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

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

Kritik al-Quran oleh Nasr Hamid Abu Zayd melalui terapan hermeneutics humanistic

Nasr Hamid Abu Zayd dikenali sebagai seorang tokoh yang lantang mengkritik al-Quran pada abad ini. Beliau mempunyai metode yang tersendiri ketika mentafsir al-Quran iaitu mengaplikasi hermeneutik dengan menerapkan elemen humanistic. Artikel ini bertujuan untuk menganalisis elemen humanistic yang dibawa oleh Abu Zayd dalam empat aspek iaitu definisi al-Quran, konsep bahawa wahyu, proses penurunan wahyu dan metode pentafsiran. Empat aspek tersebut dibandingkan secara berterusan dengan al-Quran dan al-Sunnah. Untuk mencapai validity data, artikel yang bersifat kualitatif ini menggunakan metode analisis kandungan yang terdiri daripada karyakarya Abu Zayd sebagai sumber pengumpulan data. Manakala analisis data menggunakan kaedah diskriptif dan perbandingan berterusan. Hasil kajian menunjukkan, elemen humanistic yang telah diterapkan kepada al-Quran telah mencetuskan implikasi terhadap al- Quran, konsep wahyu, tafsiran relatif dan liberalisasi hukum syariah

Intelligent control of induction motors

This thesis presents the development and implementation of an integral field oriented intelligent control for an induction motor (IM) drive using Fuzzy Logic Controller (FLC), and an Artificial Neural Network (ANN), employing a finite element controller and making use of a Proportional Integral (PI) adaptive controller as well. An analytical model of an induction motor drive has been developed. In order to prove the superiority of the proposed controller, the performance of this controller is compared with conventional PI-based IM drives. The performance of the proposed IM drive is investigated extensively at different operating conditions in simulation. The proposed adaptive PI-based speed controller’s performance is found to be robust and it is a potential candidate for high performance industrial drive applications. The novel work focuses on using a Finite Element Controller map (FECM) to manipulate adaptive controllers for motor control drives. A digital signal processing (DSP) board DS1104 and laboratory induction motor were used to implement the complete vector control scheme. The test results have been compared with simulated results at different dynamic operating conditions. The effectiveness of this control scheme has been evaluated, and it has been found to be more efficient than the conventional PI controller

Speed and Torque Estimation of BLDC using DTC and Sliding Mode Observer

This paper presents speed and torque estimation for Brushless DC (BLDC) motors with non-sinusoidal back electromotive force using six switch inverter and DTC technique. The 180 conduction mode is the more popular method used for three-phase drives but here we use two-phase conduction mode. A simple approach is discussed n how to reduce ripples in the estimated torque at low frequency operation. A simple look-up table at a pre-defined sampling time is used to select the inverter voltage space vectors and the quasi-wave current is obtained. Estimation of electromagnetic torque for BLDC drives is the key issue and so sensor-less control method are used. The sliding mode observer estimates the back-EMF and generates torque, as under sliding mode observer error equation is reduced and it makes stability easier. Only the measurements of the stator currents is used in the estimation of back-EMF waveform. The electromagnetic torque and the rotor speed is estimated using values from Sliding Mode Observer. Fuzzy Gain Scheduling method is used to tune the parameters because this scheme uses human expertise on PID gain scheduling can be represented in fuzzy rules. Furthermore, better control performance can be expected in the proposed method than that of the PID controllers with fixed parameters and the gains of the sliding mode observer are tuned manually. The effectiveness of the proposed scheme is verified by using simulation results. Keywords: BLDC, DTC, Sliding Mode Observer(SMO), PID Controller, Fuzzy Gain Scheduling, Estimated Rotor speed, Estimated Torque, Estimated Back-EMF

Application of Fuzzy Logic for Performance Enhancement of Drives

Fuzzy logic shows enormous potential for advancing power electronics technology. Its application to DC and AC drives control is discussed here. Initially, a phase-controlled bridge converter DC drive was considered. Analysis of converter performance at continuous and discontinuous conduction modes was first conducted. Fuzzy control was used to linearize the transfer characteristics of the converter in discontinuous conduction mode. It was then extended to current and speed loops, replacing the conventional proportional-integral controllers. The control algorithms were developed in detail, and verified by PC-SIMNON (developed by Lund Institute of Technology Sweden) digital simulation. Significant performance improvement was achieved over conventional control methods. Efficiency optimization of an indirect vector controlled induction motor drive was next considered. An accurate loss model of the converter induction machine system was first developed. Steady-state fundamental and harmonics loss characteristics, besides the dynamic of the machine were analyzed and incorporated in the model, resulting in a new synchronous frame dynamic De-Qe equivalent circuit. The converter system has been modeled accurately for conduction and switching losses. The lossy models were then used in the validation of the fuzzy logic based on-line efficiency optimization control. At steady-state, the fuzzy controller adaptively changes the excitation current on the basis of measured input power, until the maximum efficiency point is reached. The pulsating torque, due to flux reduction, has been compensated by an ingenious feedforward scheme. During transients, rated flux is established, to get the best transient response. After a comprehensive simulation study, an experimental 5 hp drive system was tested, with the proposed controller implemented on a Texas Instrument TMS320C25 digital signal processor, and the theoretical development was fully validated. Finally, fuzzy logic was applied in combination with model-reference adaptive control (MRAC) technique to slip gain tuning of an indirect vector controlled induction motor drive. The MRAC methods based on reactive power and D-axis voltage were combined through a weighting factor, generated by a fuzzy controller, that ensures the use of the best method for any point in the torque-speed plane. A second fuzzy controller tunes the slip gain based on combined detuning error and its slope. The drive performance was extensively investigated through simulations and experiments. The results confirmed the validity of the proposed method

Doubly-fed induction generator used in wind energy

Wound-rotor induction generator has numerous advantages in wind power generation over other generators. One scheme for wound-rotor induction generator is realized when a converter cascade is used between the slip-ring terminals and the utility grid to control the rotor power. This configuration is called the doubly-fed induction generator (DFIG). In this work, a novel induction machine model is developed. This model includes the saturation in the main and leakage flux paths. It shows that the model which considers the saturation effects gives more realistic results. A new technique, which was developed for synchronous machines, was applied to experimentally measure the stator and rotor leakage inductance saturation characteristics on the induction machine. A vector control scheme is developed to control the rotor side voltage-source converter. Vector control allows decoupled or independent control of both active and reactive power of DFIG. These techniques are based on the theory of controlling the B- and q- axes components of voltage or current in different reference frames. In this work, the stator flux oriented rotor current control, with decoupled control of active and reactive power, is adopted. This scheme allows the independent control of the generated active and reactive power as well as the rotor speed to track the maximum wind power point. Conventionally, the controller type used in vector controllers is of the PI type with a fixed proportional and integral gain. In this work, different intelligent schemes by which the controller can change its behavior are proposed. The first scheme is an adaptive gain scheduler which utilizes different characteristics to generate the variation in the proportional and the integral gains. The second scheme is a fuzzy logic gain scheduler and the third is a neuro-fuzzy controller. The transient responses using the above mentioned schemes are compared analytically and experimentally. It has been found that although the fuzzy logic and neuro-fuzzy schemes are more complicated and have many parameters; this complication provides a higher degree of freedom in tuning the controller which is evident in giving much better system performance. Finally, the simulation results were experimentally verified by building the experimental setup and implementing the developed control schemes

Earmuffs

Earmuffs are objects designed to cover a person's ears for hearing protection when doing the harsh work field or for warmth on the cool environment . They consist of a thermoplastic or metal head-band, that fits over the top or back of the head, and a cushion or cup at each end, to cover the external ears