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Iterative computing algorithms implemented in FPGA using ALTERA_CORDIC library as an example

Procedia Computer Science 2024年 246卷 2380-2389页

作者： Paweł Poczekajło Koszalin University of Technology. ul Śniadeckich 2 75-453 Koszalin Poland

The article discusses the general issues of implementing pipelined and iterative algorithms. These are typical solutions for engineering algorithms implemented in hardware like reprogrammable systems. The authors focused on the implementation of such algorithms in field-programmable gate array (FPGA) circuits. Key aspects and advantages of pipelined processing were discussed. The focus was on an example CORDIC algorithm. Analyses of the iterative implementation using the ALTERA_CORDIC library were performed. Key parameters such as frequency and circuit occupancy were measured. Also, the obtained results were compared with the exact values - the errors were determined. Realizations based on 8-, 12- and 16-bits of fractional in fixed-position notation were analyzed.

关键词： iterative algorithms pipelined algorithms computing algorithms engineering computing CORDIC FPGA Altera library finite precision implementation occupation frequency

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Fast and Reliable Computation of Instantaneous Orbital Collision Probability

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2024年第8期47卷 1660-1673页

作者： Masson, Matthieu Arzelier, Denis Brehard, Florent Joldes, Mioara Salvy, Bruno Toulouse Univ ROC Team LAAS CNRS 07 Ave Colonel Roche F-31400 Toulouse France Lille Univ Crystal Lab CNRS F-59655 Lille France ENS Ecole Normale Super INRIA Natl Inst Res Digital Sci & Technol LIP ENS Lyon F-69000 Lyon France

Because of the increasing number of objects in low Earth orbit, the fast and reliable estimation of the collision risk is an important challenge for spacecraft owners/operators. Among the available risk indicators, this paper focuses on computing the instantaneous probability of collision, which can be modeled as the integral of a three-dimensional Gaussian probability density function over a Euclidean ball. The authors propose an efficient and accurate method for evaluating this integral. It is based on the combination of two complementary strategies. For the first one, convergent series and numerical error bounds are computed. These bounds provide a tradeoff between the accuracy needed and the number of terms to compute. The second one, using divergent series, approximates the value of the integral with a good accuracy in most cases with only a few terms computed. Based on those two methods, a hybrid algorithm is tested on cases borrowed from the literature and compared against existing methods. Several numerical results and comparisons confirm both the efficiency and robustness of this paper's approach.

关键词： Active Satellites computing algorithms series expansions Space Vehicle Risk Assessment instantaneous collision probability long-term encounters Gaussian Mixture Models saddle-point method

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Optimal design of robust resilient automatic voltage regulators

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ISA TRANSACTIONS 2021年 108卷 257-268页

作者： Elsisi, M. Soliman, M. Natl Taiwan Univ Sci & Technol Ctr Cyber Phys Syst Innovat Ind Implementat Ctr 4 0 Taipei 10607 Taiwan Benha Univ Fac Engn Shoubra Elect Engn Dept 108 Shoubra St Cairo 11241 Egypt

Uncertainties in the plant model parameters and perturbations in the controller gains imposed by implementation errors represent a challenge to ensure robust stability and controller non-fragility simultaneously. Optimal design of robust non-fragile proportional-integral-derivative (PID) controller is presented for an automatic voltage regulator (AVR). The PID design relies basically on Kharitonov theorem and optimization by future search algorithm (FSA). The proposed algorithm has low computational complexity and fast convergence rate because it utilizes both local and global search methods. Further, FSA can improve the exploration characteristic and prevent trapping in local optima by updating its random initial. The PID controller is optimized by FSA to cope with expected parametric uncertainties of the plant model and tolerate its gain perturbations such that robust stability and controller non-fragility are simultaneously met. An interval plant model is suggested to account for model uncertainties where only eight extreme plants derived by Kharitonov theorem are considered in design. FSA-based PID optimization is constrained by the stability conditions of Kharitonov's plants derived using Routh-Hurwitz. A new figure-of-demerit (FoD) based performance index is suggested to enforce simultaneous minimization of the time domain specifications. The suggested objective function is represented by a weighted sum of FoD of nominal response and the sum of reciprocals of the perturbation radii of PID gains. The output results of the recommended design are compared to that of artificial bee colony (ABC) algorithm and teaching-learning based optimization (TLBO) algorithm, multi-objective extremal optimization (MOEO), and non-dominated sorting genetic algorithm II (NSGA II). The results can confirm better response of the suggested technique measured up to other techniques where robustness and non-fragility are simultaneously ensured. (c) 2020 ISA. Published by Elsevier Ltd.

关键词： computing algorithms Robustness Resiliency Uncertain systems Kharitonov's theorem

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How chaos theory improves Data Mining in research by means of ALEV

How chaos theory improves Data Mining in research by means o...

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Canadian Conference on Electrical and Computer Engineering

作者： Toplak, Werner Arsenal Research

ISBN: (纸本)9781424416424

In this paper a method for data reduction is introduced. Aspects of Lyapunov, Entropy and Variance (ALEV) provide an approach for mining large stocks of time series data. Methods of Artificial Intelligence (AI) offer two different ways for modeling observation data: The recall times of Expert Systems (XPS) depend on the size of a knowledge base. Connectionist approaches like the Multi-Layer Perceptron (MLP) have to be trained with a representative data set for mapping system behavior. While the duration of this learning process also depends on the amount of representative data the recall times are very short. On basis of the Mackey-Glass function a technique for Visual Data Mining (VDM) is proposed. Performance tests on basis of real world traffic speed patterns from different observation time periods show that ALEV thins out large pattern stocks. Viability of Data Mining methods is increased and generalization quality remains the same.

关键词： computing algorithms database and Data Mining neural networks chaos theory performance evaluation

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Study of an Innovative Indoor Robotic Navigation Approach Based on Beacons and PSD

Study of an Innovative Indoor Robotic Navigation Approach Ba...

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International Conference on Frontiers of Sensors Technologies (ICFST)

作者： Wang Zhenxing Shanghai Second Polytech Univ Dept Comp Shanghai Peoples R China

ISBN: (纸本)9781510824652

In this paper, innovative indoor navigation methods have been proposed to meet the challenges in robotic navigation systems. The general positioning methods for robotic navigation include vision-based approaches, WIFI beacons, infrared beacons, ultrasonic beacons, etc. However, the common problem with these methods is their inaccuracy. Especially, improving the precision of robotic positioning mechanisms is the key to indoor navigation systems. This paper proposes an approach that combines the external rotating beacon with an internal rotation of position sensitive devices ( PSD) which are installed on the robot. While two infrared beams from an external beacon source are equally projected to both sides of the PSD, the robot's position can be calculated precisely. The high performance and accurate results can be achieved by optimizing the rotation aligning time, dividing the working area, and compensating errors with information fusion. In comparison with other generic approaches, this proposed innovative approach requires less computing resources and is easier to implement due to its much lower complexity for the computing algorithms.

关键词： positioning methods robotic navigation computing algorithms Beacons Power spectral density PSD gene PREVENTION OF SIGNIFICANT DETERIORATION infrared beams Navigation systems compensating errors navigation Work area Robot Information fusion Internal rotation

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Reliable computing in estimation of variance components

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JOURNAL OF ANIMAL BREEDING AND GENETICS 2008年第6期125卷 363-370页

作者： Misztal, I. Univ Georgia Athens GA 30602 USA

The purpose of this study is to present guidelines in selection of statistical and computing algorithms for variance components estimation when computing involves software packages. For this purpose two major methods are to be considered: residual maximal likelihood (REML) and Bayesian via Gibbs sampling. Expectation-Maximization (EM) REML is regarded as a very stable algorithm that is able to converge when covariance matrices are close to singular, however it is slow. However, convergence problems can occur with random regression models, especially if the starting values are much lower than those at convergence. Average Information (AI) REML is much faster for common problems but it relies on heuristics for convergence, and it may be very slow or even diverge for complex models. REML algorithms for general models become unstable with larger number of traits. REML by canonical transformation is stable in such cases but can support only a limited class of models. In general, REML algorithms are difficult to program. Bayesian methods via Gibbs sampling are much easier to program than REML, especially for complex models, and they can support much larger datasets;however, the termination criterion can be hard to determine, and the quality of estimates depends on a number of details. computing speed varies with computing optimizations, with which some large data sets and complex models can be supported in a reasonable time;however, optimizations increase complexity of programming and restrict the types of models applicable. Several examples from past research are discussed to illustrate the fact that different problems required different methods.

关键词： computing algorithms MCMC REML variance components

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On the Application of a Long-Short-Term Memory Deep Learning Architecture for Aircraft Dynamic Loads Monitoring

On the Application of a Long-Short-Term Memory Deep Learning...

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AIAA Science and Technology Forum and Exposition (AIAA SciTech)

作者： Candon, Michael Esposito, Marco Levinski, Oleg Carrese, Robert Joseph, Nish Koschel, Stephan Marzocca, Pier RMIT Univ Sch Engn Aerosp Engn & Aviat Melbourne Vic Australia Def Sci & Technol Grp Aerosp Div Fishermans Bend Vic Australia

ISBN: (数字)9781624105951

ISBN: (纸本)9781624105951

For aircraft, the contemporary approach to Structural Health Monitoring (SHM), known as Prognostics and Health Management (PHM), is driven by condition-based maintenance and structural health prognosis, where pre-emptive planning of maintenance and procurement of parts will allow for maintenance and sustainment practices to be optimized, offering major beneficial fiscal and safety implications for both the civilian and defense aerospace sectors. Despite some current reluctances in industry, AI-based technologies, such as, deep learning, may have a major role to play in the contemporary aircraft PHM system. With this in mind, this paper aims to serve as an important contribution to their broader adoption at this critical time in aircraft SHM, showing how the relatively simplistic implementation of the state-of-the-art in deep learning can change the entire potential capability of the aircraft SHM system. The Bidirectional Long Short-Term Memory (BiLSTM) deep neural architecture is introduced as an indirect Multi-Input Single-Output (MISO) modeling strategy for poorly conditioned (weak MISO coherence) load predictions. It is shown that a single fixed-architecture BiLSTM strategy can be used as a general purpose strategy for MISO modeling of the loads, with a prediction accuracy that is of an unprecedented levels of fidelity and robustness/consistency. More specifically, the previous use of more traditional strategies, such as, regression models and even standard artificial neural networks, has only been viable in terms of yielding a statistically reasonable distribution of extrema (from generally very poor MISO time-series models). Hence, in this research campaign (ongoing for the past four years), the introduction of the deep learning strategy has changed the paradigm by which the weakly coherent MISO airframe loads are modeled, where the high-fidelity point-to-point time-series predictions has introduced the viability of contemporary fatigue assessment algorithms.

关键词： Fleet Aircraft Artificial Neural Network Health Monitoring Technology Airframes Structural Fatigue Power Spectral Density Wing Root computing algorithms Artificial Intelligence Aerospace Industry

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Reduced order modeling of a flow past a cylinder using sparse coding 55

Reduced order modeling of a flow past a cylinder using spars...

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55th AIAA Aerospace Sciences Meeting

作者： Deshmukh, Rohit McNamara, Jack J. Department of Mechanical and Aerospace Engineering The Ohio State University ColumbusOH43210 United States

ISBN: (数字)9781624104473

ISBN: (纸本)9781624104473

Galerkin projection is a commonly used reduced order modeling approach;however, stability and accuracy of the resulting reduced order models are highly dependent on the modal decomposition technique used. In particular, deriving stable and accurate reduced order models from turbulent flowfields is challenging due to the presence of multi-scale phenomenon that cannot be ignored and are not well captured using the ubiquitous Proper Orthogonal Decomposition (POD). A truncated set of the proper orthogonal modes is biased towards energy dominant, large-scale structures and results in overprediction of kinetic energy from the corresponding reduced order model. Recent study indicates that a sparse coding based modal decomposition approach yields multi-scale modes that are well-suited for constructing reduced order models of turbulent flow fields. Both the modal decomposition techniques are compared for a canonical problem of an incompressible flow past a stationary cylinder. Results indicate that Galerkin reduction of the governing equations using only a few sparse modes produces reasonably accurate predictions of second order statistics of the fluid flow. Additionally, the sparse modes based models are found to maintain balance between the production and dissipation of energy. Whereas, models constructed using the same numbers of proper orthogonal decomposition modes are found to perform poorly. © 2017 by R. Deshmukh and J. McNamara.

关键词： Kinetic Energy Incompressible Flow Fluid Flow Computational Fluid Dynamics Model Order Reduction Freestream Conditions Energy Production No Slip Condition Convection computing algorithms

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Biologically Inspired Model with Feature Selection for Target Recognition Using Biogeography-Based Optimization

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JOURNAL OF AEROSPACE INFORMATION SYSTEMS 2014年第7期11卷 433-446页

作者： Duan, Haibin Deng, Yimin Beihang Univ State Key Lab Virtual Real Technol & Syst Beijing 100191 Peoples R China

To detect salient ground targets precisely and rapidly during aerial reconnaissance, this paper describes a novel object recognition method based on the feature selection of a biologically inspired model and biogeography-based optimization. As a promising approach to object recognition, the biologically inspired model is a hierarchical system of building an increasingly complex and invariant feature representation, which closely follows the process of object recognition in the visual cortex. These scale-and position-tolerant features are constructed by alternating between a template-matching and a maximum-pooling operation. Because of the many patches extracted in the standard biologically inspired model, the random mechanism may extract patches from irrelevant parts of an image and consume a lot of time. In this work, a feature selection method is proposed based on a new population-based evolutionary algorithm called biogeography-based optimization to choose the proper set of patches with high accuracy of classification and recognition. A support vector machine classifier is used for evaluation of the fitness function in biogeography-based optimization and to calculate the recognition rate in testing. A series of experiments are conducted, and the comparative results demonstrate the feasibility and effectiveness of the approach.

关键词： Particle Swarm Optimization Support Vector Machine Aerial Reconnaissance Aeroplane Helicopters Aspect Ratio Optimization Algorithm Feedforward computing algorithms Automatic Target Recognition

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Partitioned component mode synthesis via a flexibility approach

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AIAA JOURNAL 2004年第6期42卷 1236-1245页

作者： Park, KC Park, YH Univ Colorado Ctr Aerosp Struct Boulder CO 80309 USA Univ Colorado Dept Aerosp Engn Sci Boulder CO 80309 USA Samsung Elect Co Ltd Suwon 443742 South Korea

A new flexibility-based component mode synthesis method is presented, which is derived by approximating the partitioned equations of motion that employ a localized method of Lagrange multipliers. The use of the localized Lagrange multipliers leads to, unlike the classical Lagrange multipliers, a linearly independent set of interface forces without any redundancies at multiply connected interface nodes. Hence, the resulting interface flexibility matrices are uniquely determined and well suited for the present method development. An attractive feature of the present method is its substructural mode selection criterion that is independent of loading conditions. Numerical experiments show that the present modal selection criterion is reliable and that the proposed flexibility-based component mode synthesis method performs well relative to the classical Craig-Bampton method in terms of accuracy and of its ability to include dominant substructural modes for simple plates and a relatively complex solid ring.

关键词： Lagrange Multipliers Three Dimensional Elements Structural Dynamics Parallel Computers Transient Response computing algorithms Structural Health Monitoring Sandia National Laboratories Structural Analysis Structural System

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