Variable Fidelity Modeling as Applied to Trajectory Optimization for a Hydraulic Backhoe

Abstract

Modeling, simulation, and optimization play vital roles throughout the engineering design process; however, in many design disciplines the cost of simulation is high, and designers are faced with a tradeoff between the number of alternatives that can be evaluated and the accuracy with which they are evaluated. In this paper, a methodology is presented for using models of various levels of fidelity during the optimization process. The intent is to use inexpensive, low-fidelity models with limited accuracy to recognize poor design alternatives and reserve the high-fidelity, accurate, but also expensive models only to characterize the best alternatives. Specifically, by setting a user-defined performance threshold, the optimizer can explore the design space using a low-fidelity model by default, and switch to a higher fidelity model only if the performance threshold is attained. In this manner, the high fidelity model is used only to discern the best solution from the set of good solutions, so computational resources are conserved until the optimizer is close to the solution. This makes the optimization process more efficient without sacrificing the quality of the solution. The method is illustrated by optimizing the trajectory of a hydraulic backhoe. To characterize the robustness and efficiency of the method, a design space exploration is performed using both the low and high fidelity models, and the optimization problem is solved multiple times using the variable fidelity framework.

Value-Based Global Optimization

“…Clearly, two models are superior to one, but what is more desirable is if any and all available models could be leveraged to aid in the design space exploration and optimization. In addition to this weakness, past approaches to variable accuracy modeling and optimization generally do not explicitly account for the cost of the analyses used during the optimization process [2,4,15,38,44,52,53,68].…”

“…While there are many approaches to managing multi-accuracy data during optimization, many of the previously delineated approaches have some shortcomings. Several approaches to multiple accuracy modeling are limited to only two analysis models, and moreover, do not explicitly account for the cost of the analyses used during the process[2,4,15,38,44,52,53,68]. Therefore, what is needed is a method to combine predictions from any number of models of different accuracies so that all of the relevant information can be used and weighted…”

Reducing whole-body vibration exposure in backhoe loaders by education of operators

“…This track has been the objective of optimization in several studies. Among these [28] has tried to optimize the tool point track for the backhoe to save energy. The way of trenching is also of great importance.…”

Selection of Excavating Equipment for the Outpacing Development of the Coal-bearing Zone

“…Requirements to the elements of excavation and loading complexes: the ability to work in the same climatic conditions; comparability of performance of separate elements of the complex; mobility of elements of the complex; possibility to work out the coal-and-rock massif at one method of preparation of rocks for excavation; use of mainly the same type of energy; possibility of spatial manipulation of the working body of the machines of the complex [1][2][3][4][5][6][7][8][9][10][11][12].…”