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Full-Text Articles in Physical Sciences and Mathematics
A Neural Network Approach To Navigation Of A Mobile Robot And Obstacle Avoidance In Dynamic And Unknown Environments, Farhad Shamsfakhr, Bahram Sadeghi Bigham
A Neural Network Approach To Navigation Of A Mobile Robot And Obstacle Avoidance In Dynamic And Unknown Environments, Farhad Shamsfakhr, Bahram Sadeghi Bigham
Turkish Journal of Electrical Engineering and Computer Sciences
Mobile robot navigation and obstacle avoidance in dynamic and unknown environments is one of the most challenging problems in the field of robotics. Considering that a robot must be able to interact with the surrounding environment and respond to it in real time, and given the limited sensing range, inaccurate data, and noisy sensor readings, this problem becomes even more acute. In this paper, we attempt to develop a neural network approach equipped with statistical dimension reduction techniques to perform exact and fast robot navigation, as well as obstacle avoidance in such a manner. In order to increase the speed …
A Novel Approach To Solve Transient Stability Constrained Optimal Power Flow Problems, Huy Nguyen-Duc, Linh Tran-Hoai, Dieu Vo Ngoc
A Novel Approach To Solve Transient Stability Constrained Optimal Power Flow Problems, Huy Nguyen-Duc, Linh Tran-Hoai, Dieu Vo Ngoc
Turkish Journal of Electrical Engineering and Computer Sciences
This paper proposes an approach to solve the transient stability constraint optimal power flow (TSC-OPF) problem. The transient stability constraints are expressed as the critical clearing time (CCT) of different contingencies, and are approximated using artificial neural networks (ANNs). The ANNs provide a nonlinear, differentiable mapping between the load flow variables and the CCT. As a result, the TSC-OPF with multiple transient stability constraints can be solved very efficiently with little additional computational burden. The effectiveness of the proposed method is demonstrated with the IEEE 39 bus and the IEEE 300 bus systems.