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How to design an effective and efficient load-frequency controller (LFC) for a multi-area interconnected power system to improve its power quality is a challenging issue. In order to deal with this issue, this paper presents a novel distributed fractional-order PID (DFOPID) control method for the load-frequency control of each area by using an adaptive population-based extremal optimization (APEO)...
When optimizing an multiobjective optimization problem, the evolution of population can be regarded as a approximation to the Pareto Front (PF). Motivated by this idea, we propose an adaptive region decomposition framework: MOEA/D-AM2M for the degenerated Many-Objective optimization problem (MaOP), where degenerated MaOP refers to the optimization problem with a degenerated PF in a subspace of the...
The particle swarm optimization (PSO) algorithm is a new and efficient intelligent search algorithm. However, most of the existing improved PSO algorithm in the late search efficiency is low, and easy fall into local minima, In view of this situation, a kind of new strategy of inertia weight adaptive changes been proposed in this paper, which enable the algorithm in the interim iterations can quick...
Considering the slow convergence problem of conventional interval particle swarm optimization algorithm based on static shrinking strategy (SIPSO), this paper proposes a new dynamic shrinking strategy to form a new interval particle swam optimization algorithm (DIPSO) to improve the SIPSO, which can make the interval shrinking more flexible and be conducive to the quick convergence. The simulation...
Trains with automatic train operation (ATO)-communication-based train control (CBTC) have the capability to follow a predesigned or calculated speed profile and also can change the control command at any point of the route. This paper presents the advances in the research about designing driving profiles for ATO trains under the CBTC signalling system. Two algorithms based on simulation are proposed,...
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