Spacecraft Dynamics and Control : The Embedded Model Control Approach /
The book introduces the Embedded Model Control methodology for the design and implementation of attitude and orbit control systems. The logic architecture is organized around the embedded model of the spacecraft and its surrounding environment. The model is compelled to include disturbance dynamics...
| Main Authors: | , , , , , |
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| Format: | software, multimedia |
| Language: | eng |
| Published: |
Cambridge : Butterworth-Heinemann,
2018
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| Subjects: | |
| Online Access: | https://www.sciencedirect.com/book/9780081007006 |
| _version_ | 1796765166694563840 |
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| author | Canuto, Enrico, author 649439 Novara, Carlo, author 649440 Massotti, Luca, author 649441 Carlucci, Donato, author 649442 Montenegro, Carlos Perez, author 649443 ScienceDirect (Online service) 7722 |
| author_facet | Canuto, Enrico, author 649439 Novara, Carlo, author 649440 Massotti, Luca, author 649441 Carlucci, Donato, author 649442 Montenegro, Carlos Perez, author 649443 ScienceDirect (Online service) 7722 |
| author_sort | Canuto, Enrico, author 649439 |
| collection | OCEAN |
| description | The book introduces the Embedded Model Control methodology for the design and implementation of attitude and orbit control systems. The logic architecture is organized around the embedded model of the spacecraft and its surrounding environment. The model is compelled to include disturbance dynamics as a repository of the uncertainty that the control law must reject to meet attitude and orbit requirements within the uncertainty class. The source of the real-time uncertainty estimation/prediction is the model error signal, as it encodes the residual discrepancies between spacecraft measurements and model output. The embedded model and the uncertainty estimation feedback (noise estimator in the book) constitute the state predictor feeding the control law. Asymptotic pole placement (exploiting the asymptotes of closed-loop transfer functions) is the way to design and tune feedback loops around the embedded model (state predictor, control law, reference generator). The design versus the uncertainty class is driven by analytic stability and performance inequalities. The method is applied to several attitude and orbit control problems. |
| first_indexed | 2024-03-05T17:20:23Z |
| format | software, multimedia |
| id | KOHA-OAI-TEST:606605 |
| institution | Universiti Teknologi Malaysia - OCEAN |
| language | eng |
| last_indexed | 2024-03-05T17:20:23Z |
| publishDate | 2018 |
| publisher | Cambridge : Butterworth-Heinemann, |
| record_format | dspace |
| spelling | KOHA-OAI-TEST:6066052023-10-08T11:03:14ZSpacecraft Dynamics and Control : The Embedded Model Control Approach / Canuto, Enrico, author 649439 Novara, Carlo, author 649440 Massotti, Luca, author 649441 Carlucci, Donato, author 649442 Montenegro, Carlos Perez, author 649443 ScienceDirect (Online service) 7722 software, multimedia Electronic books 631902 Cambridge : Butterworth-Heinemann,2018©2018engThe book introduces the Embedded Model Control methodology for the design and implementation of attitude and orbit control systems. The logic architecture is organized around the embedded model of the spacecraft and its surrounding environment. The model is compelled to include disturbance dynamics as a repository of the uncertainty that the control law must reject to meet attitude and orbit requirements within the uncertainty class. The source of the real-time uncertainty estimation/prediction is the model error signal, as it encodes the residual discrepancies between spacecraft measurements and model output. The embedded model and the uncertainty estimation feedback (noise estimator in the book) constitute the state predictor feeding the control law. Asymptotic pole placement (exploiting the asymptotes of closed-loop transfer functions) is the way to design and tune feedback loops around the embedded model (state predictor, control law, reference generator). The design versus the uncertainty class is driven by analytic stability and performance inequalities. The method is applied to several attitude and orbit control problems.Includes index.Chapter 1 - Introduction -- Chapter 2 - Attitude Representation -- Chapter 3 - Orbital Dynamics -- Chapter 4 - The Environment: Perturbing Forces and Torques -- Chapter 5 - Perturbed Orbital Dynamics -- Chapter 6 - Attitude Kinematics: Modeling and Feedback -- Chapter 7 - Attitude Dynamics: Modeling and Control -- Chapter 8 - Orbit and Attitude Sensors -- Chapter 9 - Orbit and Attitude Actuators -- Chapter 10 - Attitude Determination -- Chapter 11 - Orbital Control and Prediction Problems -- Chapter 12 - Attitude Control: A Case Study -- Chapter 13 - Introduction to Dynamic Systems -- Chapter 14 - Introduction to Embedded Model Control -- IndexThe book introduces the Embedded Model Control methodology for the design and implementation of attitude and orbit control systems. The logic architecture is organized around the embedded model of the spacecraft and its surrounding environment. The model is compelled to include disturbance dynamics as a repository of the uncertainty that the control law must reject to meet attitude and orbit requirements within the uncertainty class. The source of the real-time uncertainty estimation/prediction is the model error signal, as it encodes the residual discrepancies between spacecraft measurements and model output. The embedded model and the uncertainty estimation feedback (noise estimator in the book) constitute the state predictor feeding the control law. Asymptotic pole placement (exploiting the asymptotes of closed-loop transfer functions) is the way to design and tune feedback loops around the embedded model (state predictor, control law, reference generator). The design versus the uncertainty class is driven by analytic stability and performance inequalities. The method is applied to several attitude and orbit control problems.Embedded computer systemhttps://www.sciencedirect.com/book/9780081007006URN:ISBN:9780081007006Remote access restricted to users with a valid UTM ID via VPN. |
| spellingShingle | Embedded computer system Canuto, Enrico, author 649439 Novara, Carlo, author 649440 Massotti, Luca, author 649441 Carlucci, Donato, author 649442 Montenegro, Carlos Perez, author 649443 ScienceDirect (Online service) 7722 Spacecraft Dynamics and Control : The Embedded Model Control Approach / |
| title | Spacecraft Dynamics and Control : The Embedded Model Control Approach / |
| title_full | Spacecraft Dynamics and Control : The Embedded Model Control Approach / |
| title_fullStr | Spacecraft Dynamics and Control : The Embedded Model Control Approach / |
| title_full_unstemmed | Spacecraft Dynamics and Control : The Embedded Model Control Approach / |
| title_short | Spacecraft Dynamics and Control : The Embedded Model Control Approach / |
| title_sort | spacecraft dynamics and control the embedded model control approach |
| topic | Embedded computer system |
| url | https://www.sciencedirect.com/book/9780081007006 |
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