Summary
This paper considers resilient event‐triggered control problem for a class of networked systems subject to randomly occurring deception attacks. First, a new memory event‐triggered scheme (METS) is proposed to reduce the utilization of communication resources while maintaining desired system performance. Different from some existing event‐triggered schemes, some recently released packets are firstly utilized in the proposed METS, which provides a better flexibility to improve the system dynamics. Second, considering the security problem of the networked control systems, a randomly occurring deception attack model is employed where the bounded malicious signals are injected by the adversary. Considering both the effects of METS and deception attack, new type of networked control system model is constructed and the corresponding memory state‐feedback controller is designed. Then, sufficient conditions for the asymptotical stability of the systems are derived by using a Lyapunov functional technique. Finally, the obtained results are verified through a pendulum system, which demonstrates the effectiveness of the proposed methods.
Plug-in hybrid electric vehicles (PHEVs) have been recognized as one of the most promising vehicle categories nowadays due to their low fuel consumption and reduced emissions. Energy management is critical for improving the performance of PHEVs. This paper proposes an energy management approach based on a particle swarm optimization (PSO) algorithm. The optimization objective is to minimize total energy cost (summation of oil and electricity) from vehicle utilization. A main drawback of optimal strategies is that they can hardly be used in real-time control. In order to solve this problem, a rule-based strategy containing three operation modes is proposed first, and then the PSO algorithm is implemented on four threshold values in the presented rule-based strategy. The proposed strategy has been verified by the US06 driving cycle under the MATLAB/Simulink software environment. Two different driving cycles are adopted to evaluate the generalization ability of the proposed strategy. Simulation results indicate that the proposed PSO-based energy management method can achieve better energy efficiency compared with traditional blended strategies. Online control performance of the proposed approach has been demonstrated through a driver-in-the-loop real-time experiment.
OPEN ACCESSEnergies 2015, 8 3662
In this research study, a multiterminal voltage source converter (VSC) medium voltage DC (MVDC) distribution network hierarchical control scheme is proposed for renewable energy (RE) integration in a co-simulation environment of MATLAB and PSCAD/EMTDC. A DC optimal power flow (DC OPF) secondary controller is created in MATLAB. In PSCAD/EMTDC, the main circuit containing the adaptive DC voltage droop with a dead band and virtual synchronous generator (VSG) based primary controller for the VSCs is implemented. The simulation of the MVDC network under the proposed hierarchical control scheme is investigated considering variations in wind and solar photovoltaic (PV) power. The network is also connected to the standard IEEE-39 bus system and the hierarchical scheme tested by assessing the effect of tripping as well as restoration of the REs. The results show that during random variations in active power such as increasing wind and PV power generation, a sudden reduction or tripping of wind and PV power, the primary controller ensures accurate active power sharing amongst the droop-based VSCs as well as regulates DC voltage deviations within the set range of 0.98–1.02 pu with an enhanced dynamic response. The DC OPF secondary control optimizes the system’s losses by 38% regularly giving optimal droop settings to the primary controllers to ensure proper active power balance and DC voltage stability. This study demonstrates that the hierarchical control strategy is effective for RE integration in the MVDC distribution network.
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