Predictive Filtering for Microsatellite Control Systems introduces technological design, modeling, stability analysis, predictive filtering, state estimation problem and real-time operation of spacecraft control systems in aerospace engineering. The book gives a systematically and almost self-contained description of the many facets of envisaging, designing, implementing or experimentally exploring predictive filtering for spacecraft control systems, along with the adequate designs of integrated modeling, dynamics, state estimation, and signal processing of spacecrafts and nonlinear systems.
Predictive Filtering for Microsatellite Control Systems introduces technological design, modeling, stability analysis, predictive filtering, state estimation problem and real-time operation of spacecraft control systems in aerospace engineering. The book gives a systematically and almost self-contained description of the many facets of envisaging, designing, implementing or experimentally exploring predictive filtering for spacecraft control systems, along with the adequate designs of integrated modeling, dynamics, state estimation, and signal processing of spacecrafts and nonlinear systems.
Dr. Lu Cao is an associate research fellow. He is one of the world leading scholars in the field of nonlinear filtering/state estimation for spacecraft control systems. He is a productive researcher by publishing 50+ SCI journal papers, and has been authorized with 7 invention patents.
Dr. Cao has been the pioneer to establish advanced filtering algorithms in practice such as satellites and other. He designed the attitude determination and control system of Tian-Tuo (TT) series micro/nano satellites (totally 8 satellites), and has rich theoretical research and engineering application experience. As recognition for his significant contributions, he is a review expert in aerospace major journals such as Acta Astronautica, Advances in Space Research, Nonlinear Dynamics, and Aerospace China. Moreover, he has won many major awards, which include: the Excellent Master's Thesis, the Excellent Doctorate Thesis, and has been selected in"Yong Talent Lift Project?.Prof. Xiaoqian Chen is one of the world leading scholars in the field of spacecraft design. Prof. Chen took in charge of developing Tian-Tuo (TT) series micro/nano satellites (totally 8 satellites). Under his leadership, his team accomplished Tian-Yuan 1 on-orbit refueling satellite flight test, which is the second time in the world after the United States. He established advanced overall design theory of flight vehicles featuring multi-disciplinary design optimization (MDO).
He has been elected as an academician in International Academy of Astronautics (IAA), a member in International Astronautical Federation (IAF), a member in the robotics committee of Chinese Society of Astronautics, and an editorial board member in some major journals. He has won many major awards, which include: the "'Qiu Shi' Outstanding Youth Prize for Practical Engineering?, "Science & Technology Award for Chinese Youth?, "Science & Technology Award for Chinese Youth by Chinese Society of Aeronauti
cs and Astronautics (CSAA)?.
Inhaltsangabe
Section A: General analysis on filtering for spacecraft control systems 1. Motivations 2. A survey on filtering for spacecraft control systems 3. Modelling of spacecraft control systems
Section B: Sigma-point predictive filtering for spacecraft control systems 4. Unscented predictive filtering theory for spacecraft control systems 5. Central difference predictive filter design for spacecrafts 6. Cubature predictive filtering theory for spacecraft control systems
Section C: Variable structure predictive filtering for spacecraft control systems 7. Variable structure predictive filter design 8. Adaptive variable structure predictive filter design 9. Higher-order variable structure predictive filter design
Section A: General analysis on filtering for spacecraft control systems 1. Motivations 2. A survey on filtering for spacecraft control systems 3. Modelling of spacecraft control systems
Section B: Sigma-point predictive filtering for spacecraft control systems 4. Unscented predictive filtering theory for spacecraft control systems 5. Central difference predictive filter design for spacecrafts 6. Cubature predictive filtering theory for spacecraft control systems
Section C: Variable structure predictive filtering for spacecraft control systems 7. Variable structure predictive filter design 8. Adaptive variable structure predictive filter design 9. Higher-order variable structure predictive filter design
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