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In this paper the predictive control of switching system is introduced to the DC/AC converter. Our aim is to control the output power of converter closer to the reference. By considering the working status of DC/AC converter is actually switched among several definite subsystems, the switching system model of DC/AC converter is constructed. The tracking problem of converter output power can be changed to be that of its three-phase output currents. Based on the switching system model of converter, the three-phase output currents of those subsystems are predicted and the switching command is determined by examining the discrepancies between the three-phase predictive currents corresponding to each subsystem and the reference ones. Simulations demonstrate that our control scheme for DC/AC converter connected with ultra-capacitor has great advantages in output power tracking and sinusoidal output current waveforms.

Ice storage air-conditioning system can bring benefits to power supplier and consumers for its advantage of shifting power consumption at peak hours during day to the off-peak hours at night. In this paper, we adopted an improved particle swarm optimization algorithm to develop an optimal control strategy for ice storage air-conditioning system with the aim of minimizing operation cost subject to various operational constrains. Comparing with the usual chiller-priority and ice-storage-priority control strategy, the proposed control scheme can not only meet the building cooling load but also achieve the minimum operation cost.

Abstract: An adaptive predictive pinning control is proposed to suppress the cascade in coupled map lattices (CMLs). Two monitoring strategies are applied: (1) A specific fraction of nodes with the highest degree or betweenness are chosen to constitute the set of monitored nodes; (2) During the cascade, an adaptive pinning control is implemented, in which only the nodes in the monitored set whose current state is normal but whose predictive state is abnormal, are pinned with the predictive controller. Simulations show that for the scale-free (SF) CML the degree-based monitoring strategy is advantageous over the betweenness-based strategy, while for the small-world (SW) CML the situation is the opposite. With the adaptive predictive pinning control, the fewer local controllers can effectively suppress the cascade throughout the whole network.

The local-world (LW) evolving network model shows a transition for the degree distribution between the exponential and power-law distributions, depending on the LW size. Cascading failures under intentional attacks in LW network models with different LW sizes were investigated using the cascading failures load model. We found that the LW size has a significant impact on the network’s robustness against deliberate attacks. It is much easier to trigger cascading failures in LW evolving networks with a larger LW size. Therefore, to avoid cascading failures in real networks with local preferential attachment such as the Internet, the World Trade Web and the multi-agent system, the LW size should be as small as possible.