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Xiang Wu
Researcher at Southeast University
Publications - 26
Citations - 262
Xiang Wu is an academic researcher from Southeast University. The author has contributed to research in topics: Optimal control & Computer science. The author has an hindex of 7, co-authored 16 publications receiving 147 citations. Previous affiliations of Xiang Wu include Guizhou Normal University.
Papers
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Optimal control of constrained switched systems and application to electrical vehicle energy management
TL;DR: A numerically tractable method is provided to solve the optimal control problem of constrained switched systems with input and state constraints and is transformed into a nonlinear parameter optimization problem, which can be solved by using any gradient-based optimization method.
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Computational method for optimal control of switched systems with input and state constraints
TL;DR: Based on an improved conjugate gradient algorithm and a discrete filled function method, an improved bi-level algorithm is proposed to solve this optimization problem of switched systems with input and state constraints and results indicate that the proposed algorithm is globally convergent.
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Feasibility study to damp power system multi-mode oscillations by using a single FACTS device
TL;DR: In this paper, the authors proposed a novel scheme of damping power system multi-mode oscillations by using a single FACTS device and presented the results of feasibility study of the proposed scheme.
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Computational method for optimal machine scheduling problem with maintenance and production
TL;DR: By combining a time-scaling transformation, a second-order smoothing technique and a penalty function method, an improved Newton algorithm is developed for solving an optimal scheduling problem of maintenance and production for a machine.
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Optimal switching control for drug therapy process in cancer chemotherapy
TL;DR: This paper obtains an equivalent optimal control problem of constrained nonlinear system by using the time-scaling transformation, the smoothing technique, and the idea of l1 penalty function method, which is transformed into a nonlinear parameter optimization problem.