Development and Implementation of Some Controllers for Performance Enhancement and Effective Utilization of Induction Motor Drive

The technological development in the field of power electronics and DSP technology is rapidly changing the aspect of drive technology. Implementations of advanced control strategies like field oriented control, linearization control, etc. to AC drives with variable voltage, and variable frequency source is possible because of the advent of high modulating frequency PWM inverters. The modeling complexity in the drive system and the subsequent requirement for modern control algorithms are being easily taken care by high computational power, low-cost DSP controllers. The present work is directed to study, design, development, and implementation of various controllers and their comparative evaluations to identify the proper controller for high-performance induction motor (IM) drives. The dynamic modeling for decoupling control of IM is developed by making the flux and torque decoupled. The simulation is carried out in the stationary reference frame with linearized control based on state-space linearization technique. Further, comprehensive and systematic design procedures are derived to tune the PI controllers for both electrical and mechanical subsystems. However, the PI-controller performance is not satisfactory under various disturbances and system uncertainties. Also, precise mathematical model, gain values, and continuous tuning are required for the controller design to obtain high performance. Thus, to overcome these drawbacks, an adapted control strategy based on Adaptive Neuro-Fuzzy Inference System (ANFIS) based controller is developed and implemented in real-time to validate different control strategies. The superiority of the proposed controller is analyzed and is contrasted with the conventional PI controller-based linearized IM drive. The simplified neuro-fuzzy control (NFC) integrates the concept of fuzzy logic and neural network structure like conventional NFC, but it has the advantages of simplicity and improved computational efficiency over conventional NFC as the single input introduced here is an error instead of two inputs error and change in error as in conventional NFC. This structure makes the proposed NFC robust and simple as compared to conventional NFC and thus, can be easily applied to real-time industrial applications. The proposed system incorporated with different control methods is also validated with extensive experimental results using DSP2812. The effectiveness of the proposed method using feedback linearization of IM drive is investigated in simulation as well as in experiment with different working modes. It is evident from the comparative results that the system performance is not deteriorated using proposed simplified NFC as compared to the conventional NFC, rather it shows superior performance over PI-controller-based drive. A hybrid fuel cell (FC) supply system to deliver the power demanded by the feedback linearization (FBL) based IM drive is designed and implemented. The modified simple hybrid neuro-fuzzy sliding-mode control (NFSMC) incorporated with the intuitive FBL substantially reduces torque chattering and improves speed response, giving optimal drive performance under system uncertainties and disturbances. This novel technique also has the benefit of reduced computational burden over conventional NFSMC and thus, suitable for real-time industrial applications. The parameters of the modified NFC is tuned by an adaptive mechanism based on sliding-mode control (SMC). A FC stack with a dc/dc boost converter is considered here as a separate external source during interruption of main supply for maintaining the supply to the motor drive control through the inverter, thereby reducing the burden and average rating of the inverter. A rechargeable battery used as an energy storage supplements the FC during different operating conditions of the drive system. The effectiveness of the proposed method using FC-based linearized IM drive is investigated in simulation, and the efficacy of the proposed controller is validated in real-time. It is evident from the results that the system provides optimal dynamic performance in terms of ripples, overshoot, and settling time responses and is robust in terms of parameters variation and external load

Closed-Loop Drive Detection and Diagnosis of Multiple Combined Faults in Induction Motor Through Model-Based and Neuro-Fuzzy Network Techniques

In this paper, a fault detection and diagnosis approach adopted for an input-output feedback linearization (IOFL) control of induction motor (IM) drive is proposed. This approach has been employed to detect and identify the simple and mixed broken rotor bars and static air-gap eccentricity faults right from the start its operation by utilizing advanced techniques. Therefore, two techniques are applied: the model-based strategy, which is an online method used to generate residual stator current signal in order to indicate the presence of possible failures by means of the sliding mode observer (SMO) in the closed-loop drive. However, this strategy is not able to recognise the fault types and it can be affected by the other disturbances. Therefore, the offline method using the multi-adaptive neuro-fuzzy inference system (MANAFIS) technique is proposed to identify the faults and distinguish them. However, the MANAFIS required a relevant database to achieve satisfactory results. Hence, the stator current analysis based on the HFFT combination of the Hilbert transform (HT) and Fast Fourier transform (FFT) is applied to extract the amplitude of harmonics due to defects occur and used them as an input data set for the MANFIS under different loads and fault severities. The simulation results show the efficiency of the proposed techniques and its ability to detect and diagnose any minor faults in a closed-loop drive of IM

Advanced Fault-Tolerant Control of Induction-Motor Drives for EV/HEV Traction Applications: From Conventional to Modern and Intelligent Control Techniques

International audienceThis paper describes active fault-tolerant control systems for a high-performance induction-motor drive that propels an electrical vehicle (EV) or a hybrid one (HEV). The proposed systems adaptively reorganize themselves in the event of sensor loss or sensor recovery to sustain the best control performance, given the complement of remaining sensors. Moreover, the developed systems take into account the controller-transition smoothness, in terms of speed and torque transients. The two proposed fault-tolerant control strategies have been simulated on a 4-kW induction-motor drive, and speed and torque responses have been carried to evaluate the consistency and the performance of the proposed approaches. Simulation results, in terms of speed and torque responses, show the global effectiveness of the proposed approaches, particularly the one based on modern and intelligent control techniques in terms of speed and torque smoothness

Estimation of rotor flux of an induction machine

The objective of this dissertation is to estimate rotor flux of an IM. Some of the material is focused on the functional block of the IM i.e. Torque estimator, Speed estimator etc. while a subsequent part deals with estimation of rotor flux. The dissertation is organized as follows:Chapter 1 describes background information of the machines then it focuses on the methodology how on to approach the task on a particular time with the help of Gantt chart.Chapter 2 presents the basic principals of rotating magnetic field of the IM and asserts brief overview of the AC machines. Later it talks about different kinds of IM rotors suggesting which one is good. It is crucial to start with good and appropriate reviews which were verified by numerous journals. Literature review is presented by analysing the previous work. (Busawan et al., 2001) summarises that a nonlinear observers for the estimation of the rotor flux and the load torque in an induction motor. The observers are designed on the basis of the standard alpha - beta Park's model. Finally, fuzzy logic is mentioned in more detailed way and Membership functions were also discussedChapter 3 explains the dynamic model of induction machine plant and the model was presented. Then the model is analysed, developed in MATLAB-SIMULINK which was discussed in Chapter 4. By considering following assumptions, dynamic model is implemented i.e. it should be symmetrical two-pole, three phase windings. Slotting effects are neglected, Permeability of the iron part is infinite, and iron losses are neglected. Dynamic d-q model and Axes transformation is implemented on stationary reference frame (a-b-c). Lastly torque equation is derived.Chapter 4 is the heart of this project by scrutinizing the model thoroughly and by introducing fuzzy controller logic using MATLAB-SIMULINK; simulations are performed to estimate the functional block such as torque, speed, flux, resistance with and without fuzzy logic. Results were obtained for different blocks and the m-file, DTC, Flux table were obtained and presented in the Appendixes.Chapter 5 concludes the simulation results and concentrates mainly on the future direction what more can be done to improve the platform in a more efficient manner

Speed Control of Parallel Connected DSIM Fed by Six Phase Inverter with IFOC Strategy Using ANFIS

This paper describe the presentation of an IM for high load and high-power applications, this kind of applications the motor have a complex coupling between the field and torque. This can be achieve with assist of Indirect Field Oriented Control (IFOC) and parallel connection of two motors. The benefit is that parallel connection can provide the decoupled control of flux and torque for each motor and their concert in different operating environments. The Speed control of two Double Star Induction Motors working in parallel configuration with IFOC using a Fuzzy Logic Controller (FLC) and Adaptive Neuro Fuzzy Inference (ANFIS) controller is investigate in different operating environments. The two motors are connected in parallel at the output of a single six-phase PWM based inverter fed from a DC source. Performance of the projected method under load disturbances is studied through simulation using a MATLAB and evaluation of speed response of two controllers is analyzed. &nbsp

A Nonlinear Sliding Mode Controller for IPMSM Drives with an Adaptive Gain Tuning Rule

This paper presents a nonlinear sliding mode control (SMC) scheme with a variable damping ratio for interior permanent magnet synchronous motors (IPMSMs). First, a nonlinear sliding surface whose parameters change continuously with time is designed. Actually, the proposed SMC has the ability to reduce the settling time without an overshoot by giving a low damping ratio at the initial time and a high damping ratio as the output reaches the desired setpoint. At the same time, it enables a fast convergence in finite time and eliminates the singularity problem with the upper bound of an uncertain term, which cannot be measured in practice, by using a simple adaptation law. To improve the efficiency of a system in the constant torque region, the control system incorporates the maximum torque per ampere (MTPA) algorithm. The stability of the nonlinear sliding surface is guaranteed by Lyapunov stability theory. Moreover, a simple sliding mode observer is used to estimate the load torque and system uncertainties. The effectiveness of the proposed nonlinear SMC scheme is verified using comparative experimental results of the linear SMC scheme when the speed reference and load torque change under system uncertainties. From these experimental results, the proposed nonlinear SMC method reveals a faster transient response, smaller steady-state speed error, and less sensitivity to system uncertainties than the linear SMC metho

Modelling, simulation and analysis of DSIM using artificial intelligent controller

This paper presents an elaboration for speed control of dual stator induction motor (DSIM) using artificial intelligent controller. The main problem with the conventional fuzzy controllers is that the parameters associated with the membership functions and the rules depend broadly on the intuition of the experts. To overcome this problem, adaptive neuro-fuzzy inference system (ANFIS) controller is proposed in this paper. The elaboration allows to compare simulation results between classical and artificial intelligent controllers. The fuzzy logic controller (FLC) and ANFIS controllers are also introduced to the system for keeping the motor speed to be constant when the load varies. Comparison between PI, fuzzy and Adaptive neuro-fuzzy controller-based dynamic performance of DSIM drive has been presented. ANFIS-based control of DSIM will prove to be more reliable than other control methods. The performance of the DSIM drive has been analyzed for constant load and change in speed conditions.&nbsp

Optimized Adaptive Sliding-mode Position Control System for Linear Induction Motor Drive

[[abstract]]This paper proposes an optimized adaptive position control system applied for a linear induction motor (LIM) drive taking into account the longitudinal end effects and uncertainties including the friction force. The dynamic mathematical model of an indirect field-oriented LIM drive is firstly derived for controlling the LIM. On the basis of a backstepping control law, a sliding mode controller (SMC) with embedded fuzzy boundary layer is designed to compensate the lumped uncertainties during the tracking control of periodic reference trajectories. Since it is difficult to obtain the bound of lumped uncertainties in advance in practical applications, an adaptive tuner based on the sense of Lyapunov stability theorem is derived to adjust the fuzzy boundary parameters in real-time. It is a quite complicated process of parameter tuning, especially for the proposed controller, due to the difficulty arisen from lacking of the accurate mathematical model of a system accompanied with unknown disturbance. Therefore, the soft-computing technique is adopted for off-line optimizing the controller parameters. The effectiveness of the proposed control scheme is validated through simulations and experiments for several scenarios. Finally, the advantages of performance improvement and robustness are illustrated at the end of the optimization procedure.[[conferencetype]]國際[[conferencedate]]20130410~20130412[[booktype]]電子版[[iscallforpapers]]Y[[conferencelocation]]Paris, Franc

Nov i jednostavan hibridni neizraziti/PI regulator za istosmjerne motore bez četkica

A novel speed controller for the trapezoidal three--phase Brushless DC (BLDC) Motor Drive is proposed using a hybrid fuzzy logic and proportional plus integral (PI) control. The fuzzy logic control structure is different from conventional fuzzy logic implementations such that it only uses three simple rules based on speed error being either in the positive, negative or zero regions. The controller outputs a reference current, that is enforced through the motor phases by pulsewidth modulation (PWM) control. The proposed fuzzy logic controller can be used individually in applications requiring lower computation load and accepting small steady state offset. For high performance applications requiring offset free tracking, a PI controller is augmented with the fuzzy logic controller and a simple switching scheme is devised based on error variance to switch the active controller based on operating conditions. The response of the drive system under the proposed composite control structure is compared with the conventional PI based and the sliding mode controllers to demonstrate its improved performance. Simulations studies using detailed models in MATLAB/Simulink\u27s Simpowersystems toolbox are carried out to show the validity of proposed control.U ovome radu predlaže se nov regulator brzine za trapezoidalne trofazne istosmjerne motore bez četkica zasnovan na hibridnom regulatoru. Hibridni regulator sastoji se od dijela s neizrazitom logikom i proporcionano-integracijskog regulatora. Struktura neizrazitog regulatora razlikuje se od konvencionalnih implementacija neizrazitih regulatora po tome što koristi samo tri jednostavna pravila zasnovana na pogrešci brzine u pozitivnom, negativnom ili nultom području. Izlaz regulatora čini referentna struja, koja se šalje na faze motora pomoću širinsko-impulsne modulacije. Predloženi neizraziti regulator može se koristiti i zasebno u primjenama koje zahtijevaju manju računsku složenost i toleriraju malu pogrešku u stacionarnom stanju. Za slučajeve kada je potrebna visoka učinkovitost bez pogreške u stacionarnom stanju, s neizrazitim dijelom proširuje se PI regulator te je razvijen jednostavan postupak promijene regulatora zasnovan na varijanci pogreške. Odziv razmatranog sustava uspoređen je s konvencionalnim PI regulatorom i regulatorom u kliznom režimu rada kako bi se pokazala njegova učinkovitost. Izvršene su simulacije u Matlab/Simulinkovom SimPowerSystems alatu kako bi se pokazala ispravnost predloženog postupka