Dear Editor,This letter proposes an arbitrary pre-assigned time sliding mode approach to achieve distributed secondary control for microgrids with external disturbances.By constructing an effective time-varying gain f...Dear Editor,This letter proposes an arbitrary pre-assigned time sliding mode approach to achieve distributed secondary control for microgrids with external disturbances.By constructing an effective time-varying gain function,we can set the convergence time arbitrarily to stabilize the system,which is without being affected by initial conditions and other design parameters.展开更多
Model predictive current control(MPCC)and model predictive torque control(MPTC)are two derivatives of model predictive control.These two control methods have demonstrated their strengths in the fault-tolerant control ...Model predictive current control(MPCC)and model predictive torque control(MPTC)are two derivatives of model predictive control.These two control methods have demonstrated their strengths in the fault-tolerant control of multiphase motor drives.To explore the inherent link,the pros and cons of two strategies,the performance analysis and comparative investigation of MPCC and MPTC are conducted through a five-phase permanent magnet synchronous motor with open-phase fault.In MPCC,the currents of fundamental and harmonic subspaces are simultaneously employed and constrained for a combined regulation of the open-circuit fault drive.In MPTC,apart from the torque and the stator flux related to fundamental subspace,the x-y currents are also considered and predicted to achieve the control of harmonic subspace.The principles of two methods are demonstrated in detail and the link is explored in terms of the cost function.Besides,the performance by two methods is experimentally assessed in terms of steady-state,transition,and dynamic tests.Finally,the advantages and disadvantages of each method are concluded.展开更多
In this article, an inter-turn short-circuit(ITSC) fault diagnosis and severity estimation method based on extended state observer(ESO) and convolutional neural network(CNN) is proposed for five-phase permanent magnet...In this article, an inter-turn short-circuit(ITSC) fault diagnosis and severity estimation method based on extended state observer(ESO) and convolutional neural network(CNN) is proposed for five-phase permanent magnet synchronous motor(PMSM) drives. The relationship between fault parameters and motor parameters is analyzed and the equivalent model of ITSC faults in the natural reference frame is accordingly derived. To achieve fault detection and location, the short-circuit turn ratio and short-circuit current are integrated as the fault diagnosis index. According to the model of the shortcircuit current, an ESO is designed for the estimation of the fault diagnosis index. Further, the sensitivity analysis among fault parameters is conducted to evaluate the short-circuit turn ratio and the short-circuit resistance. Subsequently, the postfault current, back electromotive force, electrical angular velocity, q1-axis current reference and the fault diagnosis index are selected as the input signals of CNN to estimate the short-circuit turn ratio. This approach not only resolves parameter coupling challenges but also provides a quantitative assessment of fault severity. Finally, simulations and experiments under different operating points validate the effectiveness of the proposed method.展开更多
Dear Editor,This letter investigates the fixed-time trajectory tracking controller design for nonholonomic chained systems with static state constraints.Firstly,a fixed-time tracking control law is given to carry out ...Dear Editor,This letter investigates the fixed-time trajectory tracking controller design for nonholonomic chained systems with static state constraints.Firstly,a fixed-time tracking control law is given to carry out relay switching,which divides the controller development process into two stages.展开更多
With the deteriorating effects resulting from global warming in many areas, geographically distributed data centers contribute greatly to carbon emissions, because the major energy supply is fossil fuels. Considering ...With the deteriorating effects resulting from global warming in many areas, geographically distributed data centers contribute greatly to carbon emissions, because the major energy supply is fossil fuels. Considering this issue, many geographically distributed data centers are attempting to use clean energy as their energy supply, such as fuel cells and renewable energy sources. However, not all workloads can be powered by a single power sources, since different workloads exhibit different characteristics. In this paper, we propose a fine-grained heterogeneous power distribution model with an objective of minimizing the total energy costs and the sum of the energy gap generated by the geographically distributed data centers powered by multiple types of energy resources. In order to achieve these two goals, we design a two-stage online algorithm to leverage the power supply of each energy source. In each time slot, we also consider a chance-constraint problem and use the Bernstein approximation to solve the problem. Finally, simulation results based on real-world traces illustrate that the proposed algorithm can achieve satisfactory performance.展开更多
基金supported by the National Natural Science Foundation of China(62173175,61873033)the Shandong Provincial Natural Science Foundation(ZR2024MF032)。
文摘Dear Editor,This letter proposes an arbitrary pre-assigned time sliding mode approach to achieve distributed secondary control for microgrids with external disturbances.By constructing an effective time-varying gain function,we can set the convergence time arbitrarily to stabilize the system,which is without being affected by initial conditions and other design parameters.
基金supported in part by the Fundamental Research Funds for Central Universities under Grant JUSRP121020the Natural Science Foundation of Jiangsu Province under Grant BK20210475。
文摘Model predictive current control(MPCC)and model predictive torque control(MPTC)are two derivatives of model predictive control.These two control methods have demonstrated their strengths in the fault-tolerant control of multiphase motor drives.To explore the inherent link,the pros and cons of two strategies,the performance analysis and comparative investigation of MPCC and MPTC are conducted through a five-phase permanent magnet synchronous motor with open-phase fault.In MPCC,the currents of fundamental and harmonic subspaces are simultaneously employed and constrained for a combined regulation of the open-circuit fault drive.In MPTC,apart from the torque and the stator flux related to fundamental subspace,the x-y currents are also considered and predicted to achieve the control of harmonic subspace.The principles of two methods are demonstrated in detail and the link is explored in terms of the cost function.Besides,the performance by two methods is experimentally assessed in terms of steady-state,transition,and dynamic tests.Finally,the advantages and disadvantages of each method are concluded.
基金supported in part by the National Natural Science Foundation of China under Grant 52307056in part by the Natural Science Foundation of Jiangsu Province under Grant BK20210475。
文摘In this article, an inter-turn short-circuit(ITSC) fault diagnosis and severity estimation method based on extended state observer(ESO) and convolutional neural network(CNN) is proposed for five-phase permanent magnet synchronous motor(PMSM) drives. The relationship between fault parameters and motor parameters is analyzed and the equivalent model of ITSC faults in the natural reference frame is accordingly derived. To achieve fault detection and location, the short-circuit turn ratio and short-circuit current are integrated as the fault diagnosis index. According to the model of the shortcircuit current, an ESO is designed for the estimation of the fault diagnosis index. Further, the sensitivity analysis among fault parameters is conducted to evaluate the short-circuit turn ratio and the short-circuit resistance. Subsequently, the postfault current, back electromotive force, electrical angular velocity, q1-axis current reference and the fault diagnosis index are selected as the input signals of CNN to estimate the short-circuit turn ratio. This approach not only resolves parameter coupling challenges but also provides a quantitative assessment of fault severity. Finally, simulations and experiments under different operating points validate the effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China(62173207,62003148)the China Postdoctoral Science Foundation(2021M691277)the Youth Innovation Team Project of Colleges and Universities in Shandong Province(2022KJ176)。
文摘Dear Editor,This letter investigates the fixed-time trajectory tracking controller design for nonholonomic chained systems with static state constraints.Firstly,a fixed-time tracking control law is given to carry out relay switching,which divides the controller development process into two stages.
基金supported in part by National Natural Science Foundation of China (No. 61772286, No. 61802208)China Postdoctoral Science Foundation(No. 2019M651923)+2 种基金Natural Science Foundation of Jiangsu Province of China(No. BK20191381)Primary Research&Development Plan of Jiangsu Province(No. BE2019742)Natural Science Fund for Colleges and Universities in Jiangsu Province (No. 18KJB520036)。
文摘With the deteriorating effects resulting from global warming in many areas, geographically distributed data centers contribute greatly to carbon emissions, because the major energy supply is fossil fuels. Considering this issue, many geographically distributed data centers are attempting to use clean energy as their energy supply, such as fuel cells and renewable energy sources. However, not all workloads can be powered by a single power sources, since different workloads exhibit different characteristics. In this paper, we propose a fine-grained heterogeneous power distribution model with an objective of minimizing the total energy costs and the sum of the energy gap generated by the geographically distributed data centers powered by multiple types of energy resources. In order to achieve these two goals, we design a two-stage online algorithm to leverage the power supply of each energy source. In each time slot, we also consider a chance-constraint problem and use the Bernstein approximation to solve the problem. Finally, simulation results based on real-world traces illustrate that the proposed algorithm can achieve satisfactory performance.
