Resource Savings in Wireless Sensor Networks by Replacing Classical Control with Markovian Model-Based Control

The main obstacle to implementing classic control projects over long distances is the high cost of installing and maintaining the infrastructure necessary to guarantee reliable communication, for instance, through wired networks. Wireless Sensor Networks (WSN) came as an alternative to the need for cabling. However, given the loss of information inherent to this type of transmission, to guarantee the stability of the closed-loop system, it is necessary to include several nodes (close to each other) throughout the communication network. In this context, this paper describes the possibility of performing remote control via WSN, aiming to improve the trade-off: good performance of the control system and reducing network expenses by allowing a decrease in the number of nodes. The proposed strategy consists of replacing the use of a classical control technique (Linear Quadratic Regulator - LQR) that requires full-reliable communication with a Markov model-based control technique, which provides theoretical guarantees of closed-loop system stability even when there is the possibility of packet loss (as is usual in WSN context). To illustrate the efficiency of the proposed approach, simulations of the dynamic behavior of a plant controlled through a wireless communication network are carried out using real statistical data obtained via experimental tests in a workbench emulation of a WSN with two nodes.