Design optimization of the box section of the single-girder bridge crane by generalized reduced gradient algorithm

[abstFig src='/00280003/17.jpg' width=""300"" text='Stewart Gough robot and the equivalent substitutional configuration' ] This paper proposes a new method of solving the kinematic problems for parallel robots. The paper content aims to solve nonlinear optimization problems with constraints rather than to directly solve high-order nonlinear systems of equations. The nonlinear optimization problems shall be efficiently solved by applying the Generalized Reduced Gradient algorithm and appropriate downgrade techniques. This new method can be able to find exact kinematic solutions by assigning constraints onto the parameters. The procedure can be done without filtering control results from mathematical solution, from which the control time of manipulators can be reduced. The numerical simulation results in this paper shall prove that the method can be applied to solve kinematic problems for a variety of parallel robots regardless of its structures and degree of freedom (DOF). There are several advantages of the proposed method including its simplicity leading to a shorter computing time as well as achieving high accuracy, high reliability, and quick convergence in final results. Hence, the applicability of this method in solving kinematic problems for parallel manipulators is remarkably high.

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A Generalized Reduced Gradient Algorithm for Solving Large-Scale Discrete-Time Nonlinear Optimal Control Problems

IFAC Proceedings Volumes ◽

10.1016/b978-0-08-037869-5.50011-x ◽

1989 ◽

Vol 22 (2) ◽

pp. 45-50 ◽

Cited By ~ 1

Author(s):

J.L.D. Facó

Keyword(s):

Optimal Control ◽

Discrete Time ◽

Large Scale ◽

Optimal Control Problems ◽

Nonlinear Optimal Control ◽

Gradient Algorithm ◽

Control Problems ◽

Reduced Gradient ◽

Generalized Reduced Gradient ◽

Reduced Gradient Algorithm

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Optimal Design of Semisubmersible’s Form Based on Systems Analysis

Journal of Mechanisms Transmissions and Automation in Design ◽

10.1115/1.3258605 ◽

1984 ◽

Vol 106 (4) ◽

pp. 524-530 ◽

Cited By ~ 6

Author(s):

S. Akagi ◽

R. Yokoyama ◽

K. Ito

Keyword(s):

Optimal Design ◽

Computer Aided Design ◽

Optimization Problem ◽

Design Method ◽

Gradient Algorithm ◽

Interpretive Structural Modeling ◽

Reduced Gradient ◽

Optimal Design Method ◽

Generalized Reduced Gradient ◽

Aided Design

With the objective of developing a computer-aided design method to seek the optimal semisubmersible’s form, hierarchical relationships among many design objectives and conditions are investigated first based on the interpretive structural modeling method. Then, an optimal design method is formulated as a nonlinear multiobjective optimization problem by adopting three mutually conflicting design objectives. A set of Pareto optimal solutions is derived numerically by adopting the generalized reduced gradient algorithm, and it is ascertained that the designer can determine the optimal form more rationally by investigating the trade-off relationships among design objectives.

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A model for fi nding the optimal routes for a combined route container train

Innotrans ◽

10.20291/2311-164x-2021-3-15-21 ◽

2021 ◽

pp. 15-21

Author(s):

Chang Hao ◽

◽

Daria Ivanovna Kochneva ◽

Keyword(s):

Software Implementation ◽

Gradient Algorithm ◽

Rolling Stock ◽

Optimal Route ◽

Delivery Time ◽

Container Transportation ◽

Cargo Handling ◽

Reduced Gradient ◽

Generalized Reduced Gradient ◽

Train Loading

The article is devoted to the development of the model for finding an optimal route for a combined route container train (CRCT), i.e. a train with a designated route and schedule, en route from the initial to the final station without reforming of a rolling stock, but carrying out cargo handling operations for loading/unloading containers at intermediate stops of the route. It is proposed to call the optimal route of a CRCT, which provides the minimum delivery time while ensuring the targeted train loading on each section and with a set value of demand for container transportation at each point of the route. A software implementation of the model in the MS Excel environment is proposed using the built-in generalized reduced gradient algorithm.

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