Control
Razieh Heidari; Alimorad Khajehzadeh; Mahdiyeh Eslami
Abstract
In this paper, an adaptive event-triggered consensus problem considering the time delay of the communication network is studied for heterogeneous multi-agent systems. An event-triggered interval is here considered as a specific delay and unified round trip time (RTT) delay. Furthermore, an efficient ...
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In this paper, an adaptive event-triggered consensus problem considering the time delay of the communication network is studied for heterogeneous multi-agent systems. An event-triggered interval is here considered as a specific delay and unified round trip time (RTT) delay. Furthermore, an efficient optimal predictive-based coordination control strategy is introduced for balancing the non-ideal behaviors of communication channels. In order to evaluate the efficiency of the proposed method for controlling network-based multi-agent systems with coupled subsystems, two stages are studied. In the first stage, the very method is implemented on two coupled continuous stirred tank reactors while in the second one, it is used for controlling the voltage and current of a DC microgrid consisting of several distributed generation units. To prevent the unessential utilization of communication resources, the transfer of information will actually occur in this mechanism if a specific event is triggered. The simulation results show the fact that in spite of being non-ideal and time-delayed communication channels, the proposed technique is capable for improving the performance of power grids.
Control
Farnaz Sabahi
Abstract
Abstract— One of the main problems underlying most optimization theories is local optimum. When time delays are presented, this issue becomes much more problematic. In such conditions, evolutionary optimization algorithms are proven to be helpful. In this paper, quantum genetic algorithm (QGA) ...
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Abstract— One of the main problems underlying most optimization theories is local optimum. When time delays are presented, this issue becomes much more problematic. In such conditions, evolutionary optimization algorithms are proven to be helpful. In this paper, quantum genetic algorithm (QGA) has been used to tackle the stated problem in the framework of delay-dependent linear matrix inequality (LMI) robust H∞ control. QGA is employed to find suitable feedback gains and delay-dependent LMI solvers are concerned to resolve stability issues. In addition, to provide more balance between exploration and exploitation, to increase convergence rate as well as to prevent premature convergence, it is proposed that particle swarm optimization (PSO) is augmented with QGA. Simulation is dealt with LMI-based H∞ control scheme of the QGA and QGA-PSO optimization space from the design point of one-degree freedom single link scara robot. The whole controller satisfies the desired properties for uncertain-but-known constant bounded time delay. Furthermore, one of the drawbacks found in tests of most hybrid global-local strategies, i.e. premature convergence, has been cancelled by the proposed scheme of QGA and PSO.
