiphase drives’ case. This paper deals with this issue, where a novel two-stage Model Predictive optimal Control (2S-MPC) technique is presented, and a five-phase permanent magnet synchronous multiphase machine (PMSM) is used as a case example. The proposed method first applies a Continuous-Control-Set Model Predictive Control (CCS-MPC) stage to obtain the optimal real-time stator current reference for given DC-link voltage and stator current limits, exploiting the maximum performance characteristics of the multiphase drive. Then, a Finite-Control-Set Model Predictive Control (FCS-MPC) stage is utilized to generate the switching state in the power converter and force the stator current tracking. An experimental validation of the proposed controller is finally provided using a real-time simulation environment based on OPAL-RT technologies.Real-Time Validation of a Cascaded Model Predictive Control Technique for a Five-Phase Permanent Magnet Synchronous Machine Under Current and Voltage Limits
http://hdl.handle.net/10985/13801
Real-Time Validation of a Cascaded Model Predictive Control Technique for a Five-Phase Permanent Magnet Synchronous Machine Under Current and Voltage Limits
BERMUDEZ GUZMAN, Mario; GOMOZOV, Oleg; KESTELYN, Xavier; NGUYEN, Ngac Ky; SEMAIL, Eric; BARRERO, Federico
Multiphase machines have recently gained importance in the research community for their use in applications where high power density, wide speed range and fault-tolerant capabilities are needed. The optimal control of such drives requires to consider voltage and current constraints imposed by the power converter and the machine itself. If classical three-phase drives have been optimally controlled under such limits for a long time, the same cannot be said in the case of multiphase drives. This paper deals with this issue, where an optimal control technique based on Cascaded Model Predictive Controls (MPC) is presented for a five-phase permanent magnet synchronous machine (PMSM). A Continuous-Control-Set MPC (CCS-MPC) numerically computes optimal current references in real-time in order to exploit the maximum performance for given DC bus voltage and current limits. Then, a Finite-Control-Set MPC (FCS-MPC) is used to carry out the current control in the machine, directly applying the switching state that minimizes a cost function related to the current tracking. Obtained mixed microprocessor-based and FPGA-based real-time simulations prove the interest of the proposal, which ensures the optimal control of the multiphase drive operating under current and voltage constraints.
Sun, 01 Jan 2017 00:00:00 GMThttp://hdl.handle.net/10985/138012017-01-01T00:00:00ZBERMUDEZ GUZMAN, MarioGOMOZOV, OlegKESTELYN, XavierNGUYEN, Ngac KySEMAIL, EricBARRERO, FedericoMultiphase machines have recently gained importance in the research community for their use in applications where high power density, wide speed range and fault-tolerant capabilities are needed. The optimal control of such drives requires to consider voltage and current constraints imposed by the power converter and the machine itself. If classical three-phase drives have been optimally controlled under such limits for a long time, the same cannot be said in the case of multiphase drives. This paper deals with this issue, where an optimal control technique based on Cascaded Model Predictive Controls (MPC) is presented for a five-phase permanent magnet synchronous machine (PMSM). A Continuous-Control-Set MPC (CCS-MPC) numerically computes optimal current references in real-time in order to exploit the maximum performance for given DC bus voltage and current limits. Then, a Finite-Control-Set MPC (FCS-MPC) is used to carry out the current control in the machine, directly applying the switching state that minimizes a cost function related to the current tracking. Obtained mixed microprocessor-based and FPGA-based real-time simulations prove the interest of the proposal, which ensures the optimal control of the multiphase drive operating under current and voltage constraints.