STCANet:Spatiotemporal Coupled Attention Network for Ocean Surface Current Prediction

Currently,numerical models based on idealized assumptions,complex algorithms and high computational costs are unsatisfactory for ocean surface current prediction.Moreover,the complex temporal and spatial variability of ocean currents also makes the prediction methods based on time series data challenging.The deep network model can automatically learn and extract complex features hidden in large amount of complex data,so it is a promising method for high quality prediction of ocean currents.In this paper,we propose a spatiotemporal coupled attention deep network model STCANet that can extract abundant temporal and spatial coupling information on the behavior characteristics of ocean currents for improving the prediction accuracy.Firstly,Spatial Module is designed and implemented to extract the spatiotemporal coupling characteristics of ocean currents,and meanwhile the spatial correlations and dependencies among adjacent sea areas are obtained through Spatial Channel Attention Module(SCAM).Secondly,we use the GatedRecurrent-Unit(GRU)to extract temporal relationships of ocean currents,and design and implement the nearest neighbor time attention module to extract the interdependences of ocean currents between adjacent times,which can further improve the accuracy of ocean current prediction.Finally,a series of comparative experiments on the MediSea_Dataset and EastSea_Dataset showed that the prediction quality of our model greatly outperforms those of other benchmark models such as History Average(HA),Autoregressive Integrated Moving Average Model(ARIMA),Long Short-term Memory(LSTM),Gate Recurrent Unit(GRU)and CNN_GRU.

An Improved Deadbeat Predictive Current Control Method for SPMSM Drives with a Novel Adaptive Disturbance Observer

To improve the dynamic performance of conventional deadbeat predictive current control(DPCC)under parameter mismatch,especially eliminate the current overshoot and oscillation during torque mutation,it is necessary to enhance the robustness of DPCC against various working conditions.However,the disturbance from parameter mismatch can deteriorate the dynamic performance.To deal with the above problem,firstly,traditional DPCC and the parameter sensitivity of DPCC are introduced and analyzed.Secondly,an extended state observer(ESO)combined with DPCC method is proposed,which can observe and suppress the disturbance due to various parameter mismatch.Thirdly,to improve the accuracy and stability of ESO,an adaptive extended state observer(AESO)using fuzzy controller based on ESO,is presented,and combined with DPCC method.The improved DPCC-AESO can switch the value of gain coefficients with fuzzy control,accelerating the current response speed and avoid the overshoot and oscillation,which improves the robustness and stability performance of SPMSM.Finally,the three methods,as well as conventional DPCC method,DPCC-ESO method,DPCC-AESO method,are comparatively analyzed in this paper.The effectiveness of the proposed two methods are verified by simulation and experimental results.

Model Predictive Current Control with Adaptive-adjusting Timescales for PMSMs

A model predictive current control(MPCC)with adaptive-adjusting method of timescales for permanent magnet synchronous motors(PMSMs)is proposed in this paper to improve the dynamic response and prediction accuracy in transient-state,while lessening the computational burden and improving the control performance in steady-state.The timescale characteristics of different parts of MPCC,such as signal sampling,prediction calculation,control output,model error correction,are analyzed,and the algorithm architecture of MPCC with multi-timescale is proposed.The difference between reference and actual speed,and the change rate of actual speed are utilized to discriminate the transient state of speed change and load change,respectively.Adaptive-adjusting method of control period and prediction stepsize are illustrated in detail after operation condition discrimination.Experimental results of a PMSM are presented to validate the effectiveness of proposed MPCC.In addition,comparative evaluation of single-step MPCC with fixed timescale and proposed MPCC is conducted,which demonstrates the superiority of proposed control strategy.

Predictive current control system of PMSM based on LADRC

For a permanent magnet synchronous motor(PMSM)model predictive current control(MPCC)system,when the speed loop adopts proportional-integral(PI)control,speed regulation is easily affected by motor parameters,resulting in the inability to balance the system robustness and dynamic performance.A PMSM optimal control strategy combining linear active disturbance rejection control(LADRC)and two-vector MPCC(TV-MPCC)is proposed.Firstly,a mathematical model of a PMSM is presented,and the PMSM TV-MPCC model is developed in the synchronous rotation coordinate system.Secondly,a first-order LADRC controller composed of a linear extended state observer and linear state error feedback is designed to reduce the complexity of parameter tuning while linearly simplifying the traditional active disturbance rejection control(ADRC)structure.Finally,the conventional PI speed regulator in the motor speed control system is replaced by the designed LADRC controller.The simulation results show that the speed control system using LADRC can effectively deal with the changes in motor parameters and has better robustness and dynamic performance than PI control and similar methods.The system has a fast motor speed response,small overshoot,strong anti-interference,and no steady-state error,and the total harmonic distortion is reduced.

Model predictive current control for PMSM driven by three-level inverter based on fractional sliding mode speed observer

Based on the fractional order theory and sliding mode control theory,a model prediction current control(MPCC)strategy based on fractional observer is proposed for the permanent magnet synchronous motor(PMSM)driven by three-level inverter.Compared with the traditional sliding mode speed observer,the observer is very simple and eases to implement.Moreover,the observer reduces the ripple of the motor speed in high frequency range in an efficient way.To reduce the stator current ripple and improve the control performance of the torque and speed,the MPCC strategy is put forward,which can make PMSM MPCC system have better control performance,stronger robustness and good dynamic performance.The simulation results validate the feasibility and effectiveness of the proposed scheme.

Finite Control Set Model Predictive Current Control of a Five-Phase PMSM with Virtual Voltage Vectors and Adaptive Control Set

This paper presents an improved finite control set model predictive current control(FCS-MPCC)of a five-phase permanent magnet synchronous motor(PMSM).First,to avoid including all the 32 voltage vectors provided by a two-level five-phase inverter into the control set,virtual voltage vectors are adopted.As the third current harmonics can be much reduced by virtual voltage vectors automatically,the harmonic items in the cost function of conventional FCS-MPCC are not considered.Furthermore,an adaptive control set is proposed based on voltage prediction.Best control set with proper voltage vector amplitude corresponding to different rotor speed can be achieved by this method.Consequently,current ripples can be largely reduced and the system performs much better.At last,simulations are established to verify the steady and transient performance of the proposed FCS-MPCC,and experiments based on a 2 kW five-phase motor are carried out.The results have validated the performance improvement of the proposed control strategy.

Zero-Sequence Current Suppression Strategy for Open-End Winding Permanent Magnet Synchronous Motor Based on Model Predictive Control

Compared with the traditional three-phase star connection winding,the open-end winding permanent magnet synchronous motor(OW-PMSM)system with a common direct current(DC)bus has a zero-sequence circuit,which makes the common-mode voltage and the back electromotive force(EMF)harmonic generated by the inverters produce the zero-sequence current in the zero-sequence circuit,and the zero-sequence current has great influence on the operation efficiency and stability of the motor control system.A zero-sequence current suppression strategy is presented based on model predictive current control for OW-PMSM.Through the mathematical model of OW-PMSM to establish the predictive model and the zero-sequence circuit model,the common-mode voltage under different voltage vector combinations is fully considered during vector selection and action time calculation.Then zero-sequence loop constraints are established,so as to suppress the zero-sequence current.In the end,the control strategy proposed in this paper is verified by simulation experiments.

Model Predictive Current Control for Low-Cost Shunt Active Power Filter

Performance of a three-phase shunt active power filter(SAPF)relies on the capability of the controller to track the reference current.Therefore,designing an accurate current controller is crucial to guarantee satisfactory SAPF operation.This paper presents a model predictive current controller(MPCC)for a low-cost,four-switch,shunt active power filter for power quality improvement.A four-switch,B4,converter topology is adopted as an SAPF,hence offering a simple,robust,and low-cost solution.In addition,to further reduce overall cost,only two interfacing filter inductors,instead of three,are used to eliminate switching current ripple.The proposed SAPF model MPCC is detailed for implementation,where simulation and experimental results validate effectiveness of the proposed control algorithm showing a 20%improvement in total harmonic distortion compared with a conventional hysteresis band current controller.

Low-complexity model predictive control of a four-level active neutral point clamped inverter without weighting factors

The four-level active neutral point clamped(ANPC)inverter has become increasingly widely used in the renewable energy indus-try since it offers one more voltage level without increasing the total number of active switches compared to the three-level ANPC inverter.The model predictive current control(MPCC)is a promising control method for multi-level inverters.However,the conven-tional MPCC suffers from high computational complexity and tedious weighting factor tuning in multi-level inverter applications.A low-complexity MPCC without weighting factors for a four-level ANPC inverter is proposed in this paper.The computational burden and voltage vector candidate set are reduced according to the relationship between voltage vector and neutral point voltage balance.The proposed MPCC shows excellent steady-state and dynamics performances while ensuring the neutral point voltage balancing.The efficacy of the proposed MPCC is verified by simulation and experimental results.

Improved Optimal Duty Model Predictive Current Control Strategy for PMSM

To further improve the steady-state performance of the conventional dual vector model predictive current control(MPCC),an improved optimal duty MPCC strategy for permanent magnet synchronous motor(PMSM)is proposed.This strategy is realized by selecting an optimal voltage vector combination and its duration from the five basic voltage vector combinations,followed by acting on the inverter.The five combinations are:the combination of the optimal voltage vector at the previous moment and basic voltage vector with an angle difference of 60°;the combination of the optimal voltage vector at the previous moment and basic voltage vector with an angle difference of-60°;the combination of the aforementioned three basic voltage vectors with the zero vector.Experimental results indicate that the method effectively reduces the stator current ripple without increasing the calculational burden.Furthermore,it improves the steady-state performance of the system without altering the dynamic performance of the system.

Predictive current control of multi-pulse flexible-topology thyristor AC-DC converter

This paper proposes a novel multi-pulse flexible-topology thyristor rectifier(FTTR) that can operate over a large voltage range while maintaining a low total harmonic distortion(THD) in the input current.The proposed multi-pulse FTTR has two operating modes:parallel mode and series mode.Irrespective of the mode in which it operates,the multi-pulse FTTR maintains the same pulses in the load current.To mitigate the harmonic injection into the AC mains,the topology-switching mechanism is then proposed.In addition,predictive current control is employed to achieve fast current response in both the transience and the transitions between modes.To verify the effectiveness of the multi-pulse FTTR as well as the control scheme,performance analysis based on an 18-pulse FTTR is investigated in detail,including fault tolerance evaluation,current THD analysis based on IEEE standard,and potential applications.Finally,a simulation model and the corresponding laboratory setup are developed.The results from both simulation and experiments demonstrate the feasibility of the proposed multi-pulse FTTR as well as the control scheme.

Short-circuit fault-tolerant control for five-phase fault-tolerant permanent magnet motors with trapezoidal back-EMF

When a short-circuit fault occurs in a phase,the faulty phase needs to be removed artificially from the system because of the loss of the capability to generate torque.In this case,both the short-circuit current and phase-loss fault would generate additional torque ripples.In this study,a novel fault-tolerant control strategy is introduced to achieve low torque ripple operation of five-phase fault-tolerant permanent magnet synchronous motors with trapezoidal back electromotive force(FTPMSM-TEMF)in the event of a short-circuit fault.The key concept of this method is to compensate for the torque ripples caused by the short-circuit current and the adverse effect of the phase-loss.Based on the torque expression under fault conditions,the torque ripple caused by the short-circuit current can be offset by injecting a certain pulsating component into the torque expression in the phase-loss condition.This would result in smooth operation under fault conditions.Moreover,to track the fault-tolerant alternating currents,the model of the deadbeat current predictive control is extended and restructured for the fault condition.The effectiveness and feasibility of the proposed fault-tolerant strategy are verified by experimental results.

Predictive field-oriented control of PMSM with space vector modulation technique

This paper is concerned with two popular and powerful methods in electrical drive applications:fieldoriented control(FOC)and space vector modulation(SVM).The proposed FOC-SVM method is incorporated with a predictive current control(PCC)-based technique.The suggested method estimates the desirable electrical torque to track mechanical torque at a fixed speed operation of permanent magnet synchronous motor(PMSM).The estimated torque is used to calculate the reference current based on FOC.In order to improve the performance of the traditional SVM,a PCC method is established as a switching pattern modifier.Therefore,PCC-based SVM is employed to further minimize the torque ripples and transient response.The performance of the controller is evaluated in terms of torque and current ripple and transient response to step variations of the torque command.The proposed method has been verified with MATLAB-Simulink model.Simulation results confirm the ability of this technique in minimizing the torque and speed ripples and fixing switching frequency,simultaneously.However,it is sensitive to parameter changes.