A review of pseudospectral optimal control: From theory to flight

By I. Michael Ross, Mark Karpenko. Annual Reviews in Control, 2012

371 citations recorded by the source corpus.

Abstract The home space for optimal control is a Sobolev space. The home space for pseudospectral theory is also a Sobolev space. It thus seems natural to combine pseudospectral theory with optimal control theory and construct “pseudospectral optimal control theory”, a term coined by Ross. In this paper, we review key theoretical results in pseudospectral optimal control that have proven to be critical for a successful flight. Implementation details of flight demonstrations onboard NASA spacecraft are discussed along with emerging trends and techniques in both theory and practice. The 2011 launch of pseudospectral optimal control in embedded platforms is changing the way in which we see solutions to challenging control problems in aerospace and autonomous systems.

Subfields: Aerospace Engineering, Applied Mathematics

View Paper: https://www.semanticscholar.org/paper/7b2246de86248aea0bcdbfbc0f281691f5b145b7

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Aerospace Engineering

1. Qi Gong
2. Mark Karpenko
3. Ronald J. Proulx
4. I. Michael Ross
5. Juntong Qi
6. Jianda Han
7. Jizhong Xiao
8. Xia Yong

In Applied Mathematics

1. Qi Gong
2. Ronald J. Proulx
3. I. Michael Ross
4. Mark Karpenko

Citations in the corpus

• Methodology of Resonant Equiangular Composite Quantum Gates (2016, background): “[24,25] formulate this as a systematic optimization problem”
• Survey of Robot 3D Path Planning Algorithms (2016, methodology): “Containing almost all the information to generate an optimal path indeed No analytic solutions [63] Free tool OPTRAGEN [64], RIOTS 95 [65] DIDO [66], SeDuMi [67], and so forth”
• Riemann–Stieltjes Optimal Control Problems for Uncertain Dynamic Systems (2015, methodology): “Riemann–Stieltjes Optimal Control Problems for Uncertain Dynamic Systems I. Michael Ross,∗ Ronald J. Proulx,† and Mark Karpenko‡ Naval Postgraduate School, Monterey, California 93943 and Qi Gong§ University of California, Santa Cruz, California 95064 DOI: 10.2514/1.”
• GEKKO Optimization Suite (2018, background): “Some fields have developed other unique approaches, such as pseudospectral optimal control methods [13].”