A robust controller design to stabilize induction motor drive operation using (IFOC) method

This paper proposes a propulsion control algorithm considering End-effect of a linear induction motor (LIM) used in a magnetic levitation train. Indirect field oriented control (IFOC) technique is one of the popular control techniques widely applied to LIM drive control. The main idea of IFOC in a LIM is the decoupling of the flux and torque. Therefore, IFOC has a higher dynamic characteristic than the scalar control [1]. The LIM applied to the magnetic levitation trains should control the thrust force and also take into account the normal force for levitation stabilization. When the LIM is driven, normal force is inevitable. The normal force is a function of the speed, the slip frequency and the current of the train. In the rotary type induction motor, the normal force is canceled due to its symmetrical structure. Therefore, IM could operate in a low slip and high efficiency range. However, in the case of LIM, a high attraction force is generated in a low slip region, which cause the instability of the levitation system. Therefore, the propulsion control for magnetic levitation trains must operate in a higher slip region than the slip used in conventional IFOC. In this paper, the slip characteristics of the LIM are analyzed to improve the efficiency and safety of the magnetic levitation train by FEM analysis. A constant slip frequency propulsion control algorithm is proposed for operation in the analyzed slip region. The proposed algorithm can be controlled by separating magnetic flux and thrust from IFOC. The proposed algorithm is verified in 250 kW test bench. The results of FEM analysis according to speed and slip at constant voltage condition are shown on Fig. 1. The dotted lines of Indirect Field Oriented Control(IFOC) and Constant Slip Indirect Field Oriented Control(CSIFOC) are shown on the figure. The slip of the IFOC is low and that leads to operate near the maximum thrust and efficiency. However, the normal force of LIM is also increase, which could not be allowed in maglev application. On the other hand, when CSIFOC is performed considering normal force, the slip is higher than the conventional algorithm. Although the CSIFOC is not operated in maximum thrust slip, the normal force could be greatly reduced. Fig.2 (a) shows the CSIFOC algorithm considering the end-effect of the linear induction motor. In general IFOC, the d-axis current reference is calculated through the magnetic flux reference value, and the q-axis is calculated based on thrust. However, the CSIFOC for the LIM generates the d-axis and q-axis current references along with the slip frequency and thrust. Fig. 2 (b) shows the waveform of the experimental results based on the general IFOC and the proposed algorithm. Both IFOC and CSIFOC were tested with the same rate pattern of the same load. It is confirmed that CSIVC has larger slip than conventional IFOC and low normal force in all regions. In this paper, a constant slip frequency IFOC algorithm is proposed considering the end effect of LIM used for magnetic levitation trains. The efficiency, thrust and normal force according to the speed and slip through the FEM analysis of the LIM were analyzed and the slip condition suitable for the magnetic levitation train is proposed. In addition, a current reference generation algorithm based on the thrust and slip is proposed in the IFOC considering the end effect to operate under the proposed slip condition. In the full paper, the detailed formulas of the proposed algorithm are developed and will be verified through simulation and experimental results.

Indirect Field Oriented Control (IFOC) is very popular technique in industries due to its simple designing and structure, in comparison to the direct method since it requires flux and torque estimators. This paper presents detail calculation of all values needed for the development of an indirect rotor flux oriented induction motor model fed by a current-controlled voltage source inverter. With the calculated values for 1 hp 50 Hz 3 phase induction motor; an indirect rotor flux oriented model is developed using MATLAB/Simulink. The simulation results are outlined and discussed.

The purpose of this paper is to address improvement of the dynamic and load torque rejection of the indirect field oriented control (IFOC), of an induction motor (IM), by replacing all proportional-integral (PI) controllers with intelligent components: fuzzy logic controllers (FLCs). The controllers substituted, are those of the speed and the stator currents of the IFOC. The performance of the proposed fuzzy control structure, of the IM, was studied in different operating conditions, and was compared with the PI control performance in the same conditions. Simulation tests prove the robustness and relevance of the unique structure of fuzzy logic control based IFOC, in different speed ranges with the application of a load.

Speed Tracking of Indirect Field Oriented Control Induction Motor Using Neural Network

Use of induction motor (IM) at it's highest efficiency is a big demanding task because of their complex mathematical model and non linear features during saturation. These elements make the control of IM strenuous and call for the use of high performance control algorithm such as field orientation control. This paper introduces a speed controller, particularly at minimum speeds by utilizing Fuzzy logic controller (FLC) for indirect field-oriented control (IFOC) of induction motor (IM) drives fed by a four-switch three-phase (FSTP) inverter. From suggested viewpoint, the IM drive is used with a FSTP inverter as an alternative for the conventional six-switch three-phase (SSTP) inverter. Utter IFOC programme includes the FLC of IM drives with the suggested FSTP inverter is raised in MATLAB/Simulink. By considering the good dynamic performance, cost minimization and low total harmonic distortion (THD), FSTP inverters are comparable with SSTP inverters. The dynamic performance and robustness of proposed FLC with the FSTP inverter fed IM drive is verified with PI controller. It is established that the suggested FLC is further powerful than the PI controller under speed tracking and load disturbances

A fuzzy self-tuning hybrid fuzzy controller for indirect field oriented control (IFOC) induction motor drives will be presented in this paper. The developed hybrid fuzzy control law consists of proportional-integral (PI) control at steady state, PI-type fuzzy logic control (FLC) at transient state, a simple switching mechanism between steady and transient states, and fuzzy self-tuning for tuning of their coefficients to have high performance and robustness drive under steady and transient conditions. The importance of the presented hybrid fuzzy controller will be highlighted by comparing the performance of fuzzy self-tuning hybrid fuzzy controller with PI controller, for IFOC induction motor drives. It will be displayed that the presented induction motor drive has both less steady state error and better behavior in transient state; moreover, it is robust to load disturbance, the inertia variation, and robust to rotor resistance variation. Simulation results will be presented confirming the above-mentioned claims.

This paper proposes two control strategies for the bidirectional Z-source inverters (BZSI) supplied by batteries for electric vehicle applications. The first control strategy utilizes the indirect field-oriented control (IFOC) method to control the induction motor speed. The proposed speed control strategy is able to control the motor speed from zero to the rated speed with the rated load torque in both motoring and regenerative braking modes. The IFOC is based on PWM voltage modulation with voltage decoupling compensation to insert the shoot-through state into the switching signals using the simple boost shoot-through control method. The parameters of the four PI controllers in the IFOC technique are designed based on the required dynamic specifications. The second control strategy uses a proportional plus resonance (PR) controller in the synchronous reference frame to control the AC current for connecting the BZSI to the grid during the battery charging/discharging mode. In both control strategies, a dual loop controller is proposed to control the capacitor voltage of the BZSI. This controller is designed based on a small signal model of the BZSI using a bode diagram. MATLAB simulations and experimental results verify the validity of the proposed control strategies during motoring, regenerative braking and grid connection operations.

In this paper, indirect field oriented control (IFOC) of induction motor at very low speed range (1-5 rpm) using a low-count encoder is presented. To test the lowest possible pulse encoder that gives both satisfactory performance for IFOC algorithm and precise enough speed information, a low-count encoder implementation algorithm is developed. This algorithm converts high-resolution encoder data to various number of pulse low-count encoders. Using this algorithm, different pulse encoders are tested and the lowest possible pulse encoder is selected for IFOC implementation due to the cost limitation. Furthermore, solutions to computational problems of microprocessing unit associated with low speed measurement techniques are given. These contributions are experimentally tested and successfully applied to digital signal processor (DSP)- based (TMS320F28xx) ac drives used in traction applications.

Indirect vector control or Indirect Field Oriented Control (IFOC) is known to produce high performance in induction Motor (IM) drives by decoupling rotor flux and torque producing current components of stator current. The most commonly used controller for the vector control of ac motor is Proportional- Integral (P-I) controller. However, the P-I controller has some disadvantages such as high starting overshoot, sensitivity to controller gains and sluggish response to sudden disturbances. So, the Integral-Proportional (I-P) controller is proposed as speed controller for induction motor drives to overcome the disadvantages of the P-I controller. Simulation results are presented and analyzed for both the controllers and it is observed that Integral-Proportional (I-P) controllers give better responses than the traditional P-I controllers for the Indirect Field Oriented Control (IFOC) of ac motor drives.

In the recent days, for the traction and electric vehicle (EV) applications, multiphase machines with pole phase modulation (PPM) technique have been proposed. The smoother operation during pole changeovers as well as steady‐state operations is a significant constraint while adopting the PPM‐based multiphase induction motor (PPMIM) drives for EV and traction applications. So, in this paper, the PPMIM dynamic model and associated vector control are proposed for attaining a smoother operation of the machine. The machine modelling equations and transformation matrices are implemented in an arbitrary reference frame by considering the different pole phase combinations. Based on the modelling equations, the indirect field‐oriented control (IFOC) is proposed for PPMIM drives by reflecting the associated changes in parameters for different pole phase modes. In the IFOC, for regulating the d ‐axis and q‐ axis current components, single PI control loops have been implemented for all pole‐phase combinations. The proposed IFOC scheme is robust and applicable for adopting any type of pulse width modulation. The experimental, as well as simulation results, are given to illustrate the potentiality of the proposed dynamic model and IFOC. The PPMIM machine performance during the steady state as well as pole changeovers in different pole phase modes are analyzed and associated. Simulation and experimental results are presented.

In this paper, a novel multi-objective optimization method based on a Genetic-Fuzzy Algorithm (GFA) is proposed. GFA is applied to optimize the five PI controller gains in the Indirect Field Oriented Control (IFOC) of an induction motor drive. The PI controller gains are designed to optimize the step response of the system. Rise-time, maximum over-shoot, settling time and steady state error are the objective functions. In this drive system, the simultaneous estimation of the rotor speed and time constant for a voltage source inverter-fed induction motor is discussed. The theory is based on the parallel Model Reference Adaptive Control System (MRAC). The vector control of the induction motor may be achieved in the rotor-flux-oriented frame. Furthermore, to eliminate the offset error caused by the change in the stator resistance, a fuzzy resistance is also designed. The simulation results of the new method for induction motor speed control is compared with the results obtained by the conventional method, which allows better performance.

This paper presents the use of local sensitivity analysis techniques to study which output signal of several proposed in the literature can lead to better performance of on-line tuning for rotor time constant variations using model reference adaptive control (MRAC) in indirect field oriented control (IFOC) of induction motors. The expectation is that the output with the highest sensitivity to rotor time constant should be the more suitable for IFOC controller MRAC tuning. We derive the output relative sensitivity functions for steady state operation for active power, reactive power, electromagnetic torque, and the ratio of reactive power and torque to rotor time constant and study their variability as a function of slip frequency. The relative sensitivity functions are used to study their usefulness for rotor time constant tuning. No signal can give uniform satisfactory sensitivity properties over the full range of machine operation. Suggestions are given on how to tackle this issue.

The asynchronous machine has qualities that make it a preferred candidate for variable speed drives, but this simplicity is accompanied by great physical complexity due to the electromagnetic interactions between the stator and the rotor. This paper presented a comparison between fuzzy PI logic and PI traditional controllers based for the speed control of the asynchronous machine (ASM); the analysis was achieved in MATLAB/SIMULINK environment. At first, it described the ASM indirect vector control, which consists in eliminating the coupling between the armature and the inductor to reduce its operation comparable to that of a DC machine. In addition, it described the PI controller; the fuzzy logic controller that does not deal with a well-defined mathematical relationship, but uses inferences with multiple rules control, then, compared their performance. The results of all the controllers have been compared. The machine started at t = 0.1 s from zero speed to t = 0.4 s at no load, and at t = 5 s, a load torque of T = 10 N m was applied to observe the controllers’ performance. As for the comparison of the controllers’ speed response, it can be observed that the PI controller has the highest and that the fuzzy PI has the lowest overshoot of (rad/s). Besides, the settling time for the fuzzy PI is lower than that of PI. The results showed the effectiveness and robustness of the fuzzy control system compared to PI controller for indirect vector control of asynchronous machine.KeywordsAsynchronous machine (ASM)Indirect field-oriented control (IFOC)PI controllerFuzzy logic controllerVector control

This paper proposes a double stage solar-powered speed sensorless vector-controlled induction motor drive for irrigational purpose. The proposed system comprises solar photovoltaic (PV) array, boost converter, three-phase voltage source inverter (VSI), induction motor drive (IMD) and a centrifugal pump. The boost converter operates to extract the peak power from the PV source using Perturb & Observe (P&O) algorithm. The control of VSI focuses on the implementation of indirect field-oriented control (IFOC) with space vector modulation (SVM). The speed of induction motor drive is controlled accordingly to the available PV power. The model reference adaptive system (MRAS) based on rotor flux is used to determine the speed of the motor. The system incorporating two-stage PV powered sensorless IMD is modeled and simulated in MATLAB/Simulink environment, and its performance is studied under dynamic insolations levels.

This paper attempts to introduce the artificial neural network (ANN) principles in the development of an ANN based field oriented control (FOC) of an induction motor. A two-layer ANN has been trained offline to estimate the slip, the direct and the quadrature current commands that are to be used in implementing an indirect FOC scheme. Simulation work indicates the feasibility of this approach as an alternative to the conventional approach, and the practical considerations for implementing this network on a DSP development system are discussed. This paper also proposes a method for estimation and adaptation of the rotor time constant of indirect FOCs. Simulation results show excellent potentials of the proposed scheme.