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This paper presents the development of an autopilot system for self-driving an autonomous wheeled vehicle. A mathematical model, including the power allocation system, has been designed for a vehicle with three degrees of freedom. All model parameters have been identified through experimental trials. Heading and speed controllers were designed based on Lyapunov theory. These controllers have been further fine-tuned and tested through simulations to verify their robustness against external disturbances in the system dynamics. Moreover, this work proposes guidance approaches that allow the vehicle to track desired waypoints (line of sight (LOS)), and follow a given path (cross-track error) and a predefined trajectory with obstacle avoidance. A comparative study was also proposed in this paper, wherein we evaluate the paths followed by the vehicle using distinct yaw moment control techniques which are; differential thrust controller, solely relying on a steering controller, and a combination of both. To validate the effectiveness of the proposed autopilot system, we have conducted experimental tests, specifically focusing on waypoint tracking control (LOS method). The results underscore the system’s capabilities and its potential in real-world applications.

The Thrust vector control (TVC) is a method for controlling the angular velocity and attitude of aerial vehicles (AV) by manipulating the thrust direction of propulsion. This technology enhances maneuverability and allows for dynamic aerobatics at low speeds and near-zero airspeeds without stalling at high angles of attack (AOA). As the aerodynamic control surfaces are ineffective for vehicles operating outside the atmosphere, TVC is a suitable technique for these applications. To design a control system for AVs utilizing TVC, an accurate mathematical model is essential to simulate flight parameters and optimize the control gains. This work presents a complete six degrees-of-freedom (6-DOF) high-fidelity simulation model of a thrust vector control aerial vehicle (TVC-AV). The nonlinear model is developed by dividing the mathematical representation into five submodules, including the geometrical model, the actuation model that was experimentally identified, and an aerodynamic model that was validated through semi-empirical techniques, computational fluid dynamics (CFD), and wind-tunnel experiments; in addition, the propulsion model’s characteristics are identified through experimentation, and the atmospheric model is based on International Standard Atmosphere (ISA) values. The integrated model was implemented in MATLAB^Ⓡ (Simulink) that provides a foundation for designing effective flight controllers and guidance systems.

Circuits with diverse electrical behavior are often placed in close physical proximity in order to achieve high-levels of on-chip integration. The activity of certain types of circuits can generate harmful interference, and degrade the performance of the system through electromagnetic coupling. Considerable effort in system-on-a-chip implementations is in fact related to technology and architectural considerations for minimizing this interference. This is especially the case in systems that have exacting requirements on the dynamic range such as those for wireless applications.

In this paper, we will discuss the evolution of techniques for modeling and analyzing these sources of noise generation and interference. We will provide a physical description of the problem. Techniques for extraction of electrical models to represent the media that support these noise sources will be covered. Macromodeling techniques will be discussed. Finally we will introduce the concept of functional modeling of circuit functions and present such a model for an integrated flash analog-to-digital converter.

A new modeling and parameter extraction methodology to represent the parasitic effects associated with shielded test structures is presented in this paper. This methodology allows to accurately account for the undesired effects introduced by the test fixture when measuring on-wafer devices at high frequencies. Since the proposed models are based on the physical effects associated with the structure, the obtained parameters allow the identification of the most important parasitic components, which lead to potential measurement uncertainty when characterizing high-frequency devices. The proposed methodology is applied to structures fabricated on different metal levels in order to point out the advantages and disadvantages in each case. The validity of the modeling and characterization methodology is verified by achieving excellent agreement between simulations and experimental data up to 50 GHz.

A comprehensive SPICE model is developed for single photon avalanche diodes (SPADs). The model simulates both the static and dynamic behaviors of SPADs. Parameters of the model were extracted form experimental data obtained from SPADs designed and fabricated in a standard 0.5μm CMOS process. In this model, the resistive behavior of the device was modeled with an exponential function. Moreover, the device simulated response to incident optical power stimulation is modeled. Experimentally extracted parameters were incorporated into the model, and simulation results agreed with the experimental data.

As Bayesian networks become widely accepted as a normative formalism for diagnosis based on probabilistic knowledge, they are applied to increasingly larger problem domains. These large projects demand a systematic approach to handle the complexity in knowledge engineering. The needs include modularity in representation, distribution in computation, as well as coherence in inference. Multiply Sectioned Bayesian Networks (MSBNs) provide a distributed multiagent framework to address these needs.

According to the framework, a large system is partitioned into subsystems and represented as a set of related Bayesian subnets. To ensure exact inference, the partition of a large system into subsystems and the representation of subsystems must follow a set of technical constraints. How to satisfy these goals for a given system may not be obvious to a practitioner. In this paper, we address three practical modeling issues.

We propose a method of description and modeling of complex symmetrical images, which can be used for the synthesis of ornamental patterns. Our approach allows considerable memory reduction for storing symmetrical images and considerable time reduction for their synthesis. Our algorithms for ornamental patterns synthesis suggest the design of a special purpose ornamental patterns editor which can store and synthesize symmetrical images.

A novel methodology is proposed for the development of neural network models for complex engineering systems exhibiting nonlinearity. This method performs neural network modeling by first establishing some fundamental nonlinear functions from a priori engineering knowledge, which are then constructed and coded into appropriate chromosome representations. Given a suitable fitness function, using evolutionary approaches such as genetic algorithms, a population of chromosomes evolves for a certain number of generations to finally produce a neural network model best fitting the system data. The objective is to improve the transparency of the neural networks, i.e. to produce physically meaningful "white box" neural network model with better generalization performance. In this paper, the problem formulation, the neural network configuration, and the associated optimization software are discussed in detail. This methodology is then applied to a practical real-world system to illustrate its effectiveness.

In the past years, research in eye tracking development and applications has attracted much attention and the possibility of interacting with a computer employing just gaze information is becoming more and more feasible. Efforts in eye tracking cover a broad spectrum of fields, system mathematical modeling being an important aspect in this research. Expressions relating to several elements and variables of the gaze tracker would lead to establish geometric relations and to find out symmetrical behaviors of the human eye when looking at a screen. To this end a deep knowledge of projective geometry as well as eye physiology and kinematics are basic. This paper presents a model for a bright-pupil technique tracker fully based on realistic parameters describing the system elements. The system so modeled is superior to that obtained with generic expressions based on linear or quadratic expressions. Moreover, model symmetry knowledge leads to more effective and simpler calibration strategies, resulting in just two calibration points needed to fit the optical axis and only three points to adjust the visual axis. Reducing considerably the time spent by other systems employing more calibration points renders a more attractive model.

One classic example of a binary classifier is one which employs the mean and standard deviation of the data set as a mechanism for classification. Indeed, principle component analysis has played a major role in this effort. In this paper, we propose that one should also include skew in order to make this method of classification a little more precise. One needs a simple probability distribution function which can be easily fit to a data set and use this pdf to create a classifier with improved error rates and comparable to other classifiers.

The concealed microcracks in shield tunnel lining present the characteristics of being of small size, unknown shape, and are difficult to detect. Based on the finite-difference time domain (FDTD) approach, this study proposed a new construction method of a refined grid accommodating and combining the variable shapes of microcracks, and capable of designing cross type, mesh type, and wave type microcrack models. The proposed new method also configured steel bars in the models to simulate actual engineering conditions, and characteristic response images of the models under different working conditions were obtained using ground penetrating radar (GPR) technology, which were then compared and analyzed to identify the imaging characteristics and differences of microcracks with variable geometric shapes. The waveform, amplitude, and time span of the characteristic single channel signal were furthermore studied. The results showed that the new method could successfully simulate the GPR characteristic response images of 0.5mm microcracks of diverse geometric shapes. When the microcracks were wavy, their real shape could only be determined after signal pre-processing; the density and quantity of steel bars directly affected the appearance of microcrack characteristic signals; the greater the density and quantity of steel bars, the greater the interference on the waveform, amplitude, and time-frequency range of electromagnetic wave signals; a special correlation existed between the maximum mean root square value of the amplitude and the single channel signal of the cracks. Moreover, the finding that the extension in time and distance in the GPR time distance profile intersected with the cracks was deemed potentially to provide fresh insights into identifying the characteristic points of the cracks in the GPR images. The new method proposed in this study successfully obtained the GPR numerical simulation images and characteristic signals of microcracks with variable geometric shapes. Through the processing and analysis of the characteristic response signals of microcracks, the conclusions obtained were considered to provide an interpretation basis for the detection of microcracks in practical engineering.

Medical imaging is a powerful mean to access dynamic function of 3D deformable organs of the body. Due to the flow of incoming data, multiresolution methods on parallel computers is the only way to achieve complex processings in reasonable time. We present an active pyramid to model dynamic volumes. This pyramid is built on the first volume of a sequence and contains a binary model of the objects of interest. Previous knowledge is introduced within this binary model. The structure of the pyramid is rigid, but its main interest is that its components are deformed to fit the data using energetical constraints. A multiresolution algorithm based on self-organizing maps is then applied to deform the model through time. This algorithm matches the different levels of the pyramid in a coarse to fine approach. The output of the matching process is the field of deformation, modeling the transformations. This pyramid is applied to real data in the result section. The rigid structure of the pyramid is suitable for massively parallel architectures.

Reduction of power dissipation in digital circuits is a subject of research in industry and academia. A major component of power dissipation in modern microprocessors is due to their large interconnect networks which are responsible for the distribution of power and clocks as well as for the intra-chip communication. Communication is realized by data and address buses. In this paper we (i) discuss an analytical model for energy estimation in deep submicron buses, (ii) present statistical energy measures based on the analytical model, (iii) derive the energy limits of communication through buses, (iv) and introduce energy efficiency measures of communication.

The complexity of modern embedded systems requires a revised and systematic approach to efficient and concurrent management of hardware (HW) and software (SW) parts in a codesign process. In order to optimally meet the ever-increasing design requirements and at the same time leverage design productivity, higher level aspects need to be addressed before worrying about the HW/SW boundary. This paper deals with high-level aspects of system-level modeling and provides modeling extension, from which contemporary related methodologies can greatly benefit. High-level aspects, their influence on the entire design flow, and systematic integration into the codesign environment are presented. An approach is proposed with a higher level of abstraction that helps bridge the gap between informal and formal system specifications. Higher level design decisions are enabled, avoiding premature ad hoc design decisions. Applicability of the proposed high-level codesign concepts is illustrated with a case study.

This paper presents a simplified analysis of a generalized cycloconverter and suggests a new method for the estimation of the cycloconverter period as a function of the control mode. The paper presents generalized theoretical results supported by computer simulations and demonstrated by examples.

This paper offers a new approach to analyses of cycloconverter operation. The difference equations describing the cycloconverters' transient and steady-state operating regimes are derived. Theoretical predictions were validated by a computer program which calculated the load current of different cycloconverter topologies using the proposed methodology. The calculated and experimental results are compared and found to be in good agreement.

With higher operating frequencies, transmission lines are required to model global on-chip interconnects. In this paper, an accurate and efficient solution for the transient response at the far end of a transmission line based on a direct pole extraction of the system is proposed. Closed form expressions of the poles are developed for two special interconnect systems: an RC interconnect and an RLC interconnect with zero driver resistance. By performing a system conversion, the poles of an interconnect system with general circuit parameters are solved. The Newton–Raphson method is used to further improve the accuracy of the poles. Based on these poles, closed form expressions for the step and ramp response are determined. Higher accuracy can be obtained with additional pairs of poles. The computational complexity of the model is proportional to the number of pole pairs. With two pairs of poles, the average error of the 50% delay is 1% as compared with Spectre simulations. With ten pairs of poles, the average error of the 10%-to-90% rise time and the overshoots is 2% and 1.9%, respectively. Frequency dependent effects are also successfully included in the proposed method and excellent match is observed between the proposed model and Spectre simulations.

In this paper, we present a new method for characterization of radio frequency Power Amplifier (PA) in the presence of nonlinear distortions which affect the modulated signal in Radiocommunication transmission system. The proposed procedure uses a gray box model where PA dynamics are modeled with a MIMO continuous filter and the nonlinear characteristics are described as general polynomial functions, approximated by means of Taylor series. Using the baseband input and output data, model parameters are obtained by an iterative identification algorithm based on Output Error method. Initialization and excitation problems are resolved by an association of a new technique using initial values extraction with a multi-level binary sequence input exciting all PA dynamics. Finally, the proposed estimation method is tested and validated on experimental data.

In this paper, we present a new method for the modeling and characterization of oscillator circuit with a Van Der Pol (VDP) model using parameter identification. We also discussed and investigated the problem of estimation in nonlinear system based on time domain data. The approach is based on an appropriate state space representation of Van der Pol oscillator that allows an optimal parameter estimation. Using sampled output voltage signal, model parameters are obtained by an iterative identification algorithm based on Output Error method. Normalization issues are fixed by an appropriate transformation allowing a quickly global minimum search. Finally, the proposed estimation method is tested and validated using simulation data from a 1 GHz oscillator circuit in GaAs technology.

The paper proposes a unified switch model for the analysis of circuits with ideal switches. The model is unique and valid for all states of switches. The developed model is based on modified nodal analysis (MNA) that exploits an efficient algorithm developed for linear active circuits. The analysis with the new switch model requires only one topology and uses the uniform system equations regardless of states of switches. The system equations and the states of switches are updated by control variables, used in the model. There are no restrictions on circuit topology and switch connections. The switches can be both externally and internally controlled. The inconsistent initial value problem and Dirac delta impulses occurring because of ideal switch are discussed in detail. Two examples are given concerning the analysis of circuits with ideal switch.