Output-Feedback Control of Nonlinear Systems using Control Contraction Metrics and Convex Optimization
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Abstract (arXiv)
Control contraction metrics (CCMs) are a new approach to nonlinear control design based on contraction theory. The resulting design problems are expressed as pointwise linear matrix inequalities and are and well-suited to solution via convex optimization. In this paper, we extend the theory on CCMs by showing that a pair of "dual" observer and controller problems can be solved using pointwise linear matrix inequalities, and that when a solution exists a separation principle holds. That is, a stabilizing output-feedback controller can be found. The procedure is demonstrated using a benchmark problem of nonlinear control: the Moore-Greitzer jet engine compressor model.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 Jun 2014.
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Citing papers per year: 2022: 1; 2023: 1; 2024: 0; 2025: 1; 2026: 1.
4 papers.
- 2022Safe Output Feedback Motion Planning from Images via Learned Perception Modules and Contraction Theorycited by 18
- 2023Synthesizing Stable Reduced-Order Visuomotor Policies for Nonlinear Systems via Sums-of-Squares Optimizationcited by 7
- 2025Parameter-free Optimal Rates for Nonlinear Semi-Norm Contractions with Applications to Q-Learningcited by 2
- 2026Controller Design for Structured State-space Models via Contraction Theorycited by 1
- 2026Controller Design for Structured State-space Models via Contraction Theory8 Apr 2026
- 2025Parameter-free Optimal Rates for Nonlinear Semi-Norm Contractions with Applications to Q-Learning8 Aug 2025
- 2023Synthesizing Stable Reduced-Order Visuomotor Policies for Nonlinear Systems via Sums-of-Squares Optimization24 Apr 2023
- 2022Safe Output Feedback Motion Planning from Images via Learned Perception Modules and Contraction Theory14 Jun 2022