Simultaneous-Perturbation-Stochastic-Approximation Algorithm for Parachute Parameter Estimation

Kothandaraman, Govindarajan; Rotea, Mario A.

doi:10.2514/1.11721

Cited by 14 publications

(14 citation statements)

References 6 publications

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“…In this context ß can be defined as follows: (8) The functions included in the fj expression are given as follows: y,(a,^J) = -tan-M-,2"ĵ 2(j2-a2)-2i?2…”

Section: Methodsologymentioning

confidence: 99%

“…The optimization procedure adopted in this paper is based on the approach of simultaneous perturbation stochastic approximation. This approach is efficient and suited for such an intricate optimization application as abundantly explained in the literature, e.g., the excellent paper by Spall [7] and the interesting application tackled by Kothandaraman and Rotea [8].…”

Section: Introductionmentioning

confidence: 97%

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Evaluation of Slug Flow-Induced Flexural Loading in Pipelines Using a Surrogate Model

Sultan

Reda²,

Forbes

2013

Journal of Offshore Mechanics and Arctic Engineering

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Slug flow induces vibration in pipelines, which may, in some cases, result in fatigue failure. This can result from dynamic stresses, induced by the deflection and bending moment in the pipe span, growing to levels above the endurance limits of the pipeline material. As such, it is of paramount importance to understand and quantify the size of the pipeline response to slug flow under given speed and damping conditions. This paper utilizes the results of an optimization procedure to devise a surrogate closed-form model, which can be employed to calculate the maximum values of the pipeline loadings at given values of speed and damping parameters. The surrogate model is intended to replace the computationally costly numerical procedure needed for the analysis. The maximum values of the lateral deflection and bending moment, along with their locations, have been calculated using the optimization method of stochastic perturbation and successive approximations (SPSA). The accuracy of the proposed surrogate model will be validated numerically, and the model will be subsequently used in a numerical example to demonstrate its applicability in industrial situations. An accompanying spreadsheet with this worked example is also given.

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“…In this context ß can be defined as follows: (8) The functions included in the fj expression are given as follows: y,(a,^J) = -tan-M-,2"ĵ 2(j2-a2)-2i?2…”

Section: Methodsologymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 97%

Evaluation of Slug Flow-Induced Flexural Loading in Pipelines Using a Surrogate Model

Sultan

Reda²,

Forbes

2013

Journal of Offshore Mechanics and Arctic Engineering

View full text Add to dashboard Cite

show abstract

“…In this case, the system identification procedure described here could be used to develop an approximate model based on GPS alone which could then be refined with whatever additional sensor information is available. Depending on the available sensor data, this refinement could be performed using similar methods to the existing airdrop identification methods mentioned previously [4][5][6][7][8][9][10][11]. Another possibility is that the model made from GPS data using the proposed procedure could be simply augmented to capture unmodeled dynamics observed in the additional sensor channels using more general system identification techniques such as those recently developed by Majji et al [15,16].…”

mentioning

confidence: 99%

“…They demonstrated the identification of a linear 8-DOF model from simulation data using an observer/ Kalman filter identification method described by Valasek and Chen [9]. Kothandaraman and Rotea described the use of a computationally efficient method to identify coefficients for a 6-DOF circular parachute model assuming perfect knowledge of the winds [10]. Yakimenko and Statnikov presented a method for identifying aerodynamic coefficients of an 8-DOF parafoil model using a multicriteria optimization method beginning with a parameter space investigation to help address the problems of local minima and infeasible regions in the parameter space [11].…”

mentioning

confidence: 99%

“…A number of efforts have applied aerodynamic parameter identification to airdrop systems [4][5][6][7][8][9][10][11]. Jann et al describe the development of a highly instrumented parafoil and payload research platform, ALEX, incorporating a Global Positioning System (GPS) receiver, magnetometers, rate gyros, accelerometers, air data probes, and video cameras to address the problem of generating enough data for system identification [4].…”

mentioning

confidence: 99%

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Specialized System Identification for Parafoil and Payload Systems

Ward

Costello

Slegers

2012

Journal of Guidance, Control, and Dynamics

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There are a number of peculiar aspects to parafoil and payload systems that make it difficult to apply conventional system identification procedures used for aerospace systems. Parafoil and payload systems are unique because typically there is very little sensor information available, the sensors that are available are separated from the canopy by a complex network of flexible rigging, the systems are very sensitive to wind and turbulence, the systems exhibit a number of nonlinear behaviors, and the systems exhibit a high degree of variability from flight to flight. The current work describes a robust system identification procedure developed to address the specific difficulties posed by airdrop systems. By employing a two-phase approach that separately considers atmospheric winds estimation and aerodynamic coefficient estimation, a nonlinear, 6-degree-of-freedom dynamic simulation model is generated using only Global Positioning System data from the flight test. The key to this approach is the use of a simplified aerodynamic representation of the canopy, which requires identification of only the steady-state response to control input to completely define the dynamic model. The proposed procedure is demonstrated by creating a simulation model using Global Positioning System data from actual flight tests. To validate the procedure, the dynamic response of the simulation model is then compared to inertial measurement unit data that were not used in any way to develop the simulation model, with excellent results.

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Calibration of an articulated CMM using stochastic approximations

Sultan

Puthiyaveettil

2012

Int J Adv Manuf Technol

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A coordinate measuring machine (CMM) is meant to digitise the spatial locations of points and feed the resulting measurements to a CAD system for storing and processing. For reliable utilisation of a CMM, a calibration procedure is often undertaken to eliminate the inaccuracies which result from manufacturing, assembly and installation errors. In this paper, an Immersion digitizer coordinate measuring machine (IDCMM) has been calibrated using an accurately manufactured master cuboid fixture. This CMM has been designed as an articulated manipulator to enhance its dexterity and versatility. As such, the calibration problem is tackled with the aid of a kinematic model similar to those employed for the analysis of serial robots. In addition, a stochastic-based optimisation technique is used to identify the parameters of the kinematic model in order for the accurate performance to be achieved. The experimental results demonstrate the effectiveness of this method, whereby the measuring accuracy has been improved considerably.

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Simultaneous-Perturbation-Stochastic-Approximation Algorithm for Parachute Parameter Estimation

Cited by 14 publications

References 6 publications

Evaluation of Slug Flow-Induced Flexural Loading in Pipelines Using a Surrogate Model

Evaluation of Slug Flow-Induced Flexural Loading in Pipelines Using a Surrogate Model

Specialized System Identification for Parafoil and Payload Systems

Calibration of an articulated CMM using stochastic approximations

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