Search Results (7)

This paper investigates the collaborative obstacle avoidance control of multiple autonomous underwater vehicles (AUVs) in underwater environments with communication delays and intermittent connectivity. Firstly, a novel time-delay piecewise differential inequality incorporating an exponential decay term is established, which systematically integrates state delay, intermittent control strategies, and event-triggered mechanisms. Secondly, the traditional request-response mechanism is replaced by a broadcast communication protocol, significantly reducing the requirement for continuous inter-AUV communication and enhancing overall communication efficiency. Thirdly, the obstacle avoidance problem of multiple AUVs is addressed through the implementation of a nominal-optimized controller. Obstacle avoidance safety conditions between unmanned vehicles and obstacles are derived by employing a zeroing control barrier function (CBF). Based on these safety conditions and input constraints, a quadratic programming (QP) framework is formulated to dynamically optimize control signals in real time, thereby ensuring the safe operation of the multi-AUV system. Finally, the efficacy of the proposed control method is validated through comprehensive simulation results, demonstrating its robustness and practical performance. Full article

This paper studies the exponential stability in the mean square of the stochastic complex networks with time-varying coupling under an intermittent dynamic event-triggered control. A dynamic term and an exponential function are introduced into the event-triggered mechanism to reduce the number of control updates. Simultaneously, the minimum inter-execution time for every sample path solution of the stochastic complex networks, independent mathematical expectation, is obtained. Unlike previous research, the event-triggered mechanism under the stochastic version is more reasonable due to the absence of mathematical expectations in the event-triggered function. Furthermore, using the average control rate for intermittent strategy and the Lyapunov method, sufficient conditions for exponential stability in the mean square under intermittent dynamic event-triggered control are derived. Finally, an example with numerical simulations is provided to validate the feasibility of the theoretical results. Full article

In this paper, we investigate the consensus control problem of Euler–Lagrange systems which can be used to describe the motion of various mechanical systems such as manipulators and quadcopters. We focus on consensus control strategies, which are important for achieving coordinated behavior in multi-agent systems. The paper considers the key challenges posed by random communication delays and packet losses that are increasingly common in networked control systems. In addition, it is assumed that each system receives information from neighboring agents intermittently. Addressing these challenges is critical to ensure the reliability and efficiency of such systems in real-world applications. Communication delay is time-varying and can be very large, but should be smaller than some bounded constant. To decrease the frequency of control input updates, we implement an event-triggered scheme that regulates the controller’s updates for each agent. Specifically, it does not update control inputs at traditional fixed intervals, but responds to predefined conditions and introduces a dynamic consensus item to handle information irregularities caused by communication delays and intermittent information exchange. The consensus can be achieved if the communication graph of agents contains a spanning tree with the desired velocity as the root node. That is, all Euler–Lagrange systems need to obtain the desired velocity, directly or indirectly (via neighbors), to reach consensus. We establish that the Zeno behavior can be avoided, ensuring a positive minimum duration between successive event-triggered instances. Finally, we provide simulation results to show the performance of our proposed algorithm. Full article

In this paper, an event-triggered distributed secondary control, along with an energy management algorithm, was developed to ensure the voltage stability and power management of a DC microgrid containing batteries and renewable energy sources, such as PV systems and wind turbines. The energy management algorithm, employing fuzzy logic control, governs power flow based on the generation status of sources and the charging rate of the battery. Consequently, the control algorithm shields the battery from overcharging and over-discharging situations, simultaneously ensuring energy quality within the microgrid. Sampled-data-based event-triggered control is integrated into the proposed distributed secondary control to alleviate communication burdens between controllers, effectively avoiding Zeno behavior. To demonstrate the efficacy of the proposed control algorithm, several experimental studies were conducted on a real DC microgrid prototype. The results obtained confirmed the controller’s effectiveness. With the proposed control algorithm, autonomous control has been developed to ensure the safe and continuous operation of loads in island-mode microgrids, incorporating PV systems, wind turbines, and batteries, while also minimizing communication overhead. This control system adeptly manages power flow, safeguards the battery against overcharging and over-discharging, and optimizes the efficiency of intermittent energy sources. Full article

Several studies demonstrated a link between obstructive sleep apnea (OSA) and the development of insulin resistance. However, the main event triggering insulin resistance in OSA remains to be clarified. Herein, we investigated the effect of mild and severe chronic intermittent hypoxia (CIH) on whole-body metabolic deregulation and visceral adipose tissue dysfunction. Moreover, we studied the contribution of obesity to CIH-induced dysmetabolic states. Experiments were performed in male Wistar rats submitted to a control and high-fat (HF) diet. Two CIH protocols were tested: A mild CIH paradigm (5/6 hypoxic (5% O₂) cycles/h, 10.5 h/day) during 35 days and a severe CIH paradigm (30 hypoxic (5% O₂) cycles, 8 h/day) during 15 days. Fasting glycemia, insulinemia, insulin sensitivity, weight, and fat mass were assessed. Adipose tissue hypoxia, inflammation, angiogenesis, oxidative stress, and metabolism were investigated. Mild and severe CIH increased insulin levels and induced whole-body insulin resistance in control animals, effects not associated with weight gain. In control animals, CIH did not modify adipocytes perimeter as well as adipose tissue hypoxia, angiogenesis, inflammation or oxidative stress. In HF animals, severe CIH attenuated the increase in adipocytes perimeter, adipose tissue hypoxia, angiogenesis, and dysmetabolism. In conclusion, adipose tissue dysfunction is not the main trigger for initial dysmetabolism in CIH. CIH in an early stage might have a protective role against the deleterious effects of HF diet on adipose tissue metabolism. Full article

A quantized-feedback-based adaptive event-triggered tracking problem is investigated for strict-feedback nonlinear systems with unknown nonlinearities and external disturbances. All state variables are quantized through a uniform quantizer and the quantized states are only measurable for the control design. An approximation-based adaptive event-triggered control strategy using quantized states is presented. Compared with the existing recursive quantized feedback control results, the primary contributions of the proposed strategy are (1) to derive a quantized-states-based function approximation mechanism for compensating for unknown and unmatched nonlinearities and (2) to design a quantized-states-based event triggering law for the intermittent update of the control signal. A Lyapunov-based stability analysis is provided to conclude that closed-loop signals are uniformly ultimately bounded and there exists a minimum inter-event time for excluding Zeno behavior. In simulation results, it is shown that the proposed quantized-feedback-based event-triggered control law can be implemented with less than 10% of the total sample data of the existing quantized-feedback continuous control law. Full article

This paper addresses the synchronization problem of multi-agent systems with nonlinear controller outputs via event-triggered control, in which the combined edge state information is utilized, and all controller outputs are nonlinear to describe their inherent nonlinear characteristics and the effects of data transmission in digital communication networks. First, an edge-event-triggered policy is proposed to implement intermittent controller updates without Zeno behavior. Then, an edge-self-triggered solution is further investigated to achieve discontinuous monitoring of sensors. Compared with the previous event-triggered mechanisms, our policy design considers the controller output nonlinearities. Furthermore, the system’s inherent nonlinear characteristics and networked data transmission effects are combined in a unified framework. Numerical simulations demonstrate the effectiveness of our theoretical results. Full article