Event-triggered distributed secure state estimation for homologous sensor attacks.

Network security technology is capable of mitigating attack signals launched by malicious attackers, thereby safeguarding and bolstering system security. Secure state estimation is a type of network defense technology that involves reconstructing the system state by measuring potential attacks. The relevant research has also been expanded to distributed systems to enable collaborative secure state estimation among different agents facing homogeneous attacks; however, such research significantly enhance the communication load of the system. On the other hand, if the homogeneous attack is non-existent or consistent, excessive network communication is definitely inefficient. An event-triggered approach is a potent technique that can alleviate communication overhead while having minimal impact on system performance. This paper proposes a mechanism for event-triggered transmission in the context of distributed secure state estimation. While communication latency and data transmission disorder may be present within the communication network, the estimation error of the proposed observer is constrained and bounded. The simulation results indicate that for stable malicious attack signals, system communication can be divided into high-frequency and low-frequency communication periods. The simulation results also shows that the maximum estimation error is proportional to the trigger threshold, allowing the observer's performance to be finely tuned to the required precision.

Optimization of insulin pump therapy based on high order run-to-run control scheme.

BACKGROUND AND OBJECTIVES: Continuous subcutaneous insulin infusion (CSII) pump is widely considered a convenience and promising way for type 1 diabetes mellitus (T1DM) subjects, who need exogenous insulin infusion. In the standard insulin pump therapy, there are two modes for insulin infusion: basal and bolus insulin. The basal-bolus therapy should be individualized and optimized in order to keep one subject's blood glucose (BG) level within the normal range; however, the optimization procedure is troublesome and it perturb the patients a lot. Therefore, an automatic adjustment method is needed to reduce the burden of the patients, and run-to-run (R2R) control algorithm can be used to handle this significant task. METHODS: In this study, two kinds of high order R2R control methods are presented to adjust the basal and bolus insulin simultaneously. For clarity, a second order R2R control algorithm is first derived and studied. Furthermore, considering the differences between weekdays and weekends, a seventh order R2R control algorithm is also proposed and tested. RESULTS: In order to simulate real situation, the proposed method has been tested with uncertainties on measurement noise, drifts, meal size, meal time and snack. The proposed method can converge even when there are ±60 min random variations in meal timing or ±50% random variations in meal size. CONCLUSIONS: According to the robustness analysis, one can see that the proposed high order R2R has excellent robustness and could be a promising candidate to optimize insulin pump therapy.