Iterative Encoder-Controller Design for Feedback Control Over Noisy Channels

We study a closed-loop control system with state feedback transmitted over a noisy discrete memoryless channel. With the objective to minimize the expected linear quadratic cost over a finite horizon, we propose a joint design of the sensor measurement quantization, channel error protection, and controller actuation. It is argued that despite that this encoder-controller optimization problem is known to be hard in general, an iterative design procedure can be derived in which the controller is optimized for a fixed encoder, then the encoder is optimized for a fixed controller, etc. Several properties of such a scheme are discussed. For a fixed encoder, we study how to optimize the controller given that full or partial side-information is available at the encoder about the symbols received at the controller. It is shown that the certainty equivalence controller is optimal when the encoder is optimal and has full side-information. For a fixed controller, expressions for the optimal encoder are given and implications are discussed for the special cases when process, sensor, or channel noise is not present. Numerical experiments are carried out to demonstrate the performance obtained by employing the proposed iterative design procedure and to compare it with other relevant schemes.