An event-triggered robust output feedback control method is proposed for water level tracking of an uncertain three-tank system by using only the level sensor of the target tank. The system model is transformed into a canonical form with uncertainties by coordinate transformation, and the canonical system's state variables are estimated by a higher-order sliding mode differentiator based on the measurement of the target tank's water level. Then an event-triggered robust output feedback controller is constructed. The triggering condition is derived by taking the control gains and event-triggered sampling errors into account, and the control performance is rigorously analyzed. Furthermore, it is shown that the zeno behavior is also excluded. Finally, the effectiveness of the proposed method is verified by experimental studies on a real three-tank system.

FRIT and VRFT are widely applied as representatives of Data-driven control, but the actual closed-loop response cannot be predicted. Recently, Data-driven prediction methods including V-Tiger that predict the actual closed-loop response have been proposed. V-Tiger predicts the virtual frequency response and virtual time response of a closed-loop system from one-shot experimental data to read the settling time and Nyquist locus, but these readings become difficult when the noise is large. Therefore, we propose (1) a stability criterion based on the virtual time response, (2) a noise reduction method that averages multiple virtual time responses using only one-shot experimental data, and (3) a control design method to minimize cost function in frequency domain to achieve robustness against noise.

This study proposes an innovative way to diagnose the state of the organization by analyzing the log data of the company's internal currency to the management of the divided organization. In companies, individual optimization of organizations, silos, isolation of individuals, and division of organizations often become issues. In this study, we quantitatively grasp connections between people from data of a company's transmission and reception logs through an internal currency with the theme of “thanks”, We also verified the relationship with the team's performance to examine how altruistic behavior fills the division between organizations. The analysis results show that brokers who fill structural gaps have an important influence on team performance. And the more broker younger than the average age of the team have connections with key players of other teams, which have the higher the team performance.

This paper proposes a deterministic policy gradient method for port-Hamiltonian systems using an eligibility trace. The deterministic policy gradient method commonly uses one of two types of algorithms, either the on- or off-policy method. The proposed algorithm employs the off-policy method to perform a probabilistic search. In addition, we introduce an eligibility trace to the method to speed up the learning process. A numerical simulation shows the effectiveness of the proposed method.