Differential Privacy in Nonlinear Dynamical Systems with Tracking Performance Guarantees
<|reference_start|>Differential Privacy in Nonlinear Dynamical Systems with Tracking Performance Guarantees: We introduce a novel approach to make the tracking error of a class of nonlinear systems differentially private in addition to guaranteeing the tracking error performance. We use funnel control to make the tracking error evolve within a performance funnel that is pre-specified by the user. We make the performance funnel differentially private by adding a bounded continuous noise generated from an Ornstein-Uhlenbeck-type process. Since the funnel controller is a function of the performance funnel, the noise adds randomized perturbation to the control input. We show that, as a consequence of the differential privacy of the performance funnel, the tracking error is also differentially private. As a result, the tracking error is bounded by the noisy funnel boundary while maintaining privacy. We show a simulation result to demonstrate the framework.<|reference_end|>
@article{chowdhury2024differential,
    title={Differential Privacy in Nonlinear Dynamical Systems with Tracking
  Performance Guarantees},
    author={Dhrubajit Chowdhury, Raman Goyal, Shantanu Rane},
    journal={arXiv preprint arXiv:2403.08181},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.08181},
    primaryClass={eess.SY cs.SY}
}