Abstract
This paper investigates the convergence performance of second-order needle variation methods for nonlinear control-affine systems. Control solutions have a closed-form expression that is derived from the first-and second-order mode insertion gradients of the objective and are proven to exhibit superlinear convergence near equilibrium. Compared to first-order needle variations, the proposed synthesis scheme exhibits superior convergence at smaller computational cost than alternative nonlinear feedback controllers. Simulation results on the differential drive model verify the analysis and show that second-order needle variations outperform first-order variational methods and iLQR near the optimizer. Last, even when implemented in a closed-loop, receding horizon setting, the proposed algorithm demonstrates superior convergence against the iterative linear quadratic Gaussian (iLQG) controller.
Original language | English (US) |
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Title of host publication | 2018 IEEE Conference on Decision and Control, CDC 2018 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 4301-4308 |
Number of pages | 8 |
ISBN (Electronic) | 9781538613955 |
DOIs | |
State | Published - Jul 2 2018 |
Event | 57th IEEE Conference on Decision and Control, CDC 2018 - Miami, United States Duration: Dec 17 2018 → Dec 19 2018 |
Publication series
Name | Proceedings of the IEEE Conference on Decision and Control |
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Volume | 2018-December |
ISSN (Print) | 0743-1546 |
ISSN (Electronic) | 2576-2370 |
Conference
Conference | 57th IEEE Conference on Decision and Control, CDC 2018 |
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Country/Territory | United States |
City | Miami |
Period | 12/17/18 → 12/19/18 |
Funding
This work was supported by the National Science Foundation under Grant CMMI 1662233. Any opinions, findings, and conclusions or recommendations expressed here are those of the authors and do not necessarily reflect the views of the National Science Foundation.
ASJC Scopus subject areas
- Control and Systems Engineering
- Modeling and Simulation
- Control and Optimization