Privacy-aware co-design of quantizer and controller in networked control systems. Solves stochastic control problems with mutual information regularization to prevent privacy leakage. Use for secure networked control, privacy-preserving IoT systems, and adversarial-resilient control design.
This skill implements optimal privacy-aware networked control through joint design of quantizer and controller, protecting private system inputs from adversarial inference.
The framework addresses privacy concerns in networked control systems where measurements are sent to remote controllers after stochastic quantization. An adversary attempts to infer private system inputs from quantization results and control outputs.
Key Features:
Mutual information quantifies privacy leakage:
I(Private Inputs; Quantization Results, Control Outputs)
Dynamic programming decomposition yields coupled equations for:
| Component | Property | Description |
|---|---|---|
| Controller | Deterministic | Optimal control is non-random |
| Quantizer | Belief-regulating | Closed-loop privacy enhancement |
Numerical experiments demonstrate effectiveness on:
Paper: Optimal Privacy-Aware Co-Design of Quantizer and Controller in Networked Control Systems
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