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Power flow calculation is the most used procedure in electrical power systems. Generally, most of optimization problems in electric power systems need a steady state analysis to evaluate the objective function. Especially, those optimization problems that make use of artificial intelligence techniques, where, due to the high number of iterations, the power flow calculation has a crucial role. In these...
We consider the classic problem of pole placement by state feedback. We revisit the well-known eigenstructure assignment algorithm of Kautsky, Nichols and van Dooren [1] and extend it to obtain a novel parametric form for the pole-placing feedback matrix that can deliver any set of desired closed-loop eigenvalues, with any desired multiplicities. This parametric formula is then employed to introduce...
This paper introduces the notion of localizable distributed systems. These are systems for which a distributed controller exists that limits the effect of each disturbance to some local subset of the entire plant, akin to spatio-temporal dead-beat control. We characterize distributed systems for which a localizing state-feedback controller exists in terms of the feasibility of a set of linear equations...
Many real-world optimization problems are dynamic (time dependent) and require an algorithm that is able to continuously track a changing optimum over time. In this paper, we investigate a recently proposed algorithm for dynamic continuous optimization, called MLSDO (Multiple Local Search algorithm for Dynamic Optimization). MLSDO is based on several coordinated local search agents and on the archiving...
We consider the problem of approximating an integer program by first solving its relaxation linear program and "rounding" the resulting solution. For several packing problems, we prove probabilistically that there exists an integer solution close to the optimum of the relaxation solution. We then develop a methodology for converting such a probabilistic existence proof to a deterministic...
We present parallel algorithms to compute the determinant and characteristic polynomial of n×n-matrices and the gcd of polynomials of degree ≤n. The algorithms use parallel time O(log2n) and a polynomial number of processors. We also give a fast parallel Las Vegas algorithm for the rank of matrices. All algorithms work over arbitrary fields.
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