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A three-stage series model predictive torque and flux control system based on fast optimal voltage vector selection for more electric aircraft 认领 引用
1
作者 Zhaoyang FU Lixian PENG +2 位作者 Shuangrui PING Lefei GE Weilin LI 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2025年第11期315-328,共14页
With the development of More Electric Aircraft(MEA),the Permanent Magnet Synchronous Motor(PMSM)is widely used in the MEA field.The PMSM control system of MEA needs to consider the system reliability,and the inverter ... With the development of More Electric Aircraft(MEA),the Permanent Magnet Synchronous Motor(PMSM)is widely used in the MEA field.The PMSM control system of MEA needs to consider the system reliability,and the inverter switching frequency of the inverter is one of the impacting factors.At the same time,the control accuracy of the system also needs to be considered,and the torque ripple and flux ripple are usually considered to be its important indexes.This paper proposes a three-stage series Model Predictive Torque and Flux Control system(three-stage series MPTFC)based on fast optimal voltage vector selection to reduce switching frequency and suppress torque ripple and flux ripple.Firstly,the analytical model of the PMSM is established and the multi-stage series control method is used to reduce the switching frequency.Secondly,selectable voltage vectors are extended from 8 to 26 and a fast selection method for optimal voltage vector sectors is designed based on the hysteresis comparator,which can suppress the torque ripple and flux ripple to improve the control accuracy.Thirdly,a three-stage series control is obtained by expanding the two-stage series control using the P-Q torque decomposition theory.Finally,a model predictive torque and flux control experimental platform is built,and the feasibility and effectiveness of this method are verified through comparison experiments. 展开更多
关键词 Fast optimal voltage vector selection Model predictive control Permanent magnet synchronous motor Ripple suppression Switching frequency
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Koopman-Based Robust Model Predictive Control With Online Identification for Nonlinear Dynamical Systems 认领 引用
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作者 Ruiqi Ke Jingchuan Tang +1 位作者 Zongyu Zuo Yan Shi 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2025年第9期1947-1949,共3页
Dear Editor,This letter presents a novel approach to the data-driven control of unknown nonlinear systems.By leveraging online sparse identification based on the Koopman operator,a high-dimensional linear system model... Dear Editor,This letter presents a novel approach to the data-driven control of unknown nonlinear systems.By leveraging online sparse identification based on the Koopman operator,a high-dimensional linear system model approximating the actual system is obtained online.The upper bound of the discrepancy between the identified model and the actual system is estimated using real-time prediction error,which is then utilized in the design of a tube-based robust model predictive controller.The effectiveness of the proposed approach is validated by numerical simulation. 展开更多
关键词 koopman operatora online identification tube based control real time prediction error online sparse identification identified model Koopman based control robust model predictive control
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Nonlinear Model Predictive Control Based on Support Vector Machine with Multi-kernel 认领 引用 被引量：25
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作者 包哲静 皮道映 孙优贤 《Chinese Journal of Chemical Engineering》 SCIE EI CAS 2007年第5期691-697,共7页
Multi-kernel-based support vector machine （SVM） model structure of nonlinear systems and its specific identification method is proposed, which is composed of a SVM with linear kernel function followed in series by a... Multi-kernel-based support vector machine （SVM） model structure of nonlinear systems and its specific identification method is proposed, which is composed of a SVM with linear kernel function followed in series by a SVM with spline kernel function. With the help of this model, nonlinear model predictive control can be transformed to linear model predictive control, and consequently a unified analytical solution of optimal input of multi-step-ahead predictive control is possible to derive. This algorithm does not require online iterative optimization in order to be suitable for real-time control with less calculation. The simulation results of pH neutralization process and CSTR reactor show the effectiveness and advantages of the presented algorithm. 展开更多
关键词 nonlinear model predictive control support vector machine with multi-kernel nonlinear system identification kernel function
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GFTSM-based Model Predictive Torque Control for PMSM Drive System With Single Phase Current Sensor 认领 引用 被引量：4
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作者 Qingfang Teng Yuxing Jin +2 位作者 Shuyuan Li Jianguo Zhu Youguang Guo 《自动化学报》 EI CAS CSCD 北大核心 2017年第9期1644-1655,共12页
A global fast terminal sliding mode(GFTSM)-based model predictive torque control(MPTC)strategy is developed for permanent magnet synchronous motor(PMSM)drive system with only one phase current sensor.Generally two pha... A global fast terminal sliding mode(GFTSM)-based model predictive torque control(MPTC)strategy is developed for permanent magnet synchronous motor(PMSM)drive system with only one phase current sensor.Generally two phase-current sensors are indispensable for MPTC.In response to only one phase current sensor available and the change of stator resistance,a novel adaptive observer for estimating the remaining two phase currents and time-varying stator resistance is proposed to perform MPTC.Moreover,in view of the variation of system parameters and external disturbance,a new GFTSM-based speed regulator is synthesized to enhance the drive system robustness.In this paper,the GFTSM,based on sliding mode theory,employs the fast terminal sliding mode in both the reaching stage and the sliding stage.The resultant GFTSM-based MPTC PMSM drive system with single phase current sensor has excellent dynamical performance which is very close to the GFTSM-based MPTC PMSM drive system with two-phase current sensors.On the other hand,compared with proportional-integral(PI)-based and sliding mode(SM)-based MPTC PMSM drive systems,it possesses better dynamical response and stronger robustness as well as smaller total harmonic distortion(THD)index of three-phase stator currents in the presence of variation of load torque.The simulation results validate the feasibility and effectiveness of the proposed scheme. 展开更多
关键词 Adaptive observer current sensorless global fast terminal sliding mode(GFTSM) model predictive torque control(MPTC) permanent magnet synchronous motor(PMSM)
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Support vector machine based nonlinear model multi-step-ahead optimizing predictive control 认领 引用 被引量：10
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作者 钟伟民 皮道映 孙优贤 《Journal of Central South University of Technology》 2005年第5期591-595,共5页
A support vector machine with guadratic polynomial kernel function based nonlinear model multi-step-ahead optimizing predictive controller was presented. A support vector machine based predictive model was established... A support vector machine with guadratic polynomial kernel function based nonlinear model multi-step-ahead optimizing predictive controller was presented. A support vector machine based predictive model was established by black-box identification. And a quadratic objective function with receding horizon was selected to obtain the controller output. By solving a nonlinear optimization problem with equality constraint of model output and boundary constraint of controller output using Nelder-Mead simplex direct search method, a sub-optimal control law was achieved in feature space. The effect of the controller was demonstrated on a recognized benchmark problem and a continuous-stirred tank reactor. The simulation results show that the multi-step-ahead predictive controller can be well applied to nonlinear system, with better performance in following reference trajectory and disturbance-rejection. 展开更多
关键词 nonlinear model predictive control support vector machine nonlinear system identification kernel function nonlinear optimization
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Nonlinear model predictive control based on support vector machine and genetic algorithm 认领 引用 被引量：16
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作者 冯凯 卢建刚 陈金水 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2015年第12期2048-2052,共5页
This paper presents a nonlinear model predictive control(NMPC) approach based on support vector machine(SVM) and genetic algorithm(GA) for multiple-input multiple-output(MIMO) nonlinear systems.Individual SVM is used ... This paper presents a nonlinear model predictive control(NMPC) approach based on support vector machine(SVM) and genetic algorithm(GA) for multiple-input multiple-output(MIMO) nonlinear systems.Individual SVM is used to approximate each output of the controlled plant Then the model is used in MPC control scheme to predict the outputs of the controlled plant.The optimal control sequence is calculated using GA with elite preserve strategy.Simulation results of a typical MIMO nonlinear system show that this method has a good ability of set points tracking and disturbance rejection. 展开更多
关键词 Support vector machine Genetic algorithm Nonlinear model predictive control Neural network Modeling
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Robustly stable model predictive control based on parallel support vector machines with linear kernel 认领 引用 被引量：4
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作者 包哲静 钟伟民 +1 位作者 皮道映 孙优贤 《Journal of Central South University of Technology》 2007年第5期701-707,共7页
Robustly stable multi-step-ahead model predictive control (MPC) based on parallel support vector machines (SVMs) with linear kernel was proposed. First, an analytical solution of optimal control laws of parallel SVMs ... Robustly stable multi-step-ahead model predictive control (MPC) based on parallel support vector machines (SVMs) with linear kernel was proposed. First, an analytical solution of optimal control laws of parallel SVMs based MPC was derived, and then the necessary and sufficient stability condition for MPC closed loop was given according to SVM model, and finally a method of judging the discrepancy between SVM model and the actual plant was presented, and consequently the constraint sets, which can guarantee that the stability condition is still robust for model/plant mismatch within some given bounds, were obtained by applying small-gain theorem. Simulation experiments show the proposed stability condition and robust constraint sets can provide a convenient way of adjusting controller parameters to ensure a closed-loop with larger stable margin. 展开更多
关键词 parallel support vector machines model predictive control stability robustness
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Multi-Step Model Predictive Control Based on Online Support Vector Regression Optimized by Multi-Agent Particle Swarm Optimization Algorithm 认领 引用 被引量：2
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作者 TANG Xianlun LIU Nianci +1 位作者 WAN Yali GUO Fei 《Journal of Shanghai Jiaotong university(Science)》 EI 2018年第5期607-612,共6页
As optimization of parameters affects prediction accuracy and generalization ability of support vector regression(SVR) greatly and the predictive model often mismatches nonlinear system model predictive control,a mult... As optimization of parameters affects prediction accuracy and generalization ability of support vector regression(SVR) greatly and the predictive model often mismatches nonlinear system model predictive control,a multi-step model predictive control based on online SVR(OSVR) optimized by multi-agent particle swarm optimization algorithm(MAPSO) is put forward. By integrating the online learning ability of OSVR, the predictive model can self-correct and adapt to the dynamic changes in nonlinear process well. 展开更多
关键词 online support vector regression (OSVR) model predictive controller (MPC) multi-agent particleswarm optimization (MAPSO) nonlinear systems
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Model predictive current control for PMSM driven by three-level inverter based on fractional sliding mode speed observer 认领 引用 被引量：5
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作者 TENG Qing-fang LUO Wei-duo 《Journal of Measurement Science and Instrumentation》 CAS CSCD 2020年第4期358-364,共7页
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 ... 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. 展开更多
关键词 permanent magnet synchronous motor(PMSM) three-level inverter fractional sliding mode speed observer model predictive current control(MPCC)
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Support vector machine-based multi-model predictive control 认领 引用 被引量：3
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作者 Zhejing BAO Youxian SUN 《控制理论与应用（英文版）》 2008年第3期305-310,共6页
In this paper, a support vector machine-based multi-model predictive control is proposed, in which SVM classification combines well with SVM regression. At first, each working environment is modeled by SVM regression ... In this paper, a support vector machine-based multi-model predictive control is proposed, in which SVM classification combines well with SVM regression. At first, each working environment is modeled by SVM regression and the support vector machine network-based model predictive control （SVMN-MPC） algorithm corresponding to each environment is developed, and then a multi-class SVM model is established to recognize multiple operating conditions. As for control, the current environment is identified by the multi-class SVM model and then the corresponding SVMN-MPC controller is activated at each sampling instant. The proposed modeling, switching and controller design is demonstrated in simulation results. 展开更多
关键词 Multi-model predictive control Support vector machine network Multi-class support vector machine Multi-model switching
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Finite Control Set Model Predictive Current Control of a Five-Phase PMSM with Virtual Voltage Vectors and Adaptive Control Set 认领 引用 被引量：11
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作者 Wusen Wang Ying Fan +1 位作者 Siyu Chen Qiushi Zhang 《CES Transactions on Electrical Machines and Systems》 CSCD 2018年第1期136-141,共6页
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 t... 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. 展开更多
关键词 Adaptive control set current ripple finite control set model predictive current control(FCS-MPCC) permanent magnet synchronous motor(PMSM) virtual voltage vectors
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Zero-Sequence Current Suppression Strategy for Open-End Winding Permanent Magnet Synchronous Motor Based on Model Predictive Control 认领 引用
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作者 LIU Huashan LI Jie YAO Fei 《Journal of Donghua University(English Edition)》 CAS 2020年第4期286-292,共7页
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 ... 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. 展开更多
关键词 open-end winding permanent magnet synchronous motor(OW-PMSM) zero-sequence current harmonic model predictive current control common-mode voltage
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SVM with Quadratic Polynomial Kernel Function Based Nonlinear Model One-step-ahead Predictive Control 认领 引用 被引量：17
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作者 钟伟民 何国龙 +1 位作者 皮道映 孙优贤 《Chinese Journal of Chemical Engineering》 SCIE EI CAS 2005年第3期373-379,共7页
A support vector machine (SVM) with quadratic polynomial kernel function based nonlinear model one-step-ahead predictive controller is presented. The SVM based predictive model is established with black-box identifica... A support vector machine (SVM) with quadratic polynomial kernel function based nonlinear model one-step-ahead predictive controller is presented. The SVM based predictive model is established with black-box identification method. By solving a cubic equation in the feature space, an explicit predictive control law is obtained through the predictive control mechanism. The effect of controller is demonstrated on a recognized benchmark problem and on the control of continuous-stirred tank reactor (CSTR). Simulation results show that SVM with quadratic polynomial kernel function based predictive controller can be well applied to nonlinear systems, with good performance in following reference trajectory as well as in disturbance-rejection. 展开更多
关键词 nonlinear model predictive control support vector machine nonlinear system identification kernel function
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Model Predictive Current Control with Adaptive-adjusting Timescales for PMSMs 认领 引用 被引量：20
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作者 Feng Niu Xi Chen +4 位作者 Shaopo Huang Xiaoyan Huang Lijian Wu Kui Li Youtong Fang 《CES Transactions on Electrical Machines and Systems》 CSCD 2021年第2期108-117,共10页
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 t... 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. 展开更多
关键词 Model predictive current control(MPCC) permanent magnet synchronous motor(PMSM) multi-timescale adaptive-adjusting method
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Adaptive Nonlinear Model Predictive Control Using an On-line Support Vector Regression Updating Strategy 认领 引用 被引量：3
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作者 王平 杨朝合 +1 位作者 田学民 黄德先 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2014年第7期774-781,共8页
The performance of data-driven models relies heavily on the amount and quality of training samples, so it might deteriorate significantly in the regions where samples are scarce. The objective of this paper is to deve... The performance of data-driven models relies heavily on the amount and quality of training samples, so it might deteriorate significantly in the regions where samples are scarce. The objective of this paper is to develop an online SVR model updating strategy to track the change in the process characteristics efficiently with affordable computational burden. This is achieved by adding a new sample that violates the Karush–Kuhn–Tucker conditions of the existing SVR model and by deleting the old sample that has the maximum distance with respect to the newly added sample in feature space. The benefits offered by such an updating strategy are exploited to develop an adaptive model-based control scheme, where model updating and control task perform alternately.The effectiveness of the adaptive controller is demonstrated by simulation study on a continuous stirred tank reactor. The results reveal that the adaptive MPC scheme outperforms its non-adaptive counterpart for largemagnitude set point changes and variations in process parameters. 展开更多
关键词 Adaptive control Support vector regression Updating strategy Model predictive control
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Robust Dichotomy Solution-Based Model Predictive Control for the Grid-Connected Inverters with Disturbance Observer 认领 引用 被引量：8
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作者 Huanyue Liao Xin Zhang Zhijun Ma 《CES Transactions on Electrical Machines and Systems》 CSCD 2021年第2期81-89,共9页
This paper proposes a robust dichotomy-based model predictive control(DS-MPC)with a fixed switching frequency for the grid-connected inverter(GCI).The proposed fast dichotomy algorithm can select and deduce the optima... This paper proposes a robust dichotomy-based model predictive control(DS-MPC)with a fixed switching frequency for the grid-connected inverter(GCI).The proposed fast dichotomy algorithm can select and deduce the optimal voltage vector dynamically through the space vector plane.Therefore,the proposed DS-MPC strategy could ensure dynamic performance and steady-state performance as well.Also,the current control robustness can be improved through DS-MPC with disturbance observer(DO)based on the extended Kalman filter(EKF).The novelty of this control is that the current control with fast dynamic response can be realized in the weak grid,even if the grid voltages are greatly distorted.Simulation and hardware experiments on the weak grid validate the effectiveness of the proposed DS-MPC with the EKF observer approach. 展开更多
关键词 Dichotomy solution-based model predictive control(DS-MPC) three-phase grid-connected inverter(GCI) weak grid voltage vector dichotomy
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Simplified Model Predictive Current Control for Dual Three-phase PMSM with Low Computation Burden and Switching Frequency 认领 引用 被引量：1
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作者 Huawei Zhou Xiaolong Xiang +1 位作者 Yibo Li Tao Tao 《CES Transactions on Electrical Machines and Systems》 EI CSCD 2024年第4期447-454,共8页
Finite-control-set model predictive control(FCSMPC)has advantages of multi-objective optimization and easy implementation.To reduce the computational burden and switching frequency,this article proposed a simplified M... Finite-control-set model predictive control(FCSMPC)has advantages of multi-objective optimization and easy implementation.To reduce the computational burden and switching frequency,this article proposed a simplified MPC for dual three-phase permanent magnet synchronous motor(DTPPMSM).The novelty of this method is the decomposition of prediction function and the switching optimization algorithm.Based on the decomposition of prediction function,the current increment vector is obtained,which is employed to select the optimal voltage vector and calculate the duty cycle.Then,the computation burden can be reduced and the current tracking performance can be maintained.Additionally,the switching optimization algorithm was proposed to optimize the voltage vector action sequence,which results in lower switching frequency.Hence,this control strategy can not only reduce the computation burden and switching frequency,but also maintain the steady-state and dynamic performance.The simulation and experimental results are presented to verify the feasibility of the proposed strategy. 展开更多
关键词 Computation time Current increment vector Dual three-phase permanent magnet synchronous motor(DTPPMSM) Model predictive current control(MPCC) Switching frequency
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Model Predictive Control Coupled with Artificial Intelligence for Eddy Current Dynamometers 认领 引用
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作者 İhsan Uluocak Hakan Yavuz 《Computer Systems Science & Engineering》 SCIE EI 2023年第1期221-234,共14页
The recent studies on Artificial Intelligence(AI)accompanied by enhanced computing capabilities supports increasing attention into traditional control methods coupled with AI learning methods in an attempt to bringing... The recent studies on Artificial Intelligence(AI)accompanied by enhanced computing capabilities supports increasing attention into traditional control methods coupled with AI learning methods in an attempt to bringing adap-tiveness and fast responding features.The Model Predictive Control(MPC)tech-nique is a widely used,safe and reliable control method based on constraints.On the other hand,the Eddy Current dynamometers are highly nonlinear braking sys-tems whose performance parameters are related to many processes related vari-ables.This study is based on an adaptive model predictive control that utilizes selected AI methods.The presented approach presents an updated the mathema-tical model of an Eddy Current Dynamometer based on experimentally obtained system operational data.Finally,the comparison of AI methods and related learn-ing performances based on the assessment technique of mean absolute percentage error(MAPE)issues are discussed.The results indicate that Single Hidden Layer Neural Network(SHLNN),General Regression Neural Network(GRNN),Radial Basis Network(RBNN),Neuro Fuzzy Network(ANFIS)coupled MPC have quite satisfying performances.The presented results indicate that,amongst them,GRNN appears to provide the best performance. 展开更多
关键词 Model predictive control eddy current dynamometer artificial intelligence GRNN RBNN ANFIS
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Model Predictive Current Control of Permanent Magnet Synchronous Linear Motor Based on Expanded Control Set 认领 引用
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作者 Qiaoling Yang Huijun Shi +1 位作者 Shunwu Liu Yong Chang 《Chinese Journal of Electrical Engineering》 EI CSCD 2026年第1期333-343,共11页
Finite control set model predictive current control(FCS-MPCC)often induces notable thrust fluctuations and elevated current harmonics in permanent magnet synchronous linear motor(PMSLM)drives.These issues primarily ar... Finite control set model predictive current control(FCS-MPCC)often induces notable thrust fluctuations and elevated current harmonics in permanent magnet synchronous linear motor(PMSLM)drives.These issues primarily arise due to the limited number of available voltage vectors,which compromise steady-state accuracy.To address this problem,a model predictive current control strategy utilizing an expanded control set is proposed.In this approach,virtual voltage vectors are synthesized from the fundamental voltage vectors,expanding the control set to include 38 candidate vectors.Using current prediction equations and a value function,the optimal candidate region is identified by preselecting a central voltage vector,which significantly reduces the number of required optimization searches.The voltage vectors within this region are evaluated at two distinct prediction times.After analyzing the results from both moments,the voltage vector that yields the smallest current prediction error is selected as the optimal control input.A simulation analysis is conducted to validate the effectiveness of the proposed method.The results demonstrate that,compared to conventional FCS-MPCC,the expanded control set approach significantly reduces current harmonics and thrust fluctuations,while also mitigating the increase in switching frequency typically associated with a larger control set. 展开更多
关键词 Permanent magnet synchronous linear motor model predictive current control virtual voltage vector expanded control set
Predictive current control system of PMSM based on LADRC 认领 引用 被引量：5
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作者 Wang Xiaopeng Zhao Jun +1 位作者 Wang Bohui Li Baomin 《Journal of Southeast University(English Edition)》 EI CAS 2022年第3期227-234,共8页
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 ... 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. 展开更多
关键词 permanent magnet synchronous motor(PMSM) two-vector model predictive current control linear active disturbance rejection control speed control system
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