Author: Odell R. Reynolds
Publisher:
ISBN: 9781423573463
Category : Differentiable dynamical systems
Languages : en
Pages : 155
Book Description
Sensor noise is an unavoidable fact of life when it comes to measurements on physical systems, as is the case in feedback control. Therefore, it must be properly addressed during dynamic system identification. In this work, a novel approach is developed toward the treatment of measurement noise in dynamical systems. This approach hinges on proper stochastic modeling, and it can be adapted easily to many different scenarios, where it yields consistently good parameter estimates. The Generalized Minimum Variance algorithm developed and used in this work is based on the theory behind the minimum variance identification process, and the estimate produced is a fixed point of a mapping based on the minimum variance solution. Additionally, the algorithm yields an accurate prediction of the estimation error. This algorithm is applied to many different noise models associated with three basic identification problems. First, continuous-time systems are identified using frequency domain measurements. Next, a discrete-time plant is identified using discrete-time measurements. Finally, the physical parameters of a continuous-time plant are identified using sampled measurements of the continuous-time input and output. Validation of the estimates is performed correctly, and the results are compared with other, more common, identification algorithms.
Countering the Effects of Measurement Noise During the Identification of Dynamical Systems
Author: Odell R. Reynolds
Publisher:
ISBN: 9781423573463
Category : Differentiable dynamical systems
Languages : en
Pages : 155
Book Description
Sensor noise is an unavoidable fact of life when it comes to measurements on physical systems, as is the case in feedback control. Therefore, it must be properly addressed during dynamic system identification. In this work, a novel approach is developed toward the treatment of measurement noise in dynamical systems. This approach hinges on proper stochastic modeling, and it can be adapted easily to many different scenarios, where it yields consistently good parameter estimates. The Generalized Minimum Variance algorithm developed and used in this work is based on the theory behind the minimum variance identification process, and the estimate produced is a fixed point of a mapping based on the minimum variance solution. Additionally, the algorithm yields an accurate prediction of the estimation error. This algorithm is applied to many different noise models associated with three basic identification problems. First, continuous-time systems are identified using frequency domain measurements. Next, a discrete-time plant is identified using discrete-time measurements. Finally, the physical parameters of a continuous-time plant are identified using sampled measurements of the continuous-time input and output. Validation of the estimates is performed correctly, and the results are compared with other, more common, identification algorithms.
Publisher:
ISBN: 9781423573463
Category : Differentiable dynamical systems
Languages : en
Pages : 155
Book Description
Sensor noise is an unavoidable fact of life when it comes to measurements on physical systems, as is the case in feedback control. Therefore, it must be properly addressed during dynamic system identification. In this work, a novel approach is developed toward the treatment of measurement noise in dynamical systems. This approach hinges on proper stochastic modeling, and it can be adapted easily to many different scenarios, where it yields consistently good parameter estimates. The Generalized Minimum Variance algorithm developed and used in this work is based on the theory behind the minimum variance identification process, and the estimate produced is a fixed point of a mapping based on the minimum variance solution. Additionally, the algorithm yields an accurate prediction of the estimation error. This algorithm is applied to many different noise models associated with three basic identification problems. First, continuous-time systems are identified using frequency domain measurements. Next, a discrete-time plant is identified using discrete-time measurements. Finally, the physical parameters of a continuous-time plant are identified using sampled measurements of the continuous-time input and output. Validation of the estimates is performed correctly, and the results are compared with other, more common, identification algorithms.
Identification of Dynamical Systems in the Presence of Non-Gaussian and Non-Whie Noise
Author: H. Salzwedel
Publisher:
ISBN:
Category :
Languages : en
Pages : 63
Book Description
Analysis of test results indicates that the measurement and process noise is significantly non-white and non-Gaussian. Some analyses indicate that 10% to 15% of the data points may deviate significantly from non-Gaussian distribution. In addition, numerous sources lead to non-white noise. These errors effect both the accuracy of state and parameter estimates as well as the estimation of accuracy levels. In this report, techniques have been developed to treat systems with non-white and non-Gaussian noise. These techniques provide good estimates under given whiteness and Gaussianess conditions. The procedures are simple and can be easily incorporated in the standard maximum likelihood and model structure determination methods.
Publisher:
ISBN:
Category :
Languages : en
Pages : 63
Book Description
Analysis of test results indicates that the measurement and process noise is significantly non-white and non-Gaussian. Some analyses indicate that 10% to 15% of the data points may deviate significantly from non-Gaussian distribution. In addition, numerous sources lead to non-white noise. These errors effect both the accuracy of state and parameter estimates as well as the estimation of accuracy levels. In this report, techniques have been developed to treat systems with non-white and non-Gaussian noise. These techniques provide good estimates under given whiteness and Gaussianess conditions. The procedures are simple and can be easily incorporated in the standard maximum likelihood and model structure determination methods.
Universal results for the effects of noise on dynamical systems
Author: David Edward Sigeti
Publisher:
ISBN:
Category : Differentiable dynamical systems
Languages : en
Pages : 272
Book Description
Publisher:
ISBN:
Category : Differentiable dynamical systems
Languages : en
Pages : 272
Book Description
Applied Mechanics Reviews
Author:
Publisher:
ISBN:
Category : Mechanics, Applied
Languages : en
Pages : 538
Book Description
Publisher:
ISBN:
Category : Mechanics, Applied
Languages : en
Pages : 538
Book Description
Scientific and Technical Aerospace Reports
Author:
Publisher:
ISBN:
Category : Aeronautics
Languages : en
Pages : 700
Book Description
Lists citations with abstracts for aerospace related reports obtained from world wide sources and announces documents that have recently been entered into the NASA Scientific and Technical Information Database.
Publisher:
ISBN:
Category : Aeronautics
Languages : en
Pages : 700
Book Description
Lists citations with abstracts for aerospace related reports obtained from world wide sources and announces documents that have recently been entered into the NASA Scientific and Technical Information Database.
The Effects of Small Noise on Implicitly Defined Non-linear Dynamical Systems
Author: Shankar Sastry
Publisher:
ISBN:
Category : Electric circuits, Nonlinear
Languages : en
Pages : 47
Book Description
Publisher:
ISBN:
Category : Electric circuits, Nonlinear
Languages : en
Pages : 47
Book Description
Feedback Control of Dynamic Systems Int
Author: J. David Powell
Publisher: Pearson Academic Computing
ISBN: 9781447935377
Category : Feedback control systems
Languages : en
Pages :
Book Description
This text covers the material that every engineer, and most scientists and prospective managers, needs to know about feedback control, including concepts like stability, tracking, and robustness. Each chapter presents the fundamentals along with comprehensive, worked-out examples, all within a real-world context.
Publisher: Pearson Academic Computing
ISBN: 9781447935377
Category : Feedback control systems
Languages : en
Pages :
Book Description
This text covers the material that every engineer, and most scientists and prospective managers, needs to know about feedback control, including concepts like stability, tracking, and robustness. Each chapter presents the fundamentals along with comprehensive, worked-out examples, all within a real-world context.
Nuclear Science Abstracts
Author:
Publisher:
ISBN:
Category : Nuclear energy
Languages : en
Pages : 1310
Book Description
Publisher:
ISBN:
Category : Nuclear energy
Languages : en
Pages : 1310
Book Description
Master's Theses and Doctoral Dissertations in the Pure and Applied Sciences
Author:
Publisher:
ISBN:
Category : Dissertations, Academic
Languages : en
Pages : 194
Book Description
Publisher:
ISBN:
Category : Dissertations, Academic
Languages : en
Pages : 194
Book Description
Mathematics in Population Biology
Author: Horst R. Thieme
Publisher: Princeton University Press
ISBN: 0691187657
Category : Science
Languages : en
Pages :
Book Description
Publisher: Princeton University Press
ISBN: 0691187657
Category : Science
Languages : en
Pages :
Book Description