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Search Results: 1 - 10 of 15662 matches for " Stochastic Shooting Point Methods "
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Temporal Prediction of Aircraft Loss-of-Control: A Dynamic Optimization Approach  [PDF]
Chaitanya Poolla, Abraham K. Ishihara
Intelligent Control and Automation (ICA) , 2015, DOI: 10.4236/ica.2015.64023
Abstract: Loss of Control (LOC) is the primary factor responsible for the majority of fatal air accidents during past decade. LOC is characterized by the pilot’s inability to control the aircraft and is typically associated with unpredictable behavior, potentially leading to loss of the aircraft and life. In this work, the minimum time dynamic optimization problem to LOC is treated using Pontryagin’s Maximum Principle (PMP). The resulting two point boundary value problem is solved using stochastic shooting point methods via a differential evolution scheme (DE). The minimum time until LOC metric is computed for corresponding spatial control limits. Simulations are performed using a linearized longitudinal aircraft model to illustrate the concept.
Noise-Dependent Stability of the Synchronized State in a Coupled System of Active Rotators  [PDF]
Sebastian F. Brandt, Axel Pelster, Ralf Wessel
World Journal of Condensed Matter Physics (WJCMP) , 2011, DOI: 10.4236/wjcmp.2011.13014
Abstract: We consider a Kuramoto model for the dynamics of an excitable system consisting of two coupled active rotators. Depending on both the coupling strength and the noise, the two rotators can be in a synchronized or desynchronized state. The synchronized state of the system is most stable for intermediate noise intensity in the sense that the coupling strength required to desynchronize the system is maximal at this noise level. We evaluate the phase boundary between synchronized and desynchronized states through numerical and analytical calculations.
Network Reliability Analysis as a Tool to Guide Investment Decisions in Distributed Generation  [PDF]
Samson Ttondo Ssemakalu, Milton Edimu, Jonathan Serugunda, Patrick Kabanda
Journal of Power and Energy Engineering (JPEE) , 2018, DOI: 10.4236/jpee.2018.69008
Abstract: Distributed Generation (DG) in any quantity is relevant to supplement the available energy capacity based on various locations, that is, whether a site specific or non-site specific energy technology. The evacuation infrastructure that delivers power to the distribution grid is designed with appropriate capacity in terms of size and length. The evacuation lines and distribution network however behave differently as they possess inherent characteristics and are exposed to varying external conditions. It is thus feasible to expect that these networks behave stochastically due to fault conditions and variable loads that destabilize the system. This in essence impacts on the availability of the evacuation infrastructure and consequently on the amount of energy delivered to the grid from the DG stations. Reliability of the evacuation point of a DG is however not a common or prioritized criteria in the decision process that guides investment in DG. This paper reviews a planned solar based DG plant in Uganda. Over the last couple of years, Uganda has seen a significant increase in the penetration levels of DG. With a network that is predominantly radial and experiences low reliability levels, one would thus expect reliability analysis to feature significantly in the assessment of the proposed DG plants. This is however not the case. This paper, uses reliability analysis to assess the impact of different evacuation options of the proposed DG plant on its dispatch levels. The evacuation options were selected based on infrastructure options in other locations with similar solar irradiances as the planned DG location. Outage data were collected and analyzed using the chi square method. It was found to be variable and fitting to different Probability Distribution Functions (PDF). Using stochastic methods, a model that incorporates the PDFs was developed to compute the reliability indices. These were assessed using chi square and found to be variable and fitting different PDFs as well. The viability of the project is reviewed based on Energy Not Supplied (ENS) and the anticipated project payback periods for any considered evacuation line. The results of the study are also reviewed for the benefit of other stakeholders like the customers, the utility and the regulatory body.
On Implicit Algorithms for Solving Variational Inequalities  [PDF]
Eman Al-Shemas
Applied Mathematics (AM) , 2013, DOI: 10.4236/am.2013.41018
Abstract:

This paper presents new implicit algorithms for solving the variational inequality and shows that the proposed methods converge under certain conditions. Some special cases are also discussed.

Stochastic Analysis of Low-Cost Single-Frequency GPS Receivers  [PDF]
Mohamed Elsayed Elsobeiey
Positioning (POS) , 2016, DOI: 10.4236/pos.2016.73009
Abstract: Typically, dual-frequency geodetic grade GNSS receivers are utilized for positioning applications that require high accuracy. Single-frequency high grade receivers can be used to minimize the expenses of such dual-frequency receivers. However, user has to consider the resultant positioning accuracy. Since the evolution of low-cost single-frequency (LCSF) receivers is typically cheaper than single-frequency high grade receivers, it is possible to obtain comparable positioning accuracy if the corresponding observables are accurately modelled. In this paper, two LCSF GPS receivers are used to form short baseline. Raw GPS measurements are recorded for several consecutive days. The collected data are used to develop the stochastic model of GPS observables from such receivers. Different functions are tested to determine the best fitting model which is found to be 3 parameters exponential decay function. The new developed model is used to process different data sets and the results are compared against the traditional model. Both results from the newly developed and the traditional models are compared with the reference solution obtained from dual-frequency receiver. It is shown that the newly developed model improves the root-mean-square of the estimated horizontal coordinates by about 10% and improves the root-mean-square of the up component by about 39%.
Production Planning of a Failure-Prone Manufacturing/Remanufacturing System with Production-Dependent Failure Rates  [PDF]
Annie Francie Kouedeu, Jean-Pierre Kenné, Pierre Dejax, Victor Songmene, Vladimir Polotski
Applied Mathematics (AM) , 2014, DOI: 10.4236/am.2014.510149
Abstract:

This paper deals with the production-dependent failure rates for a hybrid manufacturing/remanufacturing system subject to random failures and repairs. The failure rate of the manufacturing machine depends on its production rate, while the failure rate of the remanufacturing machine is constant. In the proposed model, the manufacturing machine is characterized by a higher production rate. The machines produce one type of final product and unmet demand is backlogged. At the expected end of their usage, products are collected from the market and kept in recoverable inventory for future remanufacturing, or disposed of. The objective of the system is to find the production rates of the manufacturing and the remanufacturing machines that would minimize a discounted overall cost consisting of serviceable inventory cost, backlog cost and holding cost for returns. A computational algorithm, based on numerical methods, is used for solving the optimality conditions obtained from the application of the stochastic dynamic programming approach. Finally, a numerical example and sensitivity analyses are presented to illustrate the usefulness of the proposed approach. Our results clearly show that the optimal control policy of the system is obtained when the failure rates of the machine depend on its production rate.

VALIDACIóN DE UN ALGORITMO HíBRIDO DEL PSO CON EL MéTODO SIMPLEX Y DE TOPOLOGíA DE EVOLUCIóN PARAMéTRICA
CORREA,RODRIGO; BEGAMBRE,OSCAR; CARRILLO E.,JULIO C.;
DYNA , 2011,
Abstract: this paper describes some of the most important aspects related to the numerical experimentation of a hybrid of the algorithm pso (particle swarm optimization) with the traditional modified simplex method of nelder-mead. the hybridization of these two techniques of optimization without restrictions was carried out with a topology that allows to optimize in each iteration the parameters of the algorithm pso using the modified simplex method. numerical experiments with this hybrid algorithm were carried out and applied to several of typical test functions to establish its effectiveness. the results obtained were compared with the simplex and the quadratic methods, which turned out to be very satisfactory since the point of view of their repeatability and reproducibility, although the time of computation was considerably longer. it stands out itself, nevertheless, that the precision of the hybrid algorithm was a hundred percent in all the trials for the test functions selected.
A New Preconditioner with Two Variable Relaxation Parameters for Saddle Point Linear Systems with Highly Singular(1,1) Blocks  [PDF]
Yuping Zeng, Chenliang Li
American Journal of Computational Mathematics (AJCM) , 2011, DOI: 10.4236/ajcm.2011.14030
Abstract: In this paper, we provide new preconditioner for saddle point linear systems with (1,1) blocks that have a high nullity. The preconditioner is block triangular diagonal with two variable relaxation paremeters and it is extension of results in [1] and [2]. Theoretical analysis shows that all eigenvalues of preconditioned matrix is strongly clustered. Finally, numerical tests confirm our analysis.
Adaptation in Stochastic Dynamic Systems—Survey and New Results I  [PDF]
Innokentiy V. Semushin
Int'l J. of Communications, Network and System Sciences (IJCNS) , 2011, DOI: 10.4236/ijcns.2011.41002
Abstract: This paper surveys the field of adaptation mechanism design for uncertainty parameter estimation as it has developed over the last four decades. The adaptation mechanism under consideration generally serves two tightly coupled functions: model identification and change point detection. After a brief introduction, the pa-per discusses the generalized principles of adaptation based both on the engineering and statistical literature. The stochastic multiinput multioutput (MIMO) system under consideration is mathematically described and the problem statement is given, followed by a definition of the active adaptation principle. The distinctive property of the principle as compared with the Minimum Prediction Error approach is outlined, and a plan for a more detailed exposition to be provided in forthcoming papers is given.
Stochastic Model of a Cold-Stand by System with Waiting for Arrival & Treatment of Server  [PDF]
Rohtash K. Bhardwaj, Ravinder Singh
American Journal of Operations Research (AJOR) , 2016, DOI: 10.4236/ajor.2016.64031
Abstract: The service facility or server is the key constituent to keep a system operational for desired period of time. As any eventuality with the system necessitates immediate presence of it (server) so the time point of arrival and treatment of server significantly affects the system performance. This paper works out the steady state behavior of a cold standby system equipped with two similar units and a server with elapsed arrival and treatment times following general probability distributions. It practices the theory of semi-Markov processes, regenerative point technique and Laplace transforms to derive the expressions for state transition probabilities, mean sojourn times, mean time to system failure, system availability, server busy period and expected frequencies of repairs and treatments. The profit function is also developed taking different costs and revenue in to account. For tracing wider applicability of the model for different reliability and cost-effective systems, a particular case study is also presented as an illustration.
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