Spacecraft Dynamics and Control: The Embedded Model Control Approach (Aerospace Engineering) - Softcover

Canuto, Enrico

Softcover

ISBN 10: 0081007000 ISBN 13: 9780081007006

Publisher: Butterworth-Heinemann, 2018

Synopsis

Spacecraft Dynamics and Control: The Embedded Model Control Approach provides a uniform way of approaching space engineering control problems from the standpoint of model-based control, using state equations as the key dynamic model for simulation, design and implementation. The book introduces model-based control design methodology for spacecraft attitude and orbit control. It then covers model-based estimation and control algorithm design, using spacecraft and environment dynamics as the core of the implemented control algorithms-referred to as the embedded (or internal) model. The book also presents two appendices, in which the state equation machinery is fully exploited and introduced.

Embedded model and noise estimators constitute a closed-loop state predictor to be stabilized by the estimator gains. Kalman filter optimization may be adopted under certain restricted assumptions. This book is indispensable for researchers and practitioners in the field of control engineering, aerospace engineering, mechanical engineering and applied mathematics.

About this title

About the Authors

Enrico Canuto taught Automatic Control for more than 40 years at Politecnico di Torino, Italy. He developed and applied the embedded model control methodology for the design and implementation of digital control systems. Over the course of his career, he has contributed to data reduction of the European astrometric mission Hipparcos, concluding with the publication of the Hipparcos star Catalogue of 120,000 stars; to the European GOCE mission and other forthcoming missions; to instruments for space qualification like the Nanobalance thrust-stand. In the last ten years, he has also collaborated with the Center for Gravity Experiments, Huazhong University of Science and Technology, Wuhan, and the Tianqin Centre, Sun-Yat-Sen University, Zhuhai, China, in the field of scientific space missions aimed at detecting gravitational waves.

Carlo Novara received his MSc degree in Physics from the University of Turin in 1996 and his PhD degree in Computer and System Engineering from Politecnico di Torino in 2002. He held a visiting researcher position at University of California at Berkeley in 2001 and 2004 and is currently a Full Professor at Politecnico di Torino. He is a really prolific author of peer-reviewed scientific publications in international journals and conference proceedings. He has been involved in several national and international projects and in several research contracts in collaboration with Italian and European companies. He is the co-author of several patents in the automotive field. He is a member of the IEEE Technical Committee on System Identification and Adaptive Control, of the IFAC Technical Committee on Modelling, Identification and Signal Processing, of the IFAC Technical Committee on Modelling and Control of Environmental Systems, and a founding member of the IEEE-CSS Technical Committee on Medical and Healthcare Systems. His research interests include nonlinear and linear parameter-varying system identification, filtering/estimation, time series prediction, nonlinear control, predictive control, data-driven methods, set membership methods, sparse methods, nonlinear optimization, and aerospace, automotive, biomedical, and energy applications.

Donato Carlucci is an Associate Professor at Politecnico di Torino. He is the author or co‐author of scientific publications on applied nonlinear systems control. He has been involved in national and international projects in collaboration with Italian and European industries. He has worked for more than 40 years in the fields of nonlinear system control including aerospace systems. His current research interests include satellite attitude control. He is teaching courses on Automation and Production Systems at Politecnico di Torino

Carlos Perez-Montenegro received his MSc degree in Electronic Engineering from Pontificia Universidad Javeriana in 2007, followed in 2014 by a PhD in Computer and Control Engineering from the Department of Control and Computer Engineering of Politecnico di Torino. His research interests span the fields of guidance, navigation, and control (GNC), with a focus on applications to planetary landing systems and unmanned aerial systems. Currently, he is designing and implementing control and estimation systems for service instruments of the automotive industry.

Luca Massotti received his MSc and PhD degrees in Aerospace Engineering from Politecnico di Torino in 2000 and 2004 respectively. In 2001-2002, he was a visiting researcher at West Virginia University to study aircraft modelling and neural network controllers. In 2004, he joined Thales Alenia Space in Turin as an engineering consultant for metrology and AOCS. From 2005 to 2007, he was a post-doctoral researcher within the Earth Observation Programs of the European Space Agency at the ESTEC facility in the Netherlands, where he currently works as a system engineer for the Future Missions and Instruments division. He is actively involved in the ESA Technology Research Program, either in procurement of activities or the review phases, especially in the domain of micro-propulsion (either cold gas or electric propulsion), laser metrology, ultra-sensitive accelerometers, drag-free/compensation and fine AOCS. His research interests include aircraft and satellite modeling and simulation, nonlinear and adaptive control design, artificial intelligence techniques, nano-balancing, AOCS, drag-free and attitude control for scientific satellites. Dr. Massotti has been appointed as coordinator of the Inter-Agency Working Group between ESA and NASA on gravity topics; he is a member of the ESA/NASA JET (Joint Engineering Team) and a Member of the AIAA GNC Technical Committee, and an AIAA Associate Fellow.

Edition details

• Publisher: Butterworth-Heinemann
• Publication date: 2018
• Language: English
• ISBN 10: 0081007000
• ISBN 13: 9780081007006
• Binding: Paperback
• Number of pages: 790