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

Fuzzy second order sliding mode control of a unified power flow controller

Purpose. This paper presents an advanced control scheme based on fuzzy logic and second order sliding mode of a unified power flow controller. This controller offers advantages in terms of static and dynamic operation of the power system such as the control law is synthesized using three types of controllers: proportional integral, and sliding mode controller and Fuzzy logic second order sliding mode controller. Their respective performances are compared in terms of reference tracking, sensitivity to perturbations and robustness. We have to study the problem of controlling power in electric system by UPFC. The simulation results show the effectiveness of the proposed method especiallyin chattering-free behavior, response to sudden load variations and robustness. All the simulations for the above work have been carried out using MATLAB / Simulink. Various simulations have given very satisfactory results and we have successfully improved the real and reactive power flows on a transmission lineas well as to regulate voltage at the bus where it is connected, the studies and illustrate the effectiveness and capability of UPFC in improving power.В настоящей статье представлена усовершенствованная схема управления, основанная на нечеткой логике и режиме скольжения второго порядка унифицированного контроллера потока мощности. Данный контроллер обладает преимуществами с точки зрения статической и динамической работы энергосистемы, например, закон управления синтезируется с использованием трех типов контроллеров: пропорционально-интегрального, контроллера скользящего режима и контроллера скользящего режима нечеткой логики второго порядка. Их соответствующие характеристики сравниваются с точки зрения отслеживания эталонов, чувствительности к возмущениям и надежности. Необходимо изучить проблему управления мощностью в энергосистеме с помощью унифицированного контроллера потока мощности (UPFC). Результаты моделирования показывают эффективность предложенного метода, особенно в отношении отсутствия вибрации, реакции на внезапные изменения нагрузки и устойчивости. Все расчеты для вышеуказанной работы были выполнены с использованием MATLAB/Simulink. Различные расчетные исследования дали весьма удовлетворительные результаты, и мы успешно улучшили потоки реальной и реактивной мощности на линии электропередачи, а также регулирование напряжения на шине, к которой она подключена, что позволяет изучить и проиллюстрировать эффективность и возможности UPFC для увеличения мощности

AC voltage regulation of a bidirectional high-frequency link converter using a deadbeat controller

This paper presents a digital controller for AC voltage regulation of a bidirectional high-frequency link (BHFL) inverter using Deadbeat control. The proposed controller consists of inner current loop, outer voltage loop and a feed-forward controller, which imposes a gain scheduling effect according to the reference signal to compensate the steady-state error of the system. The main property of the proposed controller is that the current- and the voltage-loop controllers have the same structure, and use the same sampling period. This simplifies the design and implementation processes. To improve the overall performance of the system, additional disturbance decoupling networks are employed. This takes into account the model discretization effect. Therefore, accurate disturbance decoupling can be achieved, and the system robustness towards load variations is increased. To avoid transformer saturation due to low frequency voltage envelopes, an equalized pulse width modulation (PWM) technique has been introduced. The proposed controller has been realized using the DS1104 digital signal processor (DSP) from dSPACE. Its performances have been tested on a one kVA prototype inverter. Experimental results showed that the proposed controller has very fast dynamic and good steady-state responses even under highly nonlinear loads

To develop an efficient variable speed compressor motor system

This research presents a proposed new method of improving the energy efficiency of a Variable Speed Drive (VSD) for induction motors. The principles of VSD are reviewed with emphasis on the efficiency and power losses associated with the operation of the variable speed compressor motor drive, particularly at low speed operation.The efficiency of induction motor when operated at rated speed and load torque is high. However at low load operation, application of the induction motor at rated flux will cause the iron losses to increase excessively, hence its efficiency will reduce dramatically. To improve this efficiency, it is essential to obtain the flux level that minimizes the total motor losses. This technique is known as an efficiency or energy optimization control method. In practice, typical of the compressor load does not require high dynamic response, therefore improvement of the efficiency optimization control that is proposed in this research is based on scalar control model.In this research, development of a new neural network controller for efficiency optimization control is proposed. The controller is designed to generate both voltage and frequency reference signals imultaneously. To achieve a robust controller from variation of motor parameters, a real-time or on-line learning algorithm based on a second order optimization Levenberg-Marquardt is employed. The simulation of the proposed controller for variable speed compressor is presented. The results obtained clearly show that the efficiency at low speed is significant increased. Besides that the speed of the motor can be maintained. Furthermore, the controller is also robust to the motor parameters variation. The simulation results are also verified by experiment

Advanced and Innovative Optimization Techniques in Controllers: A Comprehensive Review

New commercial power electronic controllers come to the market almost every day to help improve electronic circuit and system performance and efficiency. In DC–DC switching-mode converters, a simple and elegant hysteretic controller is used to regulate the basic buck, boost and buck–boost converters under slightly different configurations. In AC–DC converters, the input current shaping for power factor correction posts a constraint. But, several brilliant commercial controllers are demonstrated for boost and fly back converters to achieve almost perfect power factor correction. In this paper a comprehensive review of the various advanced optimization techniques used in power electronic controllers is presented

Fuzzy control system review

Overall intelligent control system which runs on fuzzy, genetic and neural algorithm is a promising engine for large –scale development of control systems . Its development relies on creating environments where anthropomorphic tasks can be performed autonomously or proactively with a human operator. Certainly, the ability to control processes with a degree of autonomy is depended on the quality of an intelligent control system envisioned. In this paper, a summary of published techniques for intelligent fuzzy control system is presented to enable a design engineer choose architecture for his particular purpose. Published concepts are grouped according to their functionality. Their respective performances are compared. The various fuzzy techniques are analyzed in terms of their complexity, efficiency, flexibility, start-up behavior and utilization of the controller with reference to an optimum control system condition

HYBRID FUZZY CONTROL AND ANT COLONY OPTIMIZATION BASED PATH PLANNING FOR WHEEL MOBILE ROBOT NAVIGATION

Wheeled Mobile Robot (WMR) is extremely important for active target tracking control and reactive obstacle avoidance in an unstructured environment. A WMR needs the best control performance an automatic path planning to maintain a very high level of accuracy. Therefore, the development of control strategies and path planning is very significant. Hence, research was carried out to investigate the control and path planning issues of WMR in dynamic environment. Several controllers such as conventional controller Proportional (P), Integral (I), Derivative (D) and Fuzzy Logic controller were investigated. A Hybrid Controller for differential WMR was proposed. Various aspects of the research on WMR such as kinematics model, conventional controller, fuzzy controller and hybrid controller were discussed. Overall it was found that on average the Hybrid Controller gives the best performance with 5.5s, 5.4s and 11s for target of 10x 10y, 30x10y and 60x20y respectively

SPEED CONTROL OF DC MOTOR ON LOAD USING FUZZY LOGIC CONTROLLER (A CASE STUDY OF EMERGENCY LUBE OIL PUMP MOTOR OF H25 HITACHI TURBINE GENERATOR)

This paper presents the development of a fuzzy logic controller for the driver DC motor in the lube oil system of the H25 Hitachi gas turbine generator. The turbine generator is required to run at an operating pressure of 1.5bar with the low and the high pressure trip points being 0.78 bar and 1.9 bar respectively. However, the driver DC motor speed drifted from the desired speed of 1450 revolutions per minutes (rpm) to as low as 1414 rpm. It is against this backdrop, that this project work was envisaged to design a controller capable of controlling the speed of the DC motor in order to achieve the desired speed rating of 1450 rpm. In modelling the motor, the transfer function method was used to develop a linear approximation to the actual motor. After computing the total inertia of the motor shaft, the motor model was simulated for the speed response in MATLAB and Simulink environment, and the response showed that the motor attained an actual maximum speed of 1414 rpm at settling time of 0.3 seconds.  Based on expert knowledge of the lube oil system, a fuzzy logic controller was designed and this resulted in the issuance of a control action to correct the actual speed of the motor from 1414 rpm to the desired speed of 1450 rpm.  http://dx.doi.org/10.4314/njt.v36i3.2

MODELLING AND CONTROL OF MULTI-FINGERED ROBOT HAND USING INTELLIGENT TECHNIQUES

Research and development of robust multi-fingered robot hand (MFRH) have been going on for more than three decades. Yet few can be found in an industrial application. The difficulties stem from many factors, one of which is that the lack of general and effective control techniques for the manipulation of robot hand. In this research, a MFRH with five fingers has been proposed with intelligent control algorithms. Initially, mathematical modeling for the proposed MFRH has been derived to find the Forward Kinematic, Inverse Kinematic, Jacobian, Dynamics and the plant model. Thereafter, simulation of the MFRH using PID controller, Fuzzy Logic Controller, Fuzzy-PID controller and PID-PSO controller has been carried out to gauge the system performance based parameters such rise time, settling time and percent overshoot