Event-based Schemes Research Articles

Energy-conserving event-triggered control for multiagent systems with limited resources

An energy-conserving event-driven control method is developed for multiagent systems with unknown disturbances to achieve low-energy formation control. Firstly, an energy-conserving event-driven scheme is developed to save energy by introducing a second trigger function, which is utilized to switch the control input to zero when the consensus error is small. Then, a dynamic energy-conserving event-driven scheme is designed to further decrease the frequency of communication and control by establishing a positive dynamic variable to increase the trigger threshold. Under the designed energy-conserving event-based schemes, the energy consumption during the system stability is significantly reduced, the communication burden is decreased, and the system is Zeno-free and bounded stable. Finally, a four-agent formation example is illustrated to show the effectiveness of the proposed energy-conserving schemes.

Event-based model predictive control for nonlinear systems with dynamic disturbance

In this paper, we investigate the event-based model predictive control (MPC) for constrained nonlinear systems with dynamic disturbance. An event-triggered disturbance prediction MPC (DPMPC) scheme and a self-triggered counterpart, which explicitly consider the disturbance dynamics, are proposed. For the event-triggered DPMPC scheme, the triggering condition relying on the state prediction error and the predicted disturbance sequence, updates at each time step based on the system states. For the self-triggered DPMPC scheme, the next triggering instant is determined by using the optimal state sequence and predicted disturbance sequence. In both event-based schemes, the optimal control problems are solved only at triggering instants, thus reducing the consumption of computational resource. The effectiveness of the two schemes is demonstrated by a simulation example.

Asynchronous event-based sampling data for impulsive protocol on consensus of non-linear multi-agent systems

In this paper, we discuss the consensus problem of non-linear multi-agent systems where an impulsive protocol with event-based asynchronously sampled data is adopted. Systems that communicate by data asynchronously sampled in limited time intervals are constructed. By separating time instants at which the sampling and communication occur into different ones, resources for such activations that every agent must execute can be reallocated to reduce the system load at communication instants. Event-based schemes are introduced to manipulate the sampling behavior. Two cases that with and without leader in directed networks topologies are both investigated. Sufficient conditions for system parameters and the event-based sampling schemes are given to guarantee the consensus. Numerical simulations are presented to illustrate the effectiveness of our proposed method.

Event-based Cubature Kalman Filter for Smart Grid Subject to Communication Constraint

Accurate real-time estimation plays an important role in smart grids. Although various filtering algorithms, such as unscented Kalman filter (UKF), have been proposed for phasor measurement unit (PMU), they occupy huge communication bandwidth without specific concern, which puts heavy burden on the communication network especially when wireless communications are applied. In order to relief this burden, the event-based cubature Kalman filter (EBCKF) is proposed based on event-based schemes in this paper. The event-based strategy guarantees that only the observations containing innovational information are transmitted, and cubature Kalman filter (CKF), which is based on the spherical cubature integration, provides more accurate estimation than UKF. Besides, the design-oriented communication rate is provided corresponding to the event-based strategy design. The proposed filter can effectively reduce the communication rate while ensuring the accuracy of filtering. Finally, the standard IEEE 39-bus system is utilized to verify the feasibility and performance of the proposed method.

Sharing RFID and complex event data among organizations

Integrating RFID data from various sources in a value chain is an important requirement for leveraging the full potential of the technology. To facilitate this crucial integration, the global standardization organization GS1 is currently developing a range of service specifications. Yet, the services specified so far do not enable event-based interaction schemes and do not leverage the detection of distributed complex events. In this paper we propose to fill this gap by means of a peer-to-peer based broker network that can realize event-based interaction on top of existing specifications. For this infrastructure we present a new method to improve in-network processing. As shown by our experiments, our method significantly reduces overall system load by exploiting a priori knowledge about the observed processes.