A new non-linear system for estimating and suppressing narrowband interference in PN spread spectrum modulation

This work develops a novel dynamic fuzzy logic system that, based on a fuzzy basis function expansion, successfully solves the non-linear problem of narrowband interference prediction and rejection in DS-SS. A fuzzy basis function representation provides a natural framework for combining both numerical and linguistic information in a uniform fashion. The result is a low complexity non-linear adaptive line enhancer, which offers a faster convergence rate and an overall better performance over other well-known non-linear line enhancers.Peer ReviewedPostprint (published version

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

Induction Motors

AC motors play a major role in modern industrial applications. Squirrel-cage induction motors (SCIMs) are probably the most frequently used when compared to other AC motors because of their low cost, ruggedness, and low maintenance. The material presented in this book is organized into four sections, covering the applications and structural properties of induction motors (IMs), fault detection and diagnostics, control strategies, and the more recently developed topology based on the multiphase (more than three phases) induction motors. This material should be of specific interest to engineers and researchers who are engaged in the modeling, design, and implementation of control algorithms applied to induction motors and, more generally, to readers broadly interested in nonlinear control, health condition monitoring, and fault diagnosis

Techniques of EMG signal analysis: detection, processing, classification and applications

Electromyography (EMG) signals can be used for clinical/biomedical applications, Evolvable Hardware Chip (EHW) development, and modern human computer interaction. EMG signals acquired from muscles require advanced methods for detection, decomposition, processing, and classification. The purpose of this paper is to illustrate the various methodologies and algorithms for EMG signal analysis to provide efficient and effective ways of understanding the signal and its nature. We further point up some of the hardware implementations using EMG focusing on applications related to prosthetic hand control, grasp recognition, and human computer interaction. A comparison study is also given to show performance of various EMG signal analysis methods. This paper provides researchers a good understanding of EMG signal and its analysis procedures. This knowledge will help them develop more powerful, flexible, and efficient applications

Nonlinear Time-Frequency Control of Permanent Magnet Electrical Machines

Permanent magnet (PM) electrical machines have been widely adopted in industrial applications due to their advantages such as easy to control, compact in size, low in power loss, and fast in response, to name only a few. Contemporary control methods specifically designed for the control of PM electrical machines only focus on controlling their time-domain behaviors while completely ignored their frequency-domain characteristics. Hence, when a PM electrical machine is highly nonlinear, none of them performs well. To make up for the drawback and hence improve the performance of PM electrical machines under high nonlinearity, the novel nonlinear time-frequency control concept is adopted to develop viable nonlinear control schemes for PM electrical machines. In this research, three nonlinear time-frequency control schemes are developed for the speed and position control of PM brushed DC motors, speed and position control of PM synchronous motors, and chaos suppression of PM synchronous motors, respectively. The most significant feature of the demonstrated control schemes are their ability in generating a proper control effort that controls the system response in both the time and frequency domains. Simulation and experiment results have verified the effectiveness and superiority of the presented control schemes. The nonlinear time-frequency control scheme is therefore believed to be suitable for PM electrical machine control and is expected to have a positive impact on the broader application of PM electrical machines

A Single-phase Rectifier With Ripple-power Decoupling and Application to LED Lighting

In recent years, Light-Emitting-Diode (LED) is widely used in lighting applications for its high efficacy and high reliability. However, the rectifier, which is required by the LEDs to convert the AC power from the grid into DC power, suffers from low-reliability caused by the filtering capacitor. In order to fully utilize the long operational hours of the LEDs, this thesis proposes a rectifier that has improved reliability by adding a ripple-port to eliminate the non-reliable electrolytic capacitor. The ripple-port is capable of decoupling the ripple-power inherited in a single-phase rectifier, which enables using the reliable film capacitor to replace the electrolytic capacitor. To guarantee that the ripple-port can effectively decouple the ripple-power, a closed-loop control scheme is designed and implemented in a digital controller. Simulation and experimental results show that the proposed rectifier can reduce the required capacitance by 70%, which results in a 60% increase in lifetime. The proposed ripple-port circuit can be considered as an add-on module to be integrated into the rectifiers used in applications that require long lifetime. A detailed analysis of the efficiency, cost and reliability of applying the ripple-port in LED lighting applications supports the feasibility of the proposed circuit

Microprocessor based signal processing techniques for system identification and adaptive control of DC-DC converters

Many industrial and consumer devices rely on switch mode power converters (SMPCs) to provide a reliable, well regulated, DC power supply. A poorly performing power supply can potentially compromise the characteristic behaviour, efficiency, and operating range of the device. To ensure accurate regulation of the SMPC, optimal control of the power converter output is required. However, SMPC uncertainties such as component variations and load changes will affect the performance of the controller. To compensate for these time varying problems, there is increasing interest in employing real-time adaptive control techniques in SMPC applications. It is important to note that many adaptive controllers constantly tune and adjust their parameters based upon on-line system identification. In the area of system identification and adaptive control, Recursive Least Square (RLS) method provide promising results in terms of fast convergence rate, small prediction error, accurate parametric estimation, and simple adaptive structure. Despite being popular, RLS methods often have limited application in low cost systems, such as SMPCs, due to the computationally heavy calculations demanding significant hardware resources which, in turn, may require a high specification microprocessor to successfully implement. For this reason, this thesis presents research into lower complexity adaptive signal processing and filtering techniques for on-line system identification and control of SMPCs systems. The thesis presents the novel application of a Dichotomous Coordinate Descent (DCD) algorithm for the system identification of a dc-dc buck converter. Two unique applications of the DCD algorithm are proposed; system identification and self-compensation of a dc-dc SMPC. Firstly, specific attention is given to the parameter estimation of dc-dc buck SMPC. It is computationally efficient, and uses an infinite impulse response (IIR) adaptive filter as a plant model. Importantly, the proposed method is able to identify the parameters quickly and accurately; thus offering an efficient hardware solution which is well suited to real-time applications. Secondly, new alternative adaptive schemes that do not depend entirely on estimating the plant parameters is embedded with DCD algorithm. The proposed technique is based on a simple adaptive filter method and uses a one-tap finite impulse response (FIR) prediction error filter (PEF). Experimental and simulation results clearly show the DCD technique can be optimised to achieve comparable performance to classic RLS algorithms. However, it is computationally superior; thus making it an ideal candidate technique for low cost microprocessor based applications.EThOS - Electronic Theses Online ServiceIraq Ministry of Higher EducationGBUnited Kingdo

Use of RNS Based Pseudo Noise Sequence in DS-CDMA and 3G WCDMA

Code Division Multiple Access (CDMA) based on Spread Signal (SS) has emerged as one of the most important multiple access technologies for Second Generation (2G) and Third Generation (3G) wireless communication systems by its wide applications in many important mobile cellular standards. CDMA technique relies on spreading codes to separate dierent users or channels and its properties will govern the performance of the system. So many of the problems of communication systems based on CDMA technology stem from the spreading codes/sequences, which includes two sub-categories, one being the orthogonal codes, such as Walsh Hadamard (WH) codes and Orthogonal Variable Spreading Factor (OVSF) codes, and the other being pseudo-noise or Pseudo Random (PN) sequences, such as Gold sequences, Kasami sequences, m-sequences, etc. In this thesis a PN sequence generation based on Residue Arithmetic is investigated with an eort to improve the performance of existing interference-limited CDMA technology for mobile cellular systems. This interference-limited performance is due to the fact that all the existing CDMA codes used in mobile cellular standards does not consider external interferences, multipath propagation, Doppler eect etc. So the non-ideal correlation properties of the pseudo-random CDMA codes results in MAI when used in a multi-user system. The PN codes appear random yet they are completely deterministic in nature with a small set of initial conditions. Consequently this work focuses on CDMA code design approach based on Residue Number System (RNS) which should take into account as many real operational conditions as possible and to maintain a suciently large code set size.First, the thesis reviews RNS, DS-CDMA and CDMA codes that are already implemented in various mobile cellular standards. Then the new PN Sequencegenerator design based on RNS is discussed. Comparison of the generated PN sequence with respect to other standard sequence is done in terms of number of codes and correlation properties. Monte-Carlo simulations with the generated sequence are carried out for performance analysis under multi-path environment. The system has been evaluated in AWGN, Rayleigh Fading channel and dierent Stationary Multipath Channels for dierent cross-correlation threshold. It is known that orthogonal Codes are used to multiplex more than one signal for downlink transmission over cellular networks. This downlink transmission is prone to self interference caused by the loss of orthogonality between spreading codes due to multipath propagation. This issue is investigated in detail with respect to WCDMA standards, which is very good representative for CDMA based 3G mobile cellular systems where the channelization code is OVSF code. The code assignment blocking (CAB) (If a particular code in the tree is used in a cell, then all its parent codes and child codes should not be used in the same cell to maintain orthogonality among the users) problem of OVSF codes restricts the number of available codes for a given cell. Since the 3rd generation WCDMA mobile communication systems apply the same multiple access technique, the generated sequence can also be the channelization code for downlink WCDMA system to mitigate the the same. The performance of the system is compared with Walsh Hadamard code over multipath AWGN and dierent Fading channels. This thesis work shows that RNS based PN sequence has enhanced performance to that of other CDMA codes by comparing the bit error probability in multi- user and multipath environment thus contributing a little towards the evolution of next generation CDMA technology

Nonlinear Time-Frequency Control of Permanent Magnet Electrical Machines

Permanent magnet (PM) electrical machines have been widely adopted in industrial applications due to their advantages such as easy to control, compact in size, low in power loss, and fast in response, to name only a few. Contemporary control methods specifically designed for the control of PM electrical machines only focus on controlling their time-domain behaviors while completely ignored their frequency-domain characteristics. Hence, when a PM electrical machine is highly nonlinear, none of them performs well. To make up for the drawback and hence improve the performance of PM electrical machines under high nonlinearity, the novel nonlinear time-frequency control concept is adopted to develop viable nonlinear control schemes for PM electrical machines. In this research, three nonlinear time-frequency control schemes are developed for the speed and position control of PM brushed DC motors, speed and position control of PM synchronous motors, and chaos suppression of PM synchronous motors, respectively. The most significant feature of the demonstrated control schemes are their ability in generating a proper control effort that controls the system response in both the time and frequency domains. Simulation and experiment results have verified the effectiveness and superiority of the presented control schemes. The nonlinear time-frequency control scheme is therefore believed to be suitable for PM electrical machine control and is expected to have a positive impact on the broader application of PM electrical machines