Finite Control Set Model Predictive Torque Control Using Sliding Model Control for Induction Motors

Finite control set model predictive torque control(FCS-MPTC)has become increasingly prevalent for induction motors(IM)owing to its simple concept,easy incorporation of constraints and strong flexibility.In traditional FCS-MPTC speed controller design,a classical proportional integral(PI)controller is typically chosen to generate the torque reference.However,the PI controller is dependent on system parameters and sensitive to the load torque variation,which seriously affects control performance.In this paper,a model predictive torque control using sliding mode control(MPTC+SMC)for IM is proposed to enhance the robust performance of the drive system.First,the influence of the parameter mismatches for FCS-MPTC is analyzed.Second,the shortcomings of traditional PI controller are derived.Then,the proposed MPTC+SMC method is designed,and the MPTC+PI and MPTC+SMC are compared theoretically.Finally,experimental results demonstrate the correctness and effectiveness of the proposed MPTC+SMC.In comparison with MPTC+PI,MPTC+SMC has the better dynamic performance and stronger robust performance against parameter variations and load disturbance.

Model predictive torque control of permanent magnet synchronous motor system driven by matrix converter

Employing matrix converter （MC） as driving mode, the strategy of model predictive torque control （MPTC） is proposed for three phase permanent magnet synchronous motor （PMSM） system. MC is applied instead of conventional AC DC AC converter to increase the power factor （PF） of the system input side. MPTC is used to select optimal voltage space vector to enable the system to have satisfactory torque and flux control effect. The resultant MPTC strategy not only makes the MC fed PMSM system operate reliably and have perfect control performance, but also makes the PF of the system input side be 1. Compared with direct torque control （DTC）, the proposed MPTC strategy guarantees that MC fed PMSM has better command following characteristics in the presence of variation of load torque and tracking reference speed. Simulation results verify the feasibility and effectiveness of the proposed strategy.

Model Predictive Torque Control for a Dual Three-phase PMSM Using Modified Dual Virtual Vector Modulation Method

Single voltage vectors applied in the conventional model predictive torque control(MPTC)for multiphase motors do not only suffer from serious torque and stator flux ripples but also cause the large harmonic current.To address the aforementioned challenges,an MPTC using a modified dual virtual vector modulation method is proposed to improve the operational performance of a dual three-phase permanent magnet synchronous motor.Virtual voltage vectors are synthesized as the candidate control set to restrain the harmonic current.A transformation method is introduced to consider both the stator flux and torque in the duty cycle modulation.The torque and stator flux ripples are simultaneously reduced by addressing the limitations of nonuniform units.Furthermore,the null voltage vector is then inserted to expand the modulation range and improve the steady-state performance.Moreover,the sawtooth carrier is adopted to address the challenge of the asymmetric switch sequence caused by the modified modulation.Finally,the experimental results are presented to verify the effectiveness and superiority of the proposed MPTC method.

Model Predictive Direct Torque Control of Permanent Magnet Synchronous Motor (PMSM) with Online Parameter Estimation Based on Extended Kalman Filter

Aiming at the torque and flux ripples in the direct torque control and the time-varying parameters for permanent magnet synchronous motor (PMSM), a model predictive direct torque control with online parameter estimation based on the extended Kalman filter for PMSM is designed. By predicting the errors of torque and flux based on the model and the current states of the system, the optimal voltage vector is selected to minimize the error of torque and flux. The stator resistance and inductance are estimated online via EKF to reduce the effect of model error and the current estimation can reduce the error caused by measurement noise. The stability of the EKF is proved in theory. The simulation experiment results show the method can estimate the motor parameters, reduce the torque, and flux ripples and improve the performance of direct torque control for permanent magnet synchronous motor (PMSM).

Simulation on model predictive control for PMSM drive system based on double extended state observer

A novel double extended state observer(DESO)based on model predictive torque control(MPTC)strategy is developed for three-phase permanent magnet synchronous motor(PMSM)drive system without current sensor.In general,to achieve high-precision control,two-phase current sensors are necessary for successful implementation of MPTC.For this purpose,two ESOs are used to estimate q-axis current and stator resistance respectively,and then based on this,d-axis current is estimated.Moreover,to reduce torque and flux ripple and to improve the performance of the torque and speed,MPTC strategy is designed.The simulation results validate the feasibility and effectiveness of the proposed scheme.

A real-time prediction method for tunnel boring machine cutter-head torque using bidirectional long short-term memory networks optimized by multi-algorithm

Based on data from the Jilin Water Diversion Tunnels from the Songhua River(China),an improved and real-time prediction method optimized by multi-algorithm for tunnel boring machine(TBM)cutter-head torque is presented.Firstly,a function excluding invalid and abnormal data is established to distinguish TBM operating state,and a feature selection method based on the SelectKBest algorithm is proposed.Accordingly,ten features that are most closely related to the cutter-head torque are selected as input variables,which,in descending order of influence,include the sum of motor torque,cutter-head power,sum of motor power,sum of motor current,advance rate,cutter-head pressure,total thrust force,penetration rate,cutter-head rotational velocity,and field penetration index.Secondly,a real-time cutterhead torque prediction model’s structure is developed,based on the bidirectional long short-term memory(BLSTM)network integrating the dropout algorithm to prevent overfitting.Then,an algorithm to optimize hyperparameters of model based on Bayesian and cross-validation is proposed.Early stopping and checkpoint algorithms are integrated to optimize the training process.Finally,a BLSTMbased real-time cutter-head torque prediction model is developed,which fully utilizes the previous time-series tunneling information.The mean absolute percentage error(MAPE)of the model in the verification section is 7.3%,implying that the presented model is suitable for real-time cutter-head torque prediction.Furthermore,an incremental learning method based on the above base model is introduced to improve the adaptability of the model during the TBM tunneling.Comparison of the prediction performance between the base and incremental learning models in the same tunneling section shows that:(1)the MAPE of the predicted results of the BLSTM-based real-time cutter-head torque prediction model remains below 10%,and both the coefficient of determination(R^(2))and correlation coefficient(r)between measured and predicted values exceed 0.95;and(2)the incremental learning method is suitable for realtime cutter-head torque prediction and can effectively improve the prediction accuracy and generalization capacity of the model during the excavation process.

Real-time analysis and prediction of shield cutterhead torque using optimized gated recurrent unit neural network

An accurate prediction of earth pressure balance(EPB)shield moving performance is important to ensure the safety tunnel excavation.A hybrid model is developed based on the particle swarm optimization(PSO)and gated recurrent unit(GRU)neural network.PSO is utilized to assign the optimal hyperparameters of GRU neural network.There are mainly four steps:data collection and processing,hybrid model establishment,model performance evaluation and correlation analysis.The developed model provides an alternative to tackle with time-series data of tunnel project.Apart from that,a novel framework about model application is performed to provide guidelines in practice.A tunnel project is utilized to evaluate the performance of proposed hybrid model.Results indicate that geological and construction variables are significant to the model performance.Correlation analysis shows that construction variables(main thrust and foam liquid volume)display the highest correlation with the cutterhead torque(CHT).This work provides a feasible and applicable alternative way to estimate the performance of shield tunneling.

Prediction of Commuter Vehicle Demand Torque Based on Historical Speed Information

The development of vehicle-to-everything and cloud computing has brought new opportunities and challenges to the automobile industry.In this paper,a commuter vehicle demand torque prediction method based on historical vehicle speed information is proposed,which uses machine learning to predict and analyze vehicle demand torque.Firstly,the big data of vehicle driving is collected,and the driving data is cleaned and features extracted based on road information.Then,the vehicle longitudinal driving dynamics model is established.Next,the vehicle simulation simulator is established based on the longitudinal driving dynamics model of the vehicle,and the driving torque of the vehicle is obtained.Finally,the travel is divided into several accelerationcruise-deceleration road pairs for analysis,and the vehicle demand torque is predicted by BP neural network and Gaussian process regression.

Speed sensorless FCS-MPTC based on FOSM-MRAS five-phase permanent magnet synchronous motor

For the two-level five-phase permanent magnet synchronous motor(FP-PMSM)drive system,an improved finite-control-set model predictive torque control(MPTC)strategy is adopted to reduce torque ripple and improve the control performance of the system.The mathematical model of model reference adaptive system(MRAS)of FP-PMSM is derived and a method based on fractional order sliding mode(FOSM)is proposed to construct the model reference adaptive system(FOSMMRAS)to improve the motor speed estimation accuracy and eliminate the sliding mode integral saturation effect.The simulation results show that the FP-PMSM speed sensorless FCS-MPTC system based on FOSM-MRAS has strong robustness,good dynamic performance and static performance,and high reliability.

A novel MPTC sensorless control strategy for ANFTSMC with ESO to control PMSM

Aiming at the problem that the traditional control strategy of permanent magnet synchronous motor(PMSM)for electric vehicles has low control performance,a novel adaptive non-singular fast terminal sliding mode control(ANFTSMC)model predictive torque control(MPTC)strategy is proposed.A new adaptive exponential approach rate is designed,and the traditional switching function sgn()is replaced by the hyperbolic tangent function tanh().A new ANFTSMC with extended state observer(ESO)is constructed as the speed regulator of the system,and ESO can observe disturbances.This improved method weakens chattering and improves the robustness of the system.To realize sensorless control of the speed control system,an ESO speed observer based on tanh(Fal)is constructed.Compared with the traditional ESO based on Fal function,the observation error is smaller,and the observation accuracy is higher.Finally,aiming at the model predictive torque control strategy used,a new objective function construction method is proposed,which avoids the design of weight coefficient,and the traditional voltage vector selection method is improved and optimized,which reduces the calculation amount of the algorithm.

Anti-Windup Control Strategy of Drive System for Humanoid Robot Arm Joint

To address the problems of torque limit and controller saturation in the control of robot arm joint,an anti-windup control strategy is proposed for a humanoid robot arm,which is based on the integral state prediction under the direct torque control system of brushless DC motor. First,the arm joint of the humanoid robot is modelled. Then the speed controller model and the influence of the initial value of the integral element on the system are analyzed. On the basis of the traditional antiwindup controller,an integral state estimator is set up. Under the condition of different load torques and the given speed,the integral steady-state value is estimated. Therefore the accumulation of the speed error terminates when the integrator reaches saturation. Then the predicted integral steady-state value is used as the initial value of the regulator to enter the linear region to make the system achieve the purpose of anti-windup. The simulation results demonstrate that the control strategy for the humanoid robot arm joint based on integral state prediction can play the role of anti-windup and suppress the overshoot of the system effectively. The system has a good dynamic performance.

A novel control method for turboshaft engine with variable rotor speed based on the Ngdot estimator through LQG/LTR and rotor predicted torque feedforward

In order to compensate for the disturbance of wide variation in rotor demanded torque on power turbine speed and realize the fast response control of turboshaft engine during variable rotor speed,a cascade PID control method based on the acceleration estimator of gas turbine speed(Ngdot)and rotor predicted torque feedforward is proposed.Firstly,a two-speed Dual Clutch Transmission(DCT)model is applied in the integrated rotor/turboshaft engine system to achieve variable rotor speed.Then,an online estimation method of Ngdot based on the Linear Quadratic Gaussian with Loop Transfer Recovery(LQG/LTR)is proposed for power turbine speed cascade control.Finally,according to the cascade PID controller based on Ngdot estimator,a rotor demanded torque predicted method based on the Min-batch Gradient Descent-Neural Network(MGD-NN)is put forward to compromise the influence of rotor torque interference.The simulation results show that compared with cascade PID controller based on Ngdot estimator and the one combined with collective pitch feedforward control,the novel control method proposed can reduce the overshoot of power turbine speed by more than 20%,which possesses faster response,superior dynamic effect and satisfactory robustness performance.The control method proposed can realize the fast response control of turboshaft engine with variable rotor speed better.