Second-order distributed consensus with one-bit adaptive quantization

In order to improve the accuracy and the convergence rate of distributed consensus under quantized communication, in the paper, based on one-bit adaptive quantization scheme, we propose the second-order distributed consensus to update the state of every node by the present quantized values and the previous quantized values of the adjacency nodes. We analyze the convergence performance. The second-order distributed consensus with one-bit adaptive quantization achieves a consensus in a mean square sense, and the consensus is equal to the average of the initial states. Simultaneously, Simulations are done about the second-order distributed consensus based on one-bit adaptive quantization. Results show that the second-order distributed consensus algorithm based on one-bit adaptive quantization can reach an average consensus, and its convergence rate is higher than that of the first-order adaptive quantized distributed consensus algorithm, moreover, the mean square errors are smaller within the finite steps.