Browsing by Author "Bikdash, Marwan"

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    Analysis and filtering of time-varying signals
    Bikdash, Marwan (Virginia Polytechnic Institute and State University, 1988)
    The characterization, analysis and filtering of a slowly time-varying (STV) deterministic signal are considered. A STV signal is characterized as a sophisticated signal whose windowed sections are elementary signals. Mixed time-frequency representations (MTFRs) such as the Wigner distribution (WD), the Pseudo-Wigner distribution (PWD), the Short-time Fourier transform (STFT) and the optimally smoothed Wigner distribution (OSWD) used in analyzing STV signals are analyzed and compared. The OSWD is shown to perform satisfactorily even if the signals are amplitude modulated. The OSWD is shown to yield the exact instantaneous frequency for STV signals having quadratic phase: and to have a minimal and meaningful Bandwidth (BW) that does not depend on the slope of the instantaneous frequency curve in the time-frequency plane, unlike the BW of the spectrogram. We also present some contributions to the ongoing debate addressing the issue of choosing the MTFR that is best suited to the analysis of STV signals. Using analytical and experimental results, the performances of the different MTFRs are compared, and the conditions under which a given MTFR performs better are considered. The filtering of a signal from a noise-corrupted measurement, and the decomposition of a STV signal into its components in the presence of noise, are considered. These two related problems have been solved through masking the MTFRs of the measured signal. This approach has been successfully used in the case of the WD, PWD and the STFT. We propose extending the use of this approach to the OSWD. An equivalent time-domain implementation based on linear shift-variant (LSV) filters is derived and fully analyzed. It is based on the concept of local nonstationarity cancellation. The proposed filter is shown to have a superior performance when compared to the filter based on masking the STFT. The sensitivity of the filter is studied. The filter ability to suppress white noise and to decompose a STV signal into its components is analyzed and illustrated.
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    A Meso-Scale Petri Net Model to Simulate a Massive Evacuation along the Highway System
    Qabaja, Hamzeh; Ashqer, Mujahid I.; Bikdash, Marwan; Ashqar, Huthaifa I. (MDPI, 2023-03-02)
    Natural disasters may require that the residents of the affected area be evacuated immediately using a potentially damaged infrastructure. In this paper, we developed a mesoscopic simulation modeling approach for modeling traffic flow over a large geographic area and involving many people and vehicles. This study proposed a novel model, namely, Colored Deterministic and Stochastic Petri Net (CDSPN), which can mesoscopically provide an individual vehicular traffic dynamic. Each vehicle has a unique identifier, speed, distance to go, assigned target, and a specific route. It also proposed a method to automatically construct a Petri net model that represents the evacuation of Guilford County (GC), North Carolina, from standard Geographic Information Systems (GIS) shapefiles. We showed that this model could successfully simulate the dynamics of hundreds of thousands of vehicles moving on the highway system towards pre-specified safe targets such as medical facilities, exit points, or designated shelters. The vehicles are assumed to obey traffic laws, and the model reflects the complexities of the actual highway systems. The developed software can be used to analyze in reasonable detail the evacuation process, such as identifying bottlenecks and estimating efficiency and the time needed. An explicit list of 18 assumptions is stated and discussed. The Petri net for GC evacuation is reasonably massive, consisting of 35,476 places and 43,540 transitions with 531,595 colored tokens, where each token represents a vehicle in GC. We simulate the evacuation, develop statistics, and evaluate patterns of evaluation. We found that the evacuation took about 8.7 h.
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    Time-optimal and saturating controls with application to flexible structures
    Bikdash, Marwan (Virginia Tech, 1993-04-27)
    This dissertation is concerned with developing new time-optimal control techniques for higher-order linear and weakly nonlinear systems. As an application, we consider the simultaneous slewing and vibration suppression of a flexible beam, possibly with a tip mass. This application arises in the design of large space structures and flexible lightweight and accurate robotic arms. The solution of the soft-constrained time-optimal control problem is expressed in terms of the controllability Grammian. The properties of the open-loop solution are studied. A closed-loop control algorithm, which takes into account the mUltiplicity of extremal solutions, is then developed. The algorithm is based on the concept of continuation and reduces the computational complexity by as much as two orders of magnitude when compared to the brute-force approach. The amplitude of the soft-constrained time-optimal control is found to saturate as the state norm becomes large, thus suggesting a simpler but suboptimal feedback implementation. We develop and discuss the concept of saturating controls for linear systems, and we develop a design approach that generates a family of saturating control laws in which the speed of the response and amount of available control action can be explicitly traded off. The soft-constrained time-optimal cheap-control problem is formulated and solved using singular-perturbation theory. The solution procedures are illustrated with an example solved using the MACSYMA symbolic manipulation language. Regular-perturbation theory is then used to find the open-loop hard-constrained time-optimal control for a class of weakly nonlinear systems. The control is found by solving a nonlinear two-point boundary value problem (TPBVP) characterizing the control of the linearized system, and a second linear TPBVP.