Class of Recursive Wideband Digital Differentiators and Integrators

New designs of recursive digital differentiators are obtained by optimizing a general fourth-order recursive digital filter over different Nyquist bands. In addition, another design of recursive digital differentiator is also obtained by optimizing the specified pole-zero locations of existing recursive digital differentiator of second-order system. Further, new designs of recursive digital integrators are obtained by inverting the transfer functions of designed recursive digital differentiators with suitable modifications. Thereafter, the zero-reflection approach is discussed and then applied to improve the phase responses of designed recursive digital differentiators and integrators. The beauty of finally obtained recursive digital differentiators and integrators is that they have nearly linear phase responses over wideband and also provide the choice of suitable recursive digital differentiator and integrator according to the importance of accuracy, bandwidth and the system simplicity

On the eigenfilter design method and its applications: a tutorial

The eigenfilter method for digital filter design involves the computation of filter coefficients as the eigenvector of an appropriate Hermitian matrix. Because of its low complexity as compared to other methods as well as its ability to incorporate various time and frequency-domain constraints easily, the eigenfilter method has been found to be very useful. In this paper, we present a review of the eigenfilter design method for a wide variety of filters, including linear-phase finite impulse response (FIR) filters, nonlinear-phase FIR filters, all-pass infinite impulse response (IIR) filters, arbitrary response IIR filters, and multidimensional filters. Also, we focus on applications of the eigenfilter method in multistage filter design, spectral/spacial beamforming, and in the design of channel-shortening equalizers for communications applications

Digital Filter Design Using Improved Artificial Bee Colony Algorithms

Digital filters are often used in digital signal processing applications. The design objective of a digital filter is to find the optimal set of filter coefficients, which satisfies the desired specifications of magnitude and group delay responses. Evolutionary algorithms are population-based meta-heuristic algorithms inspired by the biological behaviors of species. Compared to gradient-based optimization algorithms such as steepest descent and Newton’s like methods, these bio-inspired algorithms have the advantages of not getting stuck at local optima and being independent of the starting point in the solution space. The limitations of evolutionary algorithms include the presence of control parameters, problem specific tuning procedure, premature convergence and slower convergence rate. The artificial bee colony (ABC) algorithm is a swarm-based search meta-heuristic algorithm inspired by the foraging behaviors of honey bee colonies, with the benefit of a relatively fewer control parameters. In its original form, the ABC algorithm has certain limitations such as low convergence rate, and insufficient balance between exploration and exploitation in the search equations. In this dissertation, an ABC-AMR algorithm is proposed by incorporating an adaptive modification rate (AMR) into the original ABC algorithm to increase convergence rate by adjusting the balance between exploration and exploitation in the search equations through an adaptive determination of the number of parameters to be updated in every iteration. A constrained ABC-AMR algorithm is also developed for solving constrained optimization problems.There are many real-world problems requiring simultaneous optimizations of more than one conflicting objectives. Multiobjective (MO) optimization produces a set of feasible solutions called the Pareto front instead of a single optimum solution. For multiobjective optimization, if a decision maker’s preferences can be incorporated during the optimization process, the search process can be confined to the region of interest instead of searching the entire region. In this dissertation, two algorithms are developed for such incorporation. The first one is a reference-point-based MOABC algorithm in which a decision maker’s preferences are included in the optimization process as the reference point. The second one is a physical-programming-based MOABC algorithm in which physical programming is used for setting the region of interest of a decision maker. In this dissertation, the four developed algorithms are applied to solve digital filter design problems. The ABC-AMR algorithm is used to design Types 3 and 4 linear phase FIR differentiators, and the results are compared to those obtained by the original ABC algorithm, three improved ABC algorithms, and the Parks-McClellan algorithm. The constrained ABC-AMR algorithm is applied to the design of sparse Type 1 linear phase FIR filters of filter orders 60, 70 and 80, and the results are compared to three state-of-the-art design methods. The reference-point-based multiobjective ABC algorithm is used to design of asymmetric lowpass, highpass, bandpass and bandstop FIR filters, and the results are compared to those obtained by the preference-based multiobjective differential evolution algorithm. The physical-programming-based multiobjective ABC algorithm is used to design IIR lowpass, highpass and bandpass filters, and the results are compared to three state-of-the-art design methods. Based on the obtained design results, the four design algorithms are shown to be competitive as compared to the state-of-the-art design methods

Transformational leadership, job autonomy and role-breadth self-efficacy : their influence on proactive behaviour in entry-level graduate roles

This study investigated the model on the antecedents of proactive behaviour as identified by Den Hartog and Belschak (2012) within the context of entry-level graduate roles (n = 76). A survey was devised which included the use of a five-point Likert-type scale. It was then administered to graduates in entry-level roles in various industries in South Africa to measure the different variables stipulated by the model. When data was analysed, the results revealed that transformational leadership (inspirational), task-related role-breadth self-efficacy (RBSE), and people-related RBSE correlated significantly and positively with proactive behaviour. Transformational leadership (performance) and job autonomy obtained non-significant correlations with proactive behaviour. The results also revealed that job autonomy, task-related RBSE and people-related RBSE did not moderate the relationship between transformational leadership (inspirational or performance) and proactive behaviour. This meant that the display of transformational leadership did not lead to a significant increase in proactive behaviour in low autonomy, low RBSE situations or in high autonomy, high RBSE situations as hypothesised. The unique characteristics of entry-level graduate roles are highlighted by the study - the significance of this model on proactive behaviour in a general employee context potentially may not be relevant to a graduate context. The findings contribute towards research evidence on the development of proactive behaviour in entry-level graduate roles

DECISION MAKING PROCESSES FOR BIM SOFTWARE SELECTION IN THE U.S. A.E.C. INDUSTRY: DEVELOPING A UNIFIED, STREAMLINED FRAMEWORK.

The use of Building Information Modeling (BIM) techniques and tools continues to gain popularity in the Architecture, Engineering and Construction (AEC) industry as more companies in the various sectors are utilizing it in one form or another. In this research, the decision-making process of construction firms with respect to the selection of BIM software for use is investigated. Through one on one interviews and gathered survey responses, a framework mapping out the various paths the exist in the decision-making process are explored. This data is then used to form a framework for BIM software selection in the construction sector of the AEC industry in the United States

Model Reference Adaptive Control of Web Guides

The term web is used to describe materials which are typically manufactured in a roll-to-roll manner. A wide variety of materials such as textile, paper, plastics, composites and metals are manufactured in rolled form because roll-to-roll manufacture of materials is convenient for transport and storage, saves time and reduces costs. As the web is transported in the processing machinery, inherent machine misalignment and process induced disturbance cause lateral fluctuations. These lateral fluctuations, if not controlled, can result in inferior quality of the finished product. The primary focus of this research is on the development and implementation of adaptive control strategies for controlling the lateral fluctuations (lateral control or lateral guiding) in a web processing line. New performance measures which can better assist machine operators in diagnosing lateral behavior were also investigated. A novel model reference adaptive controller, which is referred to as the ``Guide Adaptive Controller'' (GAC), was developed for web guiding applications. The GAC was implemented on an experimental web line and the performance of the controller was compared with an existing industrial controller. The adaptive control strategy resulted in better performance compared to an industrial controller especially when used with difference web materials with opacity and gage variations. Compared to the existing industrial controller, the adaptive controller does not require re-tuning when the operating conditions change because the GAC adapts to process variations and attenuates disturbances. Additionally, the same adaptive controller can be used with different guide mechanisms. Two simplified approximations of GAC were also developed and implemented on an experimental web line in order to observe the adaptive behavior of the controllers. Based on these observations a systematic procedure for industrial implementation of the adaptive control strategy was developed. Extensive experimental results on commercial guides with different operating conditions and disturbances indicate that GAC can provide improved guiding performance when compared to an existing industrial controller. Therefore, GAC has a high potential to successfully replace existing guide controllers. A novel performance metric which provides a better characterization of the guiding performance when compared to existing metrics was developed. The developed metric is based on histograms. Commonly observed histograms were studied and their occurrence in web guiding applications were analyzed. The performance metric can be used as a diagnostic tool in the web processing industry to monitor the occurrence of different machine and process induced disturbances, and also to compare controllers.Mechanical & Aerospace Engineerin

Development of adaptive control methodologies and algorithms for nonlinear dynamic systems based on u-control framework

Inspired by the U-model based control system design (or called U-control system design), this study is mainly divided into three parts. The first one is a U-model based control system for unstable non-minimum phase system. Pulling theorems are proposed to apply zeros pulling filters and poles pulling filters to pass the unstable non-minimum phase characteristics of the plant model/system. The zeros pulling filters and poles pulling filters derive from a customised desired minimum phase plant model. The remaining controller design can be any classic control systems or U-model based control system. The difference between classic control systems and U-model based control system for unstable non-minimum phase will be shown in the case studies.Secondly, the U-model framework is proposed to integrate the direct model reference adaptive control with MIT normalised rules for nonlinear dynamic systems. The U-model based direct model reference adaptive control is defined as an enhanced direct model reference adaptive control expanding the application range from linear system to nonlinear system. The estimated parameter of the nonlinear dynamic system will be placement as the estimated gain of a customised linear virtual plant model with MIT normalised rules. The customised linear virtual plant model is the same form as the reference model. Moreover, the U-model framework is design for the nonlinear dynamic system within the root inversion.Thirdly, similar to the structure of the U-model based direct model reference adaptive control with MIT normalised rules, the U-model based direct model reference adaptive control with Lyapunov algorithms proposes a linear virtual plant model as well, estimated and adapted the particular parameters as the estimated gain which of the nonlinear plant model by Lyapunov algorithms. The root inversion such as Newton-Ralphson algorithm provides the simply and concise method to obtain the inversion of the nonlinear system without the estimated gain. The proposed U-model based direct control system design approach is applied to develop the controller for a nonlinear system to implement the linear adaptive control. The computational experiments are presented to validate the effectiveness and efficiency of the proposed U-model based direct model reference adaptive control approach and stabilise with satisfied performance as applying for the linear plant model

Newark College of Engineering Graduate Programs 1974-75 Academic Year

https://digitalcommons.njit.edu/coursecatalogs/1021/thumbnail.jp

New Jersey Institute of Technology Catalog of Graduate Programs 1975-1976 Academic Year

https://digitalcommons.njit.edu/coursecatalogs/1020/thumbnail.jp