Rate Allocation for Quantized Control Over Binary Symmetric Channels

Utility maximization in networked control systems (NCSs) is difficult in the presence of limited sensing and communication resources. In this paper, a new communication rate optimization method for state feedback control over a noisy channel is proposed. Linear dynamic systems with quantization errors, limited transmission rate, and noisy communication channels are considered. The most challenging part of the optimization is that no closed-form expressions are available for assessing the performance and the optimization problem is nonconvex. The proposed method consists of two steps: (i) the overall NCS performance measure is expressed as a function of rates at all time instants by means of high-rate quantization theory, and (ii) a constrained optimization problem to minimize a weighted quadratic objective function is solved. The proposed method is applied to the problem of state feedback control and the problem of state estimation. Monte Carlo simulations illustrate the performance of the proposed rate allocation. It is shown numerically that the proposed method has better performance when compared to arbitrarily selected rate allocations. Also, it is shown that in certain cases nonuniform rate allocation can outperform the uniform rate allocation, which is commonly considered in quantized control systems, for feedback control over noisy channels.