The Experts below are selected from a list of 9 Experts worldwide ranked by ideXlab platform
Jatinder Singh - One of the best experts on this subject based on the ideXlab platform.
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Frequency and Time Domain Recursive Parameter Estimation For a Flexible Aircraft
IFAC Proceedings Volumes, 2013Co-Authors: M. Majeed, Jatinder SinghAbstract:Abstract Aerodynamic parameter estimation is an integral part of aerospace system design and life cycle process. Recent advances in computational power have allowed the use of online parameter estimation techniques in various applications. In this paper, two online parameter estimation methods are considered for the identification of aerodynamic derivatives of a flexible Aircraft: Equation Error Method and Kalman Filtering Method. The performance of the two algorithms is compared in terms of accuracy, computational efficiency and convergence. Simulation results indicate that Kalman filtering method has good convergence property and yields parameter estimates with better accuracy compared to the Equation error method.
M. Majeed - One of the best experts on this subject based on the ideXlab platform.
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Frequency and Time Domain Recursive Parameter Estimation For a Flexible Aircraft
IFAC Proceedings Volumes, 2013Co-Authors: M. Majeed, Jatinder SinghAbstract:Abstract Aerodynamic parameter estimation is an integral part of aerospace system design and life cycle process. Recent advances in computational power have allowed the use of online parameter estimation techniques in various applications. In this paper, two online parameter estimation methods are considered for the identification of aerodynamic derivatives of a flexible Aircraft: Equation Error Method and Kalman Filtering Method. The performance of the two algorithms is compared in terms of accuracy, computational efficiency and convergence. Simulation results indicate that Kalman filtering method has good convergence property and yields parameter estimates with better accuracy compared to the Equation error method.
Hiroshi Tokutake - One of the best experts on this subject based on the ideXlab platform.
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Application of Moving Horizon Method to States Estimation from Flight Test Data
TRANSACTIONS OF THE JAPAN SOCIETY FOR AERONAUTICAL AND SPACE SCIENCES, 2001Co-Authors: Ari Legowo, Hiroshi Okubo, Eiichi Muramatsu, Hiroshi TokutakeAbstract:This paper presents the application of the moving horizon states estimation (MHSE) method to estimate the states of nonlinear Aircraft Equation of motion from a dynamic maneuver’s flight test data. To determine the optimum solution of minimizing the performance index, a Quasi-Newton or gradient method is used. The present method also uses the Armijo’s line search gradient to guarantee the solution/estimation to converge faster to the global optimum estimate. The MHSE method is applied to flight test data of N250 PA-1 Aircraft for parameter identification and flight path reconstruction. The result of estimation is also used to evaluate the accuracies of the measurement systems.
Ari Legowo - One of the best experts on this subject based on the ideXlab platform.
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Application of Moving Horizon Method to States Estimation from Flight Test Data
TRANSACTIONS OF THE JAPAN SOCIETY FOR AERONAUTICAL AND SPACE SCIENCES, 2001Co-Authors: Ari Legowo, Hiroshi Okubo, Eiichi Muramatsu, Hiroshi TokutakeAbstract:This paper presents the application of the moving horizon states estimation (MHSE) method to estimate the states of nonlinear Aircraft Equation of motion from a dynamic maneuver’s flight test data. To determine the optimum solution of minimizing the performance index, a Quasi-Newton or gradient method is used. The present method also uses the Armijo’s line search gradient to guarantee the solution/estimation to converge faster to the global optimum estimate. The MHSE method is applied to flight test data of N250 PA-1 Aircraft for parameter identification and flight path reconstruction. The result of estimation is also used to evaluate the accuracies of the measurement systems.
Hiroshi Okubo - One of the best experts on this subject based on the ideXlab platform.
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Application of Moving Horizon Method to States Estimation from Flight Test Data
TRANSACTIONS OF THE JAPAN SOCIETY FOR AERONAUTICAL AND SPACE SCIENCES, 2001Co-Authors: Ari Legowo, Hiroshi Okubo, Eiichi Muramatsu, Hiroshi TokutakeAbstract:This paper presents the application of the moving horizon states estimation (MHSE) method to estimate the states of nonlinear Aircraft Equation of motion from a dynamic maneuver’s flight test data. To determine the optimum solution of minimizing the performance index, a Quasi-Newton or gradient method is used. The present method also uses the Armijo’s line search gradient to guarantee the solution/estimation to converge faster to the global optimum estimate. The MHSE method is applied to flight test data of N250 PA-1 Aircraft for parameter identification and flight path reconstruction. The result of estimation is also used to evaluate the accuracies of the measurement systems.
