Laboratory Implementation of Direct Torque Controller based Speed Loop Pseudo Derivative Feedforward Controller for PMSM Drive

This paper,evaluate the effectiveness of a proposed speed loop pseudo derivative feedforward(PDFF)controller-based direct torque controller(DTC)for a PMSM drive against the performance of existing PI speed controller-based DTC and hysteresis current controller(HCC).The proposed PDFF-based speed regulator effectively reduces oscillation and overshoot associated with rotor angular speed,electromagnetic torque,and stator current.Two case studies,one using forward-to-reverse motoring operation and the other involving reverse-to-forward braking operation,has been validated to show the effectiveness of the proposed control strategy.The proposed controller's superior performance is demonstrated through experimental verification utilizing an FPGA controller for a 1.5 kW PMSM drive laboratory prototype.

A novel fuzzy logic direct torque controller for a permanent magnet synchronous motor with a field programmable gate array

A high-performance digital servo system built on the platform of a field programmable gate array (FPGA),a fully digitized hardware design scheme of a direct torque control (DTC) and a low speed permanent magnet synchronous motor (PMSM) is proposed. The DTC strategy of PMSM is described with Verilog hardware description language and is employed on-chip FPGA in accordance with the electronic design automation design methodology. Due to large torque ripples in low speed PMSM,the hysteresis controller in a conventional PMSM DTC was replaced by a fuzzy controller. This FPGA scheme integrates the direct torque controller strategy,the time speed measurement algorithm,the fuzzy regulating technique and the space vector pulse width modulation principle. Experimental results indicate the fuzzy controller can provide a controllable speed at 20 r min-1 and torque at 330 N m with satisfactory dynamic and static performance. Furthermore,the results show that this new control strategy decreases the torque ripple drastically and enhances control performance.

Genetic algorithm and particle swarm optimization tuned fuzzy PID controller on direct torque control of dual star induction motor

This study presents analysis, control and comparison of three hybrid approaches for the direct torque control (DTC) of the dual star induction motor (DSIM) drive. Its objective consists of combining three different heuristic optimization techniques including PID-PSO, Fuzzy-PSO and GA-PSO to improve the DSIM speed controlled loop behavior. The GA and PSO algorithms are developed and implemented into MATLAB. As a result, fuzzy-PSO is the most appropriate scheme. The main performance of fuzzy-PSO is reducing high torque ripples, improving rise time and avoiding disturbances that affect the drive performance.

Direct Torque Control System and Sensorless Technique of Permanent Magnet Synchronous Motor

The direct torque control theory has achieved great success in the control ofinduction motors. However, in the DTC drive system of Permanent Magnet Synchronous Machine (PMSM)proposed a few years ago, there are many basic theoretical problems that must be clarified. Thispaper describes an investigation about the effect of the zero voltage space vectors in the DTCsystem of PMSM and points out that if using the zero voltage space vectors rationally, not only canthe DTC system be driven successfully but also the torque ripple is reduced and the performance ofthe system is improved. This paper also studies the sensorless technique in the DTC system of PMSMand configures the DTC system of PMSM with sensorless technique including zero voltage spacevectors. Numerical simulations and experimental tests have proved the theory correct. In thecondition of sensor-less, the DTC system of PMSM is wide-rangely speed adjusting, and the ratio ofspeed adjustment is 1: 100.

Application of neural networks for permanent magnet synchronous motor direct torque control

Neural networks require a lot of training to understand the model of a plant or a process. Issues such as learning speed, stability, and weight convergence remain as areas of research and comparison of many training algorithms. The application of neural networks to control interior permanent magnet synchronous motor using direct torque control （DTC） is discussed. A neural network is used to emulate the state selector of the DTC. The neural networks used are the back-propagation and radial basis function. To reduce the training patterns and increase the execution speed of the training process, the inputs of switching table are converted to digital signals, i.e., one bit represent the flux error, one bit the torque error, and three bits the region of stator flux. Computer simulations of the motor and neural-network system using the two approaches are presented and compared. Discussions about the back-propagation and radial basis function as the most promising training techniques are presented, giving its advantages and disadvantages. The system using back-propagation and radial basis function networks controller has quick parallel speed and high torque response.

Model Predictive Control-Based Direct Torque Control for Matrix Converter-Fed Induction Motor with Reduced Torque Ripple

To reduce the torque ripple in motors resulting from the use of conventional direct torque control(DTC),a model predictive control(MPC)-based DTC strategy for a direct matrix converter-fed induction motor is proposed in this paper.Two new look-up tables are proposed,these are derived on the basis of the control of the electromagnetic torque and stator flux using all the feasible voltage vectors and their associated switching states.Finite control set model predictive control(FCS-MPC)has then been adopted to select the optimal switching state that minimizes the cost function related to the electromagnetic torque.Finally,the experimental results are shown to verify the reduced torque ripple performance of the proposed MPC-based DTC method.

A Novel Fuzzy Direct Torque Control System for Three-level Inverter-fed Induction Machine

Diode clamped multi-level inverter （DCMLI） has a wide application prospect in high-voltage and adjustable speed drive systems due to its low stress on switching devices, low harmonic output, and simple structure. However, the problem of complexity of selecting vectors and capacitor voltage unbalance needs to be solved when the algorithm of direct torque control （DTC） is implemented on DCMLI. In this paper, a fuzzy DTC system of an induction machine fed by a three-level neutral-point-clamped （NPC） inverter is proposed. After introducing fuzzy logic, optimal selecting switching state is realized by applying various strategies which can distinguish the grade of the errors of stator flux linkage, torque, the neutral-point potential, and the position of stator flux linkage. Consequently, the neutral-point potential unbalance, the dr/dr of output voltage and the switching loss are restrained effectively, and desirable dynamic and steady-state performances of induction machines can be obtained for the DTC scheme. A design method of the fuzzy controller is introduced in detail, and the relevant simulation and experimental results have verified the feasibility of the proposed control algorithm.

Fuzzy-second order sliding mode control optimized by genetic algorithm applied in direct torque control of dual star induction motor

The direct torque control of the dual star induction motor(DTC-DSIM) using conventional PI controllers is characterized by unsatisfactory performance, such as high ripples of torque and flux, and sensitivity to parametric variations. Among the most evoked control strategies adopted in this field to overcome these drawbacks presented in classical drive, it is worth mentioning the use of the second order sliding mode control(SOSMC) based on the super twisting algorithm(STA) combined with the fuzzy logic control(FSOSMC). In order to realize the optimal control performance, the FSOSMC parameters are adjusted using an optimization algorithm based on the genetic algorithm(GA). The performances of the envisaged control scheme, called G-FSOSMC, are investigated against G-SOSMC, G-PI and BBO-FSOSMC algorithms. The proposed controller scheme is efficient in reducing the torque and flux ripples, and successfully suppresses chattering. The effects of parametric uncertainties do not affect system performance.

Simplified EKF Based Sensorless Direct Torque Control of Permanent Magnet Brushless AC Drives

A simplified extended Kalman filter (EKF) based sensorless direct torque control technique for a permanent magnet brushless AC drive is proposed. Its performance is compared with that obtained with other sensorless methods for estimating the rotor speed and position from a stator flux-linkage. Since the EKF has an inherently adaptive filtering capability and does not introduce phase delay, the technique provides better speed estimates. In addition, the technique is easy to implement and requires minimal computation.

Application of direct torque control to electric screw presses for speeding up torque response and reducing starting current

Fast response and stable torque output are crucial to the performance of electric screw presses. This paper describes the design of a direct torque control （DTC） system for speeding up torque response and reducing the starting current of electric screw presses and its application to the J58K series of numerical control electric screw presses with a dual-motor drive. The DTC drive system encompasses speed control, torque reference control, and switching frequency control. Comparison of the DTC dual-AC induction motor drive with corresponding AC servo motor drive showed that for the J58K-315 electric screw press, the DTC drive system attains a higher maximum speed （786 r/min） within a shorter time （1.13 s） during a 250 nun stroke and undergoes smaller rise in temperature （42.0 ℃） in the motor after running for 2 h at a 12 min-1 strike frequency than the AC servo motor drive does （751 r/min within 1.19 s, and 50.6 ℃ rise）. Moreover, the DTC AC induction motor drive, with no need for a tachometer or position encoder to feed back the speed or position of the motor shaft, enjoys increased reliability in a strong-shock work environment.

Research on Direct Torque Control of Permanent Magnet Synchronous Motor for New Energy Vehicles

This article introduces the control principle,technical status and two commonly used motor control schemes of permanent magnet synchronous motors for new energy vehicles.Direct torque control is selected as the research object,and its advantages and disadvantages with vector control are analyzed.A Simulink simulation model was established according to the control principle.

Research on Direct Torque Control System Based on Induction Motor

The mathematic model of direct torque control (DTC) was deduced. Two simulating models based on the MATLAB & SIMULINK were established. The emphasis is focused on study of the performance difference of the DTC system with stator flux hexagon and circle trajectories. The simulation waveforms of flux, torque and current characters with two flux trajectories were given. Experiments were carried out in an AC drive system based on induction motor and two-level inverter. A dual-CPU structure was used and the communication with two CPUs was obtained by a dual-port RAM in this system.

Novel torque ripple minimization algorithm for direct torque control of induction motor drive

To elucidate the principles of notable torque and flux ripple during the steady state of the conventional direct torque control （DTC） of induction machines, the factors of influence torque variation are examined. A new torque ripple minimization algorithm is proposed. The novel method eradicated the torque ripple by imposing the required stator voltage vector in each control cycle. The M and T axial components of the stator voltage are accomplished by measuring the stator flux error and the expected incremental value of the torque at every sampling time. The maximum angle rotation allowed is obtained. Experimental results showed that the proposed method combined with the space vector pulse width modulation （SVPWM） could be implemented in most existing digital drive controllers, offering high performance in both steady and transient states of the induction drives at full speed range. The result of the present work implies that torque fluctuation could be eliminated by imposing proper stator voltage, and the proposed scheme could not only maintain constant switching frequency for the inverter, but also solve the heating problem and current harmonics in traditional induction motor drives.

A novel speed sensor-less direct torque control system for mining locomotive haulage

A novel speed sensor-less direct torque control induction motor drive system for the mining locomotive haulage is presented in the paper. Rotor speed identification is based on the model reference adaptive control theory with neural network using back propagation algorithm. The system is implemented using a real-time TMS320F240 digital signal processor. The simulation study and experiment results indicate that the suggested system has good performance.

An Observing Method for Flux and Speed with Direct Torque Control

An observing method for stator flux and rotor flux is presented. Based on the proposed flux observing method, a novel speed estimator has been designed. At last, the speed estimator combined with the flux observing is applied in the direct torque control system without speed sensor. The simulation results show that these methods can improve the accuracy of speed observing and the low speed performance of direct torque control system, and strengthen the robustness of system.

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).

A Novel Multilevel Inverter Circuit for the Performance Enhancement of Direct Torque Controlled Induction Motor

Induction motor is the most sought after motor in the industry for excellent performance characteristics and robustness. Developments in the Power Electronic circuitry have revolutionised the induction motor industry leading to the developments in various control strategies and circuits for motor control. Direct Torque Control (DTC) is one of the excellent control strategies preferred by industries for controlling the torque and flux in an induction machine. The main drawback of DTC is the presence of torque ripple which is slightly more than the acceptable limit. There are various parameters that introduce ripples in the electromagnetic torque, one of them being the type of inverter circuit. There are various types of inverter circuits available and the effect of each of them in the production of torque ripple is different. This work is an attempt to identify the influence of various multilevel inverter circuits on the torque ripple level and to propose the best inverter circuit. The influence of multilevel diode clamped inverter and cascaded H bridge inverter circuits on torque ripple minimization, is analysed using simulation studies for identifying the most suitable multilevel inverter circuit which gives minimum torque ripple. The results obtained from the simulation studies are validated by hardware implementation on 0.75 kW induction motor.

An Improved Proportional Integral Estimator of the Stator Resistance for a Direct Torque Controlled Induction Motor

In this paper, an improved PI （proportional integral） stator resistance estimation for a DTC （direct torque controlled） induction motor is proposed. This estimation method is based on an on-line stator resistance correction regarding the variations of the stator current estimation error. In fact, the input variable of the P1 estimator is the stator current estimation error. The main idea is to tune accurately the stator resistance value relatively to the evolution of the stator current estimation error gradient to avoid the drive instability and ensure the tracking of the actual value of the stator resistance. But there is an unavoidable steady state error between the filtered stator current modulus and its estimated value from the dq model of the machine which is due to pseudo random commutations of the inverter switches. This may deteriorate the performance of the proposed fuzzy stator resistance estimator. An offset has been introduced in order to overcome this problem, for different speed command values and load torques. Simulation results show that the proposed estimator was able to successfully track the actual value of the stator resistance lbr different operating conditions.

A New Scheme to Direct Torque Control of Interior Permanent Magnet Synchronous Machine Drives for Constant Inverter Switching Frequency and Low Torque Ripple

DTC （direct torque control） can produce quick and robust response, but it has the problems of large torque ripples and inconstant inverter switching frequency. This paper introduces a modified direct torque control based on the SVM （space vector modulation） for IPMSM （interior permanent magnet synchronous motor） drive. Two PI （proportional-integral） controllers regulate the flux and torque, respectively, and the inverter is controlled by the SVM technique in the proposed DTC system. Simulation results show that the performance of the proposed DTC system has been improved with respect to the conventional DTC. The DTC system can effectively reduce the flux and torque ripples.

Comparative Study of the DTC-IM Speed Controller Based on Artificial Intelligence

Recently, artificial intelligence technique is increasingly receiving attention in solving complex and practical problem and they are widely applying in electrical machine domain. The authors consider also the direct torque control （DTC） as an alternative to conventional methods of control by pulse width modulation （PWM） and by Field oriented control （FOC）, so the application of the DTC based on artificial intelligence can show more advantages and simplified control algorithms with high performance. For this reason, the objectives of this paper can be divided into two parts, the first part is to apply neural networks and fuzzy logic techniques to the DTC control in the presence of a loop speed control comparing to the conventional regulators （as PI） to show the feasibility of these approaches, the second part is to further improve the performance of the neural network by using a neural-fuzzy regulator which combine the advantages of two techniques. Simulation results confirm the validity of the proposed techniques.