The paper discusses an optimal control problem, where both the time and the energy are to be minimized with the prescribed weights. Utilizing minimum principle the possible values of optimal control are derived in an ...
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ISBN:
(纸本)0080440746
The paper discusses an optimal control problem, where both the time and the energy are to be minimized with the prescribed weights. Utilizing minimum principle the possible values of optimal control are derived in an analytic form. To obtain the complete solution, the constrained mathematical programming problem is formulated and solved. There are finally discussed some numerical calculations to show an interesting dependence of the obtained results on a choice of weight parameters. Copyright (C) 2003 IFAC.
The paper presents the Mixed-Integer Non-linear programming optimization approach (MINLP) to structural synthesis. The MINLP is a combined discrete/continuous optimization technique, where discrete binary 0-1 variable...
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ISBN:
(纸本)1853129720
The paper presents the Mixed-Integer Non-linear programming optimization approach (MINLP) to structural synthesis. The MINLP is a combined discrete/continuous optimization technique, where discrete binary 0-1 variables are defined for optimization of discrete alternatives and continuous variables for optimization of parameters. The MINLP optimization to structural synthesis is performed through three steps: i.e. the generation of a mechanical superstructure, the modelling of an MINLP model formulation and the solution of the defined MINLP problem. As the discrete/continuous optimization problems are usually non-convex and highly non-linear, the Modified Outer-Approximation/Equality-Relaxation (OA/ER) algorithm is selected to be used for the optimization. The accompanied Linked Multilevel Hierarchical Strategy (LMHS) is developed to accelerate the convergence of the mentioned algorithm. Some examples are presented at the end of the paper.
This paper considers the nonlinear optimization problems arising in robust control synthesis for discrete linear systems with polytopic time-varying uncertainty. Here a linear objective function is minimized under non...
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For multi-cycle reloading optimization problem, a new solving scheme is presented. The multi-cycle problem is de-coupled into a number of relatively independent mono-cycle issues, then this non-linear programming prob...
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For multi-cycle reloading optimization problem, a new solving scheme is presented. The multi-cycle problem is de-coupled into a number of relatively independent mono-cycle issues, then this non-linear programming problem with complex constraints is solved by a advanced new algorithm, which is based on probability theory. The result on real core model shows well effect of this new multi-cycle optimization code.
A modified ant colony algorithm for solving optimization problem with continuous parameters is presented. In the method, groups of candidate values of the components are constructed, and each value in the group has it...
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A modified ant colony algorithm for solving optimization problem with continuous parameters is presented. In the method, groups of candidate values of the components are constructed, and each value in the group has its trail information. In each iteration of the ant colony algorithm, the method first chooses initial values of the components using the trail information. Then GA operations of crossover and mutation can determine the values of the components in the solution. Our experimental results on the problem of nonlinear programming show that our method has a much higher convergence speed and stability than those of simulated annealing (SA) and GA.
In this paper, we consider a nonlinear optimization problem with inequality constraints. The paper addresses the degenerate case when the active constraint gradients axe linearly dependent at the solution, and the Man...
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ISBN:
(纸本)3540401555
In this paper, we consider a nonlinear optimization problem with inequality constraints. The paper addresses the degenerate case when the active constraint gradients axe linearly dependent at the solution, and the Mangasarian-Fromovitz constraint qualification fails to hold. For this case, we present new generalized p-order necessary optimality conditions. The conditions subsume the classical conditions and give new and nontrivial conditions for the degenerate case. The presented results can be considered as a part of the p-regulaxity theory.
This paper addresses the application of an autonomous guidance concept to the ascent flight of the reusable launch vehicle Hopper, and to the reentry mission of the space plane X-38. Presently, the guidance requiremen...
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This paper addresses the application of an autonomous guidance concept to the ascent flight of the reusable launch vehicle Hopper, and to the reentry mission of the space plane X-38. Presently, the guidance requirements with respect to autonomy, accuracy and mission flexibility have been increased steadily for RLV applications. nonlinear programming based guidance strategies have been proposed that offer the potential to meet these demands. The autonomous guidance is achieved by combining onboard flight path prediction and nonlinear programming methods (NLP) for flight optimization. Such guidance strategies hold promise for reduced pre-mission analyses for trajectory planning, and for improved adaptability to non-nominal mission conditions. Its applicability, autonomy and performance will be discussed showing numerical results obtained with a flight simulation environment.
Engineering optimization problems often encounter mixed discrete design variables. Very few of the existing methods can obtain a globally optimal solution if the objective functions are non-convex and non-differentiab...
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ISBN:
(纸本)9781624101007
Engineering optimization problems often encounter mixed discrete design variables. Very few of the existing methods can obtain a globally optimal solution if the objective functions are non-convex and non-differentiable. In this research, a mixed discrete synthetic approach (MDSA), taking the advantages of random search methods and deterministic search methods, is proposed. Specifically, the modified complex algorithm is combined with the hybrid negative sub-gradient search, coupled with an implicit enumeration checking-point technique, for the solution of mixed-discrete optimization problems. The MDSA is used for the optimal designs of a pressure vessel and a welded beam. The numerical results demonstrate the high reliability and effectiveness of the MDSA as an advanced global method in solving mixed-discrete engineering optimization problems.
The aim of this work is towards a better understanding of the effect of using constraint violations in guiding evolutionary search for nonlinear programming problems. Different penalty functions, based on constraint v...
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In this paper, we propose a new method using only three vanishing points to recover the dimensions of object and its pose from a single image with a camera of unknown focal length. Our approach is to compute the dimen...
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