In this paper, a mixed-integer quadratic programming approach is proposed for the short-term hydro scheduling problem, considering head-dependency, discontinuous operating regions and discharge ramping constraints. As...
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In this paper, a mixed-integer quadratic programming approach is proposed for the short-term hydro scheduling problem, considering head-dependency, discontinuous operating regions and discharge ramping constraints. As new contributions to earlier studies, market uncertainty is introduced in the model via price scenarios, and risk aversion is also incorporated by limiting the volatility of the expected profit through the conditional value-at-risk. Our approach has been applied successfully to solve a case Study based on one of the main Portuguese cascaded hydro systems, requiring a negligible computational time. (C) 2011 Elsevier Ltd. All rights reserved.
The control system for energy-efficient train operation with the inclusion of a detailed train motion model and train traction system energy efficiency is presented in the paper. A piecewise affine train model is cons...
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The control system for energy-efficient train operation with the inclusion of a detailed train motion model and train traction system energy efficiency is presented in the paper. A piecewise affine train model is constructed with the parameters obtained for the electromotive train of an industrial manufacturer. The model encompasses intrinsic features of the train system such as linearized resistance force, a set of traction and braking force physical limitations and passengers comfort constraints. The resulting quadratic optimization problem is solved parametrically through dynamic programming giving the off-line precomputed optimal control law that is a function of train speed and traversed path. The on-line computed traction force profile is then tuned with respect to the traction system energy efficiency. The developed control system is evaluated on a detailed real case study scenario put together with a railway operator and the train manufacturer. The presented results show the possibility of significant energy consumption reductions achieved by energy-efficient train control.
We present numerical results of a comparative study of codes for nonlinear and nonconvex mixed-integer optimization. The underlying algorithms are based on sequential quadraticprogramming (SQP) with stabilization by ...
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We present numerical results of a comparative study of codes for nonlinear and nonconvex mixed-integer optimization. The underlying algorithms are based on sequential quadraticprogramming (SQP) with stabilization by trust-regions, linear outer approximations, and branch-and-bound techniques. The mixed-integer quadratic programming subproblems are solved by a branch-and-cut algorithm. Second order information is updated by a quasi-Newton update formula (BFGS) applied to the Lagrange function for continuous, but also for integer variables. We do not require that the model functions can be evaluated at fractional values of the integer variables. Thus, partial derivatives with respect to integer variables are replaced by descent directions obtained from function values at neighboring grid points, and the number of simulations or function evaluations, respectively, is our main performance criterion to measure the efficiency of a code. Numerical results are presented for a set of 100 academic mixed-integer test problems. Since not all of our test examples are convex, we reach the best-known solutions in about 90 % of the test runs, but at least feasible solutions in the other cases. The average number of function evaluations of the new mixed-integer SQP code is between 240 and 500 including those needed for one-or two-sided approximations of partial derivatives or descent directions, respectively. In addition, we present numerical results for a set of 55 test problems with some practical background in petroleum engineering.
This paper treats the problem of position formation flight control of a group of three multirotor aerial vehicles under obstacle and collision avoidance constraints. In order to solve the problem, a distributed archit...
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This paper treats the problem of position formation flight control of a group of three multirotor aerial vehicles under obstacle and collision avoidance constraints. In order to solve the problem, a distributed architecture with model predictive controllers for each vehicle includes a set of convex constraints on the vehicles's position to prevent collisions with other vehicles and obstacles. The resulting distributed scheme controls the formation based on a virtual structure approach where the computers of the architecture exchange position data through diagrams in Simulink. The performance of the method is assessed through simulations considering that the vehicles are subject to disturbance forces and the results show the effectiveness and the ability of the control architecture to handle the obstacle and collision avoidance constraints.
In the present article, we discuss a general concept of lifting a non-convex quadratic optimization problem into a convex program with matrix variables, and then apply it to construct two kinds of equivalent lifted pr...
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In the present article, we discuss a general concept of lifting a non-convex quadratic optimization problem into a convex program with matrix variables, and then apply it to construct two kinds of equivalent lifted problems, which are completely positive programs (linear programs with completely positive matrix variables) for a class of quadratic optimization problem with linear inequality and mixed binary constraints. The duals of the resulting completely positive programs, which are copositive programs, are constructed. It is shown that, under some conditions, the dual problems are strictly feasible, such that strong duality holds and existing numerical methods for both primal and dual problems can be applied.
This article studies the problem of obtaining equilibrium clearing prices for markets with non-convexities when it is relevant to account for convex quadratic deliverability costs and constraints. In a general market,...
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This article studies the problem of obtaining equilibrium clearing prices for markets with non-convexities when it is relevant to account for convex quadratic deliverability costs and constraints. In a general market, such a situation arises when quadratic commodity or transactions costs are relevant. In the particular case of electricity markets, there is a mix of resources including dispatchable and renewable energy sources, leading to the presence of integer variables and quadratic costs reflecting ramping needs. To illustrate our results, we compute and analyze the equilibrium clearing prices of the Scarfs classical market problem with the addition of ramping costs. (C) 2019 Elsevier B.V. All rights reserved.
The uncapacitated plant location problem under uncertainty is formulated in a mean-variance framework with prices in various markets correlated according to their response to a common random factor. This formulation ...
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The uncapacitated plant location problem under uncertainty is formulated in a mean-variance framework with prices in various markets correlated according to their response to a common random factor. This formulation leads to a mixed-integer quadratic programming problem. However, for a given integer solution, the problem lends itself to a very simple solution procedure. Because of the simplicity of this algorithm, reasonably large problems should be solvable through the use of existing branch-and-bound techniques. Except for the sorting procedure, the computation time increases at most linearly with the size of the nodal subproblem. Dominance holds for the plant location problem addressed here, allowing some relaxation of Jucker and Carlson's (1976) independence assumption.
Dictionary learning for sparse representations is generally conducted in two alternating steps-sparse coding and dictionary updating. In this paper, a new approach to solve the sparse coding step is proposed. Because ...
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Dictionary learning for sparse representations is generally conducted in two alternating steps-sparse coding and dictionary updating. In this paper, a new approach to solve the sparse coding step is proposed. Because this step involves an l(0)-norm, most, if not all, existing solutions only provide a local or approximate solution. Instead, a real l(0) optimization is considered for the sparse coding problem providing a global solution. The proposed method reformulates the optimization problem as a mixed-integerquadratic program (MIQP), allowing then to obtain the global optimal solution by using an off-the-shelf optimization software. Because computing time is the main disadvantage of this approach, two techniques are proposed to improve its computational speed. One is to add suitable constraints and the other to use an appropriate initialization. The results obtained on an image denoising task demonstrate the feasibility of the MIQP approach for processing real images while achieving good performance compared to the most advanced methods.
Stiction is a nonlinear friction phenomenon that causes poor performance of control loops in the process industries. In this work, we develop a mixed-integer MPC (Model Predictive Control) formulation including valve ...
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ISBN:
(纸本)9780993244049
Stiction is a nonlinear friction phenomenon that causes poor performance of control loops in the process industries. In this work, we develop a mixed-integer MPC (Model Predictive Control) formulation including valve dynamics for a sticky valve in order to improve control loop performance. The introduction of the valve nonlinearity into the model prevents the MPC from requesting physically unrealistic control actions due to valve stiction. Simulation studies using a two-tank systems show that, if the deadband value is known a priori, the mixed-integer quadratic programming (MIQP) can effectively improve the closed-loop performance in the presence of valve stiction.
The paper provides a comparison between different control allocation techniques in over-actuated Autonomous Underwater Vehicles. The pseudoinverse, Linear programming (LP), quadraticprogramming (QP), mixedinteger Li...
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The paper provides a comparison between different control allocation techniques in over-actuated Autonomous Underwater Vehicles. The pseudoinverse, Linear programming (LP), quadraticprogramming (QP), mixedinteger Linear programming (MILP) and mixedintegerquadraticprogramming (MIQP) are evaluated in simulation on the V-Fides vehicle model. The MILP and MIQP techniques allow to include in their implementations a more detailed characterization of the non-linear static behaviour of the actuators. This customizability can be also exploited to improve the practical stability of the system. The metrics used for comparison include the maximum attainable forces and torques, the integral of the error allocation and the required thrusters effort. Our simulation results show that, in particular with respect to thrusters effort, MILP and MIQP are the preferred allocation methods. The computational complexity associated to both methods is not such to compromise their implementation in operating vehicles;in particular, the MILP version is currently implemented in the V-Fides vehicle. (C) 2016, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
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