Energy Optimization on Wireless-networked Control Systems (W-NCSs) Using Linear Quadratic Gaussian (LQG)

In a wireless networked control system (W-NCS), energy is required to transmit a sensor reading to the controller. It should be noted that the packet success rate (PSR) is an essential factor in the control performance, and PSR is directly proportional to the energy per symbol. Hence, it requires a significant amount of energy to have perfect control performance. However, in most cases in wireless sensor network scenarios, each node is attached to a limited power battery. Therefore, an energy optimization scheme that can harvest energy while maintaining the control performance is essentially required. The combination of Kalman filter and Linear Quadratic Regulator (LQR) that is known as Linear Quadratic Gaussian (LQG) is used as the backbone of the scheme to estimate the state and synthesize the optimal control. In addition, the optimal power scheduler (PS) is introduced to minimize energy usage while maintaining control performance. The finite block length approach is applied to achieve the upper bound of packet error rate. The results of energy consumption optimization showed that the scheme worked perfectly, wherein the energy per symbol usage is low, and the stability of the dynamic system is well maintained.