Difference between revisions of "SURF 2019: Geometry of Control-Invariant Sets"
(Created page with "The concept of a ''control-invariant'' set---a set <math>X</math> with the property that a controller can make the state <math>x(t)</math> of a system remain inside of <math>X...")
Revision as of 00:05, 28 November 2018
The concept of a control-invariant set---a set with the property that a controller can make the state of a system remain inside of for all positive ---is closely connected with safety and reliability of engineered systems . Unfortunately, analytical expressions for control-invariant sets are not known for many important systems, and are also hard to compute numerically in high dimensions.
Some of the most fundamental dynamical systems are linear -order integrators. For = 2 a closed-form expression of the maximal control-invariant set contained inside the unite hypercube is known [2. eq. (53)], but for higher orders of only numerical approaches are available. The Figure above shows numerical approximations for equal to 2 and equal to 3. The objective of this project is to investigate geometrical properties of these sets via a combination of analytical and numerical techniques. In particular,
- Search for closed-form expressions or cheap-to-evaluate algorithms that characterize control-invariant sets of for n larger than 3.
- Investigate incremental algorithms, i.e., if the set for $n$ is known, can we characterize the set for $n+1$?
- Stretch goal: generalize the incremental ideas to differential extensions of general systems such as the quadrotor dynamics on $SE(3)$.
Familiarity with the following topics is desirable:
- Advanced knowledge of linear ordinary differential equations.
- Programming in Matlab and/or Python (the figures above were created with code from https://github.com/pettni/pcis).
 Blanchini, F. (1999). Set invariance in control. Automatica, 35(11), 1747–1767. https://doi.org/10.1016/S0005-1098(99)00113-2
 Ames, A. D., Xu, X., Grizzle, J. W., & Tabuada, P. (2017). Control Barrier Function Based Quadratic Programs for Safety Critical Systems. IEEE Transactions on Automatic Control, 62(8), 3861–3876. https://doi.org/10.1109/TAC.2016.2638961