Dynamic Quantizer Design Under Communication Rate Constraints

Feedback type dynamic quantizers such as delta-sigma modulators are typically effective for encoding high-resolution data into lower resolution data. The dynamic quantizers include a filter and a static quantizer. When it is required to control under a communication rate constraint, the data rate of the quantizer output should be minimized appropriately by quantization. This technical note provides numerical methods for the complete design of a type of dynamic quantizers, including the selection of all the quantizer parameters in order to minimize a specific performance index and satisfy a communication constraint. The design method of the dynamic quantizer is proposed using a particle swarm optimization (PSO) method. A part of the initial quantizers in PSO are designed based on an invariant set analysis and an iteration algorithm. Effectiveness of the system with the proposed quantizer is assessed through numerical examples

Dynamic Quantized Consensus of General Linear Multi-agent Systems under Denial-of-Service Attacks

In this paper, we study multi-agent consensus problems under Denial-of-Service (DoS) attacks with data rate constraints. We first consider the leaderless consensus problem and after that we briefly present the analysis of leader-follower consensus. The dynamics of the agents take general forms modeled as homogeneous linear time-invariant systems. In our analysis, we derive lower bounds on the data rate for the multi-agent systems to achieve leaderless and leader-follower consensus in the presence of DoS attacks, under which the issue of overflow of quantizer is prevented. The main contribution of the paper is the characterization of the trade-off between the tolerable DoS attack levels for leaderless and leader-follower consensus and the required data rates for the quantizers during the communication attempts among the agents. To mitigate the influence of DoS attacks, we employ dynamic quantization with zooming-in and zooming-out capabilities for avoiding quantizer saturation

On the effect of quantization on performance at high rates

We study the effect of quantization on the performance of a scalar dynamical system in the high rate regime. We evaluate the LQ cost for two commonly used quantizers: uniform and logarithmic and provide a lower bound on performance of any centroid-based quantizer based on entropy arguments. We also consider the case when the channel drops data packets stochastically