hysteresis regulators. The first one is to control the flux and the other to control the torque. The use of fuzzy controllers permits a faster response and greater robustness. As an intelligent method, fuzzycontrol does not need an accurate mathematic model of the process to be controlled, and it uses the experience of people’s knowledge to form its control rule base. A fuzzylogic controller is used to select the voltage vectors in a conventional DTC in . For the duty ratio control method, a fuzzylogic controller is used to determine the duration of the output voltage vector at each sampling period . These fuzzylogic controllers can provide good dynamic performance and robustness. A fuzzy adaptive controller was also used to reduce torque ripples . In this method the duty ratio of the vectors was calculated based on fuzzy estimators and can effectively reduce the torque ripples. However, it cannot have a constant frequency. A significant improvement in the steady state performance was reported. Some of the different solutions proposed include DTC with SVM, different power converter topologies, such as multi-level inverters , , a matrix converter , sensor-less methods , , optimum statorflux estimators for high speed operation , , and artificial intelligence techniques, such as fuzzylogic and neuro-controllers . Directtorquecontrol consists of a pair of hysteresis comparators, torque and flux calculators, a lookup table, and a voltage-source inverter (VSI) . However, major problems usually associated with this drive are a switching frequency that varies with the operating conditions, a hightorque and flux ripples with current distortion.
Over the years directtorquecontrol (DTC) of induction motor emerged as an alternative to field oriented control of induction motor . DTC is employed for highperformance and quick response drives .Compared to field oriented control, DTC has following advantages like (a) simple and quick response control, (b) absence of co-ordinate transformation and current controllers, (c) PI controllers in Flux and torquecontrol loops[3-4]. The conventional DTC (CDTC) suffers from major disadvantages like (a) hightorque and flux ripples, (b) accurate estimation of torque and flux, (c) sluggish speed response during low speed and sudden change in torque command and (d) variable switching frequency [3-5]. Over the last two decades several solutions are proposed by researches to improve CDTC. Few researches proposed improvements in CDTC by employing multilevel inverters [6-8], but multi level inverters results in high switching losses. Few developed DTC with variable gain hysteresis bands or by replacing hysteresis band with constant switching controllers [9-10]. CDTC is also improved by spacevectormodulation and discrete spacevectormodulation techniques as given in [11- 13] but in these methods accurate design of torque and flux loop PI controllers is required. The use of artificial intelligent techniques like neural networks, fuzzylogic for improvements in CDTC gained more importance in recent years. In order to improve CDTC few researchers did works on replacing conventional torque and speed PI controllers with fuzzy, neuro-fuzzy (ANFIS), sliding mode fuzzy and neural
The control scheme for PMSM includes director control and vectorcontrol out of which directtorquecontrol is popular. DirectTorqueControl (DTC) method has been first proposed and applied for induction machines in the mid- 1980’s as reported in . This concept can also be applied to synchronous drives . Indeed, in the late 1990s, DTC techniques for the interior permanent magnet synchronous machine appeared, as reported in .Permanent magnet (PM) synchronous motors are widely used in high-performance drives such as industrial robots and machine tools to their advantages as: high efficiency, high power density, hightorque/inertia ratio, and free maintenance. In recent years, the magnetic and thermal capabilities of the PM have been considerably increased by employing the high coercive PM material . For some applications, the DTC becomes unusable, despite it significantly improves the dynamic performance of the drive compared to the vectorcontrol due to torque and flux ripples. Indeed, hysteresis controllers used in the conventional structure of the DTC generates a variable switching frequency, causing electromagnetic torque oscillations , this frequency is also varying with speed, load torque and hysteresis bands selected . In addition, a high sampling frequency needed for digital implementation of hysteresis comparators and a current and torque distortion caused by sectors changes . Several contributions have been proposed to overcome these problems, by using a multilevel inverter: more voltage space vectors available to control the flux and torque. However, more power switches are needed to achieve a lower ripple and almost fixed switching frequency, which increases the system cost and complexity -. In  and , two structures of modified DTC have been proposed to improve classical DTC performances by replacing the hysteresis controllers and the commutation table by a PI regulator, predictive controller and SpaceVectorModulation (SVM). In this paper, a modified DTC algorithm with fixed switching frequency for PMSM is proposed to reduce the flux and torque ripples. It is an extension of the modified DTC scheme for the PMSM proposed by the authors in . The performance of the basic DTC and the proposed DTC scheme is analyzed by modeling and simulation using MATLAB.
Induction motor drives using field oriented control (FOC) for torque and fluxcontrol have been used in highperformance industrial applications instead of dc motors for many years. In FOC, torque and flux of an induction motor can be controlled independently by decoupling the stator current into its orthogonal components. The FOC method has achieved a quick torque response. But in order to achieve expected performancefrom FOC, exact identification of parameters is required. A new torque and fluxcontrol scheme called the directtorquecontrol (DTC) has been introduced for inductionmotors. In DTC the torque and flux of an induction motor can be controlled directly by applying a suitable voltage vector to the stator of an induction motor. However, convectional DTC result in large torque and flux ripples. In this paper, a controller based on fuzzylogic is designed to improve the performance of DTC and reduce the torque and flux ripple.
Abstract — Directtorquecontrol (DTC) is a new method of induction motor control. The key issue of the DTC is the strategy of selecting proper stator voltage vectors to force statorflux and developed torque within a prescribed band. Due to the nature of hysteresis control adopted in DTC, there is no difference in control action between a larger torque error and a small one. It is better to divide the torque error into different intervals and give different control voltages for each of them. To deal with this issue a fuzzy controller has been introduced. But, because the number of rules is too high some problems arise and the speed of fuzzy reasoning will be affected. In this paper, a comparison between a new fuzzydirect-torquecontrol (DTFC) with spacevectormodulation (SVM) is made. The principle and a tuning procedure of the fuzzydirecttorquecontrol scheme are discussed. The simulation results, which illustrate the performance of the proposed control scheme in comparison with the fuzzy hysteresis connected of DTC scheme are given.
By using an input-output feedback linearization control, the inverter reference voltage is obtained. Also a full-order adaptive stator flu x observer is designed and a new speed adaptive law is given. Thus the stability of the observer system is ensured . S. A. Zaid  suggested a decoupled control of amplitude and statorflux angle to generate the pulses of voltage source inverter. MATLAB/SIMULINK software simulates the suggested and conventional DTC. The use of SVM enables fast speed and torque responses. Variations of motor parameter do not affect the optimization in the new method. M. sathish Kumar presents the comparative evaluation of the two popular control strategies for induction motor drive. These strategies are classical DTC and DTC-SVM. The Simu-link mode l of both classical and SVPWM directtorquecontrol drives are simulated in all the four quadrant of operation) and the results are analyzed .A LNASIR Z. A. presents the design of a directtorquecontrol model and tested using MATLAB/SIMULINK package. Simulation results illustrate the validity & high accuracy of the proposed model . A new torque ripple reduction scheme is proposed with a modified look up table. This table including a large no. of synthesized non - zero active voltage vector to overcome the limitation of the conventional strategy and duty ratio control switching strategy . The DT C principle is based upon the decoupling of torque and stator flu x. directtorquecontrol method employees hysteresis comparator which produces high ripples in torque and switching frequency is variable. The proposed DTC- SVM scheme reduces torque ripples and preserves the DTC transient merits. The SVM technique is utilized to obtain the required voltage spacevector which compensates the flu x and torque errors, at each cycle period  .
The induction motor is most widely because of its high reliability, robust in operations, relatively low cost and modest maintenance requirements. But they require much more complex methods of control, more expensive and higher rated power converters than DC and permanent magnet machines. Three phase induction motor is widely used in industrial drive because they are reliable and rugged. Single phase inductionmotors are widely used for heavier loads for example in fans in household appliances. The fix speed service, inductionmotors are being increased with variable frequency drives. Induction motor achieves a quick torque response, and has been applied in various industrial applications instead of dc motors. It permits independent control of the torque and flux by decoupling the stator current into two orthogonal components FOC (Field Oriented Control). However it is very sensitive to flux, which is mainly affected by parameter variations. It depends on accurate parameter identification to achieve the expected performance. The vectorcontrol of IM drive for speed control is mainly classified into two types such as field oriented control (FOC) and directtorquecontrol (DTC). In FOC, the speed of the induction motor is controlled like a separately excited dc-motor with more transformations and complexity involved in the system. In order to control the induction motor speed in simple way without required any transformations the DTC is used. In the middle of 1980 directtorquecontrol was developed by Takahashi and Depenbrock as an alternative to field oriented control to overcome its problems. Directtorquecontrol is derived from the fact that on the basis of the errors between the reference and the estimated values of torque and flux it is possible to directly control the inverter states in order to reduce the torque and flux errors within the prefixed band limits. Directtorquecontrol is a strategy research for induction motor speed adjustment feeding by variable frequency converter. It controls torque on the base of keeping the flux value invariable by choosing voltage spacevector.
Takahashi and Noguchi. Directtorquecontrol (DTC)drives are finding great interest, since ABB recently introduced the first industrial direct-torque- controlled induction motordrive in the mid-1980’s, which can work even at zero speed. This is a very significant industrial contribution.Conventional directtorque controlled inductionmotors are utilized hysteresis controller to compensate the flux and torqueerrors. Due to the use of flu x and torque hysteresis controller, conventional DTC suffers fro m hightorque ripples and alsoswitching frequency is variable. To overco me the disadvantages of conventional DTC, several techniques have beendeveloped. One of them is the directtorquecontrolusingspacevectormodulation (DTC-SVM ). Spacevectormodulation isan algorithm wh ich is used to calculate the required voltage spacevector to compensate the flu x and torque ripples. SVMtechnique is based on the switching between two adjacent boundaries of a zero vector and active vectors. SVM techniqueshave several advantages such as, lower torque ripple, lower switching losses. Also lower Total Harmonic Distortion (THD)in the current, and easier to implement in the dig ital systems.In this paper, SVM-DTC technique with PIcontroller for induction machine drives is developed.Furthermore, a robust full-order speed adaptivestator flu x observer is designed for a speed sensorless DTC-SVM system and a speed-adaptive law isgiven. The observer gain matrix, which is obtainedby solving linear matrix inequality, can improve therobustness of the adaptive observer gain in . Thestability of the speed adaptive stator flu x observer isalso guaranteed by the gain matrix in very lowspeed. The proposed control algorith ms are verifiedby extensive simulation results.
The figure summarizes the essential features of DTC control. Basically, the control is accomplished by simple but advanced scalar control of torque and statorflux by hysteresis-band feedback loops. There is no feedback current control although current sensors are essential for protection. Note that no traditional SPWM or SVM technique is used as in other drives. The indirect PWM control is due to voltage vector selection from the look- up table to constrain the flux within the hysteresis band. Similar to hysteresis band (HB) current control, there will be ripple in current, flux, and torque. The current ripple will give additional harmonic loss, and torque ripple will try to induce speed ripple in a low inertia system. In recent years, the simple HB-based DTC control has been modified by fuzzy and neuro-fuzzycontrol in inner loops with SVM control of the inverter. Multiple inverter vector selection in SVM within a sample time smoothes current, flux, and torque. However, with the added complexity, the simplicity of DTC control is lost. DTC control can be applied to PM synchronous motor drives also.
This paper describes a mix of directtorquecontrol (DTC) and spacevectormodulation (SVM) for a customizable speed sensor less induction motor (IM) drive. The motor drive is provided by a two-level SVPWM inverter. The inverter reference voltage is gotten in view of information output criticism linearization control, utilizing the IM display in the stator – axes reference frame with stator current further more flux vectors segments as state factors. Additionally, a powerful full-arrange versatile statorflux observer is intended for a speed sensor less DTC-SVM system and another speed-versatile law is given. By outlining the observer pick up matrix in view of state criticism H_∞ control hypothesis, the strength and robustness of the observer systems is guaranteed. At last, the viability and validity of the proposed control approach is verified by simulation results. Keywords : DirectTorqueControl (DTC), Speed Sensor less Induction Motor (IM) Drive, SpaceVector
DTC drive over the last decade becomes one possible alternative to the well-known VectorControl of Induction Machines. Its main characteristic is the good performance, obtaining results as good as the classical vectorcontrol but with several advantages based on its simpler structure and control diagram. DTC (DirectTorqueControl) is characterized, as deduced from the name, by directly controlled torque and flux and indirectly controlled stator current and voltage. The DTC has some advantages in comparison with the conventional vector-controlled drives, like:-Directtorquecontrol and directstatorfluxcontrol, Indirect control of stator currents and voltages, Approximately sinusoidal stator fluxes and stator currents, High dynamic performance even at locked rotor, Absences of co-ordinates transform, Absences of mechanical transducers, Current regulators, PWM pulse generation, PI control of flux and torque and co- ordinate transformation are not required, Very simple control scheme and low computation time, Reduced parameters sensitivity, Very good dynamic properties.Conventional DTC has also some disadvantages: Possible problems during starting and low speed operation, high requirements upon flux and torqueestimation, Variable switching frequency, these are disadvantages that we want to remove by usingfuzzylogic. In the following, we will describe the application of fuzzylogic in DTC control.
The generalized predictive control (GPC) of Clarke (Papafotiou and Kley, 2009), is considered as the most popular method of prediction, especially for industrial processes. This resolution is not repeated each time there is an optimal control problem: "how to get from the current state to a goal of optimally satisfying constraints" (Rawlings and Mayne, 2009). For this, you must know at each iteration the system state using a numerical tool. Temporal representation of generalized predictive control is given by (Fig.2), where there are controls u(k) applied to the system for rallying around the set point w (k). Numerical model is obtained by a discretization of the continuous transfer function of the model which is used to calculate the predicted output of a
The DTC of DMC is based on Table 1, and the control of input power factor for fixed that to one, a hysteresis com- parator is added to confirmed that, whatever is the sec- tor which the input voltage vector is in, the MC takes any time two switching configurations with several directions for each VSI output vector selection by the classical DTC, this directions allows the possibility to control the input power factor by applied one to increase the angle and the second to decrease. The all probability switching con- figuration of MC used in DTC it gives in the Table 2, and the spacevector diagram of output voltage and input cur- rent has been shown in Fig. 4 [14, 17, 18].
On the other hand, multi-level inverters have become a very attractive solution for high power application areas . The three-level neutral point clamped (NPC) inverter is one of the most commonly used multi-level inverter topologies in high power ac drives. By comparing to the standard two-level inverter, the three-level inverter presents its superiority in terms of lower stress across the semiconductors, lower voltage distortion, less harmonic content and lower switching frequency .
is proposed for induction motor drives to ensure maximum efficiency operation for a given torque demand. The continuous needs of energy savings require higher efficient electrical drives which uses Adjustable Speed Drives (ASDs). Due to its ruggedness, simple technology, maintenance-freeness and low cost, the Induction Machine (IM) still represents the major energy consumer in ASDs. For applications that require flux-weakening, IMs provide a better solution for ASDs. The efficiency of IM drives can be improved by flux adaptation according to the load demand. The flux adaptation can be done through three categories of loss-minimizing strategies, implemented for scalar or vectorcontrol of induction motor drives. These loss minimizing strategies are 1) control of a single motor variable, such as the displacement power factor or the slip frequency 2) the search control, where the motor flux is iteratively adapted to minimize the input power and 3) loss model of the motor and/or the power converter. The proposed strategy directly regulates the machine statorflux according to the desired torque, using an optimal statorflux reference. Therefore, the proposed strategy is suitable for motor control schemes that are based on directflux regulation, such as directtorquecontrol or directfluxvectorcontrol. The maximum efficiency per torque (MEPT) statorflux map is computed offline using the traditional no-load and short-circuit tests’ data. This strategy makes the motor efficiency is significantly improved below rated torque compared to the constant rated flux operation An iron loss model based on the statorflux and frequency is also proposed for the calibration of the machine loss model and also for on-line monitoring of the iron losses during motor.
in the vectorcontrol are compared with the respective and currents generated by transformation of phase current equation (6) with help of unit vector ( ). The respective error generate the voltage command signal ∗ and ∗ through P-I compensators and these voltage commands are then converted into and voltages, these voltages are given to the input of SVPWM. The outputs of the Spacevector pulse width modulation are the signals that drive the inverter. Among various modulation techniques for inverter, SVPWM technique is an attractive technique which directly uses the control variable given by the control system and identifies each switching vector as a point in complex space. The current model generates the rotor flux position and is dependent on the rotor time constant ( = ). The proposed block diagram is shown in the fig.1.
The motor speed can be controlled indirectly by controlling the torque with a fuzzy controller. Fuzzylogic is based on the theory of fuzzy sets developed by Zadeh . This is an extension of the classical theory for the incorporation of fuzzy set. The proposed fuzzy controller has two inputs and one output as described in Figure 5.
Four-Wheels-Drive (4WD) Electric Vehicle (EV) controlled with DirectTorqueControlbasedSpaceVector Modula- tion (DTC-SVM) is presented, where the electrical traction chain was well analyzed and studied from the lithium bat- tery, the buck boost to the mechanical load behavior. The speed of four wheels is calculated independently during the turning with the electronic differential system computations which distributes torque and power to each in-wheel motor according to the requirements, adapts the speed of each motor to the driving conditions. The basic idea of this work is to maintain the initial battery state of charge (SOC) equal to 70% and the prototype was tested in several topology condi- tions and under speed. The simulations carried in Matlab/Simulink verified the efficiency of the proposed DTC-SVM controller, and show that the system has more favorable dynamic performance. Results also indicate that this strategy can be successfully implemented into the traction drive of the modern 4WD electric vehicles.
The fundamental idea of a directtorquecontrol is a based on the switching tables with hysteresis of torque and statorflux. Using this method, for a the minimization of the commutations of the inverter switches, on the torque/statorflux decoupling, on the control of the PWM generator, DTC requires precise knowledge of the amplitude and angular position of the controlled flux with respect to the stationary stator axis in addition to the angular velocity for the torquecontrol purpose [8, 13]. We don’t require the rotor position in order to choose the voltage vector. This particularity defines the DTC as an adapted control technique of AC machines [10-12].
The directtorque and fluxcontrol for induction machine drives has been developed as directtorquecontrol (DTC) in , and as direct self control (DSC) in . Classic DTC  has several drawbacks: it exhibits large torque, flux, and current ripple, produces annoying acoustical noise, operates with nonzero steady-state torque error, has difficulties in controlling the flux at low speeds, and the switching frequency is variable and lower than the sampling frequency. Three classes of modified DTC schemes that deal with these problems and attempt to improve DTC behavior have evolved: (a) schemes that use improved comparators and switching tables, while the original topology is unchanged –; (b) solutions that implement the DTC concept my means of space-vectormodulation (SVM) –; (c) torque and fluxcontrol systems that explicitly use the variable- structure control (VSC) approach –.