The finite control set-model predictive control (FCS-MPC) has been adopted as an excellent choice for the applications of multilevel converters during the last two decades for its salient performance. However, in the ...
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The finite control set-model predictive control (FCS-MPC) has been adopted as an excellent choice for the applications of multilevel converters during the last two decades for its salient performance. However, in the case of modular multilevel converters (MMCs), a high amount of calculation is always involved in the implementation, making the FCS-MPC less suitable especially for an MMC with a high number of submodules. To cope with the issue, this article proposes an MPC technique for the MMC with a very low calculation cost. In each sampling period, the arm voltage references of each phase are determined analytically by solving a constrained quadratic programming problem formulated from the cost function. Both a rigorous and simplified procedure is provided to solve the optimization problem. Then, the four nearest candidates around the arm voltage references are evaluated, leading to a proper selection of arm voltage levels. Several experimental tests on an MMC prototype are carried out to validate the effectiveness of the proposed method. Results show that compared with the conventional FCS-MPC method which evaluates all voltage-level combinations, the proposed scheme presents an apparent advantage in terms of calculation cost while achieving similar performance.
A sequential quadratic programming numerical method is proposed for American option pricing based on the variational inequality formulation. The variational inequality is discretized using the theta-method in time and...
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A sequential quadratic programming numerical method is proposed for American option pricing based on the variational inequality formulation. The variational inequality is discretized using the theta-method in time and the finite element method in space. The resulting system of algebraic inequalities at each time step is solved through a sequence of box-constrained quadratic programming problems, with the latter being solved by a globally and quadratically convergent, large-scale suitable reflective Newton method. It is proved that the sequence of quadratic programming problems converges with a constant rate under a mild condition on the time step size. The method is general in solving the variational inequalities for the option pricing with many styles of optimal stopping and complex underlying asset models. In particular, swing options and stochastic volatility and jump diffusion models are studied. Numerical examples are presented to confirm the effectiveness of the method.
In a previous work, the authors have introduced an upper bound on the stability number of a graph and several of its properties were given. The determination of this upper bound was done by a quadratic programming app...
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In a previous work, the authors have introduced an upper bound on the stability number of a graph and several of its properties were given. The determination of this upper bound was done by a quadratic programming approach whose implementation has given good computational results. We now extend this bound to the weighted case, i.e., an upper bound on the weighted stability of an arbitrary graph with node weights is presented. Similarly to the non-weighted case, the deduced bound allows us to give a necessary and sufficient condition to a weighted graph that attains the given bound. Also a heuristic for determining the maximum weight stable set is proposed which is based on an integrality property of a convex quadratic problem that produces the bound. Some comments about the proposed approach will conclude the paper. (C) 2001 Elsevier Science B.V. All rights reserved.
Based on the parametric variational principle, a general but effective parametric quadratic programming technique satisfying various contact conditions is established for dynamic analysis of contact problems with fric...
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Based on the parametric variational principle, a general but effective parametric quadratic programming technique satisfying various contact conditions is established for dynamic analysis of contact problems with friction and damping. The discretization with respect to time and space leads to a static linear complementary problem (LCP) for each time step which is solved by a quadratic optimization algorithm such as the Lemke algorithm, etc. Thus, the convergence and numerical stability of the solution can be guaranteed. The substructure condensation technique is implemented to handle the unknown contact boundary condition so that the computation effect is considerably reduced. As an application of the method presented, three dynamic contact examples and numerical results are
We analyze the convergence of an infeasible inexact potential reduction method for quadratic programming problems. We show that the convergence of this method is achieved if the residual of the KKT system satisfies a ...
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We analyze the convergence of an infeasible inexact potential reduction method for quadratic programming problems. We show that the convergence of this method is achieved if the residual of the KKT system satisfies a bound related to the duality gap. This result suggests stopping criteria for inner iterations that can be used to adapt the accuracy of the computed direction to the quality of the potential reduction iterate in order to achieve computational efficiency.
The minimax model of quadratic programming with uncertain parameters is considered. The existence of the minimax strategy is proved. A converging iteration algorithm for the calculation of this strategy is proposed. N...
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The minimax model of quadratic programming with uncertain parameters is considered. The existence of the minimax strategy is proved. A converging iteration algorithm for the calculation of this strategy is proposed. Numerical examples of the optimization of the portfolio of securities are considered.
In this paper, a new practical method is presented for solving the non-convex security constraint unit commitment (SCUC) problem in power systems. The accuracy of the proposed method is desirable while the shorter com...
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In this paper, a new practical method is presented for solving the non-convex security constraint unit commitment (SCUC) problem in power systems. The accuracy of the proposed method is desirable while the shorter computation time makes it useful for SCUC solution of large-scale power systems, real-time market operation and long-term SCUC problems. The proposed framework allows inclusion of the valve point effects, warmth-dependent start-up costs, ramp rates, minimum up/down time constraints, multiple fuels costs, emission costs, prohibited operating zones and AC power flow limits in normal and contingency conditions. To solve the non-convex problem, combination of a modified Branch-and-Bound method with the quadratic programming is used as an optimization tool and a developed AC power flow algorithm is applied for considering the security and contingency concerns using the nonlinear/linear AC model. These modifications improve the convergence speed and solution precision of SCUC problem. In the proposed method, in contrast with traditional SCUC algorithms, unit commitment solution, checking and satisfying the security constraints are managed simultaneously. The obtained results are compared with other reported methods for investigating the effectiveness of the proposed method. Also, the proposed method is applied to an Iranian power system including 493 thermal units. (C) 2011 Elsevier Ltd. All rights reserved.
A quadratic programming (QP) approach for deter-mining the coefficients of the McClellan transform is presented for the design of 2-D FIR digital filters. Three features of the proposed method are as follows. First, t...
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A quadratic programming (QP) approach for deter-mining the coefficients of the McClellan transform is presented for the design of 2-D FIR digital filters. Three features of the proposed method are as follows. First, the transform parameters are determined by minimising the integration of the squared errors along the desired contour. Second, a set of linear constraints are incorporated into the QP formulation such that the conventional scaling problem of the transform can be avoided. Third, the optimal cutoff frequencies of a 1-D prototype filter are obtained directly from the QP solution. Several design examples, including fan filters, elliptic filters, diamond filters and bandpass filters, are illustrated to demonstrate the effectiveness of the QP method.
We present a new strategy for choosing primal and dual steplengths in a primal-dual interior-point algorithm for convex quadratic programming. Current implementations often scale steps equally to avoid increases in du...
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We present a new strategy for choosing primal and dual steplengths in a primal-dual interior-point algorithm for convex quadratic programming. Current implementations often scale steps equally to avoid increases in dual infeasibility between iterations. We propose that this rnethod can be too conservative, while safeguarding an unequally-scaled steplength approach will often require fewer steps toward a solution. Computational results are given. (C) 2006 Elsevier Ltd. All rights reserved.
Interest in the seakeeping loads of vessels has increased dramatically in recent years. While many studies focused on predicting seakeeping loads, little attention was given on how loads are transferred to 3D finite-e...
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Interest in the seakeeping loads of vessels has increased dramatically in recent years. While many studies focused on predicting seakeeping loads, little attention was given on how loads are transferred to 3D finite-element models. In current design practice, methods for predicting seakeeping motions and loads are mainly based on the potential flow theory, either strip theory methods or 3D-panel methods. Methods based on strip theory provide reasonable motion prediction for ships and are computationally efficient. However, the load outputs of strip theories are only hull girder sectional forces and moments, such as vertical bending moment and vertical shear force, which cannot be directly applied to a 3D finite-element structural model. Methods-based 3D panel methods can be applied to a wide range of structures, but are computationally expensive. The seakeeping load outputs of panel methods include not only the global hull girder loads, but also panel pressures, which are well suited for 3D finite-element analysis. However, because the panel-based methods are computationally expensive, meshes used for hydrodynamic analyses are usually coarser than the mesh used for structural finite-element analyses. When pressure loads are mapped from one mesh to another, a small discrepancy at the element level will occur regardless of what interpolation method is used. The integration of those small pressure discrepancies along the whole ship inevitably causes an imbalanced structural finite-element model. To obtain equilibrium of an imbalanced structural model, a common practice is to use the 'inertia relief' approach. However, this type of balancing causes a change in the hull girder load distribution, which in turn could cause inaccuracies in an extreme load analysis (ELA) and a spectral fatigue analysis (SFA). This paper presents a practical method to balance the structural model without using inertia relief. The method uses quadratic programming to calculate equivalent nodal
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