Control with Communication Constraints

Researchers: Erik Johannesson, Anders Rantzer, Bo Bernhardsson, Andrey Ghulchak

Funding: Swedish Research Council through LCCC and EU/IST/FP7 through CHAT

Classical control theory assumes perfect communication, without limitations, between different parts of the control system and the process. A current trend in control systems is, however, for the systems to become more distributed and more dependent on communication over different types of networks. This makes it necessary to study the implications of the resulting communication constraints. In the control community this has spurred interest in the research of the interplay between communication and control. The results have mainly concerned fundamental limitations of control performance that arise from communication constraints.

In this project, the goal is to design optimal controllers and estimators for some specific problems with limited communication. We model the communication constraints by analog communication channels with limited SNR (signal to noise ratio). These channels give an incentive to perform coding and decoding of the transmitted signal, in addition to the usual filtering and computation of control signals. The problem of designing the controller, coder and decoder simultaneously is a distributed control problem, which can be solved using tools from convex optimization. Currently, we are focusing on two specific problem structures, which represent an estimation problem and a control problem respectively.

Estimation over Channel with SNR Constraint

The objective is to design the coder and the decoder so that the estimation error is minimized. This can be interpreted as a real-time coding problem (if P is replaced by a time delay) with input noise. Another interpretation is that this concerns the design of a disturbance feedforward compensator, where the sensor and the actuator are geographically separated.

Control over Channel with SNR Constraint

In this problem, the objective is to design an observer/coder C and decoder/controller D that stabilize the plant and minimizes the effect caused by a plant disturbance (not shown).



Erik Johannesson: Control and Communication with Signal-to-Noise Ratio Constraints. PhD Thesis ISRN LUTFD2/TFRT--1087--SE, Department of Automatic Control, Lund University, Sweden, October 2011.

Erik Johannesson: "Signal Estimation over Channels with SNR Constraints and Feedback". In 18th IFAC World Congress, Milano, Italy, August 2011.

Erik Johannesson, Anders Rantzer, Bo Bernhardsson: "Optimal Linear Control for Channels with Signal-to-Noise Ratio Constraints". In 2011 American Control Conference, San Francisco, California, USA, June 2011.

Erik Johannesson, Andrey Ghulchak, Anders Rantzer, Bo Bernhardsson: "MIMO Encoder and Decoder Design for Signal Estimation". In Proc. 19th International Symposium on Mathematical Theory of Networks and Systems, Budapest, Hungary, July 2010.

Erik Johannesson, Anders Rantzer, Bo Bernhardsson, Andrey Ghulchak: "Encoder and Decoder Design for Signal Estimation". In 2010 American Control Conference, Baltimore, Maryland, USA, June 2010.