1 edition of **Robust Discrete Estimation of the Space Shuttle Main Engine** found in the catalog.

Robust Discrete Estimation of the Space Shuttle Main Engine

- 0 Want to read
- 37 Currently reading

Published
**1996**
by Storming Media
.

Written in English

- TEC002000

The Physical Object | |
---|---|

Format | Spiral-bound |

ID Numbers | |

Open Library | OL11852223M |

ISBN 10 | 1423579844 |

ISBN 10 | 9781423579847 |

Choose a custom storage class package by selecting a signal object class that the target package defines. For example, to apply custom storage classes from the built-in package mpt, select you use an ERT-based code generation target with Embedded Coder ®, custom storage classes do not affect the generated code.. If the class that you want does not appear in the Data Types: double | single. motor using discrete time optimal tracking controller. The model of the BLDC motor is expressed as discrete time equations. The optimal tracking controller based on the estimated states by using discrete time observer is designed to control. The effectiveness of the designed controller is shown via numerical and experimental results. 2.

Efficient Simulation and Integrated Likelihood Estimation in State Space Models Joshua C.C. Chan⁄ University of Queensland Ivan Jeliazkovy University of California, Irvine November Abstract We consider the problem of implementing simple and e–cient Markov chain Monte Carlo (MCMC) estimation algorithms for state space models. An Overview of Sequential Monte Carlo Methods for Parameter Estimation in General State-Space Models on a (measurable) space (Ω,F). The discrete-time process {Xn}n≥0 is a hidden (or latent) [14] for a book length review. A selection of these results that give useful.

To summarize, our main contributions are: A novel data-driven framework that combines multiple cues for ground plane estimation using learned models to adaptively weight per-frame observation covariances. Highly accurate, robust, scale-corrected and real-time monocular SFM File Size: 1MB. Specifying Discrete-Time Models. Control System Toolbox™ lets you create both continuous-time and discrete-time models. The syntax for creating discrete-time models is similar to that for continuous-time models, except that you must also provide a sample time (sampling interval in seconds).

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Robust Discrete Estimation of the Space Shuttle Main Engine by Jonathan Andrew Jensen B.S., Mechanical Engineering, United States Air Force Academy () Submitted to the Department of Aeronautics and Astronautics on in partial fulfillment of the requirements for the degree of Master of Science Abstract.

Download Citation | Robust discrete estimation of the space shuttle main engine | Thesis (M.S.)--Massachusetts Institute of Technology, Dept.

of Aeronautics and Astronautics, Includes. This is a final report on an analysis of the Space Shuttle Main Engine Program, a digital simulator code written in Fortran. The research was undertaken by the authors in ultimate support of future design studies of a shuttle life-extending Intelligent Control System (ICS).

These studies are to be conducted by NASA Lewis Space Research Center. This book takes a giant first step in presenting decision support tools and solution methods for generating robust decisions in a variety of interesting application environments.

Robust Discrete Optimization is a comprehensive mathematical programming framework for robust decision making. ON-LINE IMPLEMENTATION OF NONLINEAR PARAMETER ESTIMATION FOR THE SPACE SHUTTLE MAIN ENGINE Julia H.

Buckland* University of Cincinnati Cincinnati, Ohio Jeffrey L. Musgrave National Aeronautics and Space Administration Lewis Research Center Cleveland, Ohio and Bruce K.

Walker University of Cincinnati Cincinnati, Ohio The Space Shuttle’s Main Engine (SSME) was a highly innovative, high performance, liquid propelled rocket engine with a variable thrust and mixture ratio.

It was controlled electronically by an automatic system that could perform checkout, start, mainstage and shutdown functions. Ignited on the ground, the three engines on the orbital vehicle /5(13). Kouvelis and Yu proposed a framework for robust discrete optimization mini-mizing the worst case performance under a set of scenarios for the data.

(2) However, many problems become NP-hard in that framework. Bertsimas’ approach Bertsimas’ approach from the year has a. Robust estimation of simultaneous actuator and sensor faults is as follows.

In this section, we propose the use of the resulting filters RPF and RPIF to solve the robust estimation of simultaneous actuator and sensor faults problem.

We consider the same numerical example used in (Chen and Patton [5, 6]).Author: Feten Gannouni, Fayçal Ben Hmida. Robust 1-Median with Linear Edge Distances Observations on Uncertain Node Demands and Edge Distances, and Conclusions on Robust 1-Median with Discrete Scenarios Robust 1-Median Problem on a Tree with Interval Input Data Robust 1-Median on a Tree with Mixed Scenarios A Brief Guide Through Related Literature In this chapter we derive estimators for discrete-time linear systems that are robust to plant and noise model uncertainties.

The approach used is based on a game theoretic formulation in which the disturbances and the modeling errors act as opponents of the state : Rami S.

Mangoubi. An observer- based integrated robust fault estimation and accommoda- tion for a class of discrete-time uncertain nonlinear sys- tems was presented in [13]. Both full-order and reduced- order fault. Model and simulation development for space turbopump health monitoring by parameter estimation.

25th Joint Propulsion Conference (Monterey). AlAA paper AIAA, Washington, D.C. Whitehead, B., H. Ferber and M. Ali (). Neural network approach to space shuttle main engine health monitoring. 26th Joint Propulsion Conference (Orlando).Author: B.K.

Walker, E.T. Baumgartner. Conclusions. The robust H ∞ fault estimation for 2-D time-varying uncertainty systems has been studied using the Krein space based method in this work. By introducing a new H ∞ performance function, the process uncertainty can be appropriately conducted in fault estimation.

With the aid of the Krein space based method, the robust fault estimation problem, which has been formulated into Cited by: 8.

the problem of state and fault estimation over finite-horizon is developed. A numerical example is illustrated in section 4. Problem formulation The problem consists of designing a filter that gives a robust state and fault estimation for discrete time-varying uncertain system.

This problem is described by the bloc diagram of Fig. Fig Author wdgreene Posted on Aug J Categories Uncategorized Tags closed loop engine, J-2X rocket engine, Marshall Space Flight Center, open loop engine, Space Shuttle Main Engine, William Greene 12 Comments on Inside The J-2X Doghouse: Engine Control — Open versus Closed Loop J-2X Progress: Valves, Commands into Action.

State-Space Model Estimation Methods. The method works on discrete time-domain data and frequency-domain data. It first estimates a high-order regularized ARX or FIR model, converts it to a state-space model and then performs balanced reduction on it.

noisy data sets. With all the estimation methods, you have the option of specifying. Abstract: A general non-parametric technique is proposed for the analysis of a complex multimodal feature space and to delineate arbitrarily shaped clusters in it. The basic computational module of the technique is an old pattern recognition procedure: the mean shift.

For discrete data, we prove the convergence of a recursive mean shift procedure to the nearest stationary point of the. Description. dlinmod compute a linear state-space model for a discrete-time system by linearizing each block in a model individually.

linmod obtains linear models from systems of ordinary differential equations described as Simulink models.

Inputs and outputs are denoted in Simulink block diagrams using Inport and Outport blocks. The default algorithm uses preprogrammed analytic block sys: Name of the Simulink® system from which the linear, model is extracted.

ECE/, State-Space Models and the Discrete-Time Realization Algorithm 5–2 We then preview the approach to generate the state-space models from the PDEs of the variables of interest: •We start by generating transfer functions for each PDE; •We then use the “discrete-time realization algorithm” to convert transfer functions to state-space Size: KB.

RS engines, formerly used as space shuttle main engines, line the the Space Shuttle Main Engine Processing Facility at NASA's Kennedy Space Center in Florida. 15 flight engines used during the Space Shuttle Program have been relocated to NASA's Stennis Space Center in southern Mississippi.

The engines will be stored at Stennis for future use on. This textbook aims to provide a clear understanding of the various tools of analysis and design for robust stability and performance of uncertain dynamic systems.

In model-based control design and analysis, mathematical models can never completely represent the “real world” system that is being modeled, and thus it is imperative to incorporate and accommodate a level of uncertainty into.Discrete-time state-space models provide the same type of linear difference relationship between the inputs and outputs as the linear ARMAX model, but are rearranged such that there is only one delay in the expressions.

You cannot estimate a discrete-time state-space model using continuous-time frequency-domain data.space model the synchron on method spectively. T ion 4. Sectio el ear synchron is considered this model, f dampers cal equation (ed for study lity analysis rived in [s are assumed escribed by r Estimation 14] ine ear be not ons ay can ted BS al ses ine em to ons ted.

and ght ine ers. ns. wn are ous are he n 5 ous as the are the ing of 18] to File Size: KB.