Demonstration of CLIPS as an Intelligent Front-End for POST

Abstract

Most of the analysis codes used in the design of aerospace systems are complex, requiring some expertise to set up and execute. Usually the Program to Optimize Simulated Trajectories (POST) fails to converge when its control variables are given a bad set of initial guesses, causing the trajectory to remain in the infeasible design region throughout the computations. The user then analyzes the output produced and relies on a set of heuristics, typically gained from experience with the program, to determine the appropriate modification to the problem setup that will guide POST in finding a feasible region and eventually converge to a solution. The potential benefits of employing knowledge-based system within a design environment have long been well known. Various methods of utilization have been identified. As a postprocessing guide, an expert system can distill information obtained from an analysis code, such as POST, into knowledge. The system then can emulate the human analyst's decision-making capability based on this collected knowledge. This paper describes the implementation of POST expertise in a knowledge-based system called CLIPS and demonstrates the feasibility of utilizing this integrated system as a design tool.