# Training Classifiers For Feedback Control

@article{Poonawala2019TrainingCF, title={Training Classifiers For Feedback Control}, author={Hasan A. Poonawala and Niklas T. Lauffer and Ufuk Topcu}, journal={2019 American Control Conference (ACC)}, year={2019}, pages={4961-4967} }

One approach for feedback control using high dimensional and rich sensor measurements is to classify the measurement into one out of a finite set of situations, each situation corresponding to a (known) control action. This approach computes a control action without estimating the state. Such classifiers are typically learned from a finite amount of data using supervised machine learning algorithms. We model the closed-loop system resulting from control with feedback from classifier outputs as…

## 3 Citations

Stability Analysis of Conewise Affine Dynamical Systems Using Conewise Linear Lyapunov Functions

- MathematicsIEEE Control Systems Letters
- 2021

It is shown that this approach verifies stability of 2D and 3D examples of conewise affine dynamical systems, including combinations of the harmonic and nonsmooth oscillators.

Stability Analysis Via Refinement Of Piece-wise Linear Lyapunov Functions

- Mathematics2019 IEEE 58th Conference on Decision and Control (CDC)
- 2019

This work presents an algorithm that involves iteratively refining partitions using an exact criterion which strictly reduces the set of points over which the Lyapunov function is non-decreasing.

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