Brown, Terry | Search NASA

NASA NTRS2001

Use of Soft Computing Technologies for a Qualitative and Reliable Engine Control System for Propulsion Systems

The problem to be addressed in this paper is to explore how the use of Soft Computing Technologies (SCT) could be employed to improve overall vehicle system safety, reliability, and rocket engine performance by development of a qualitative and reliable engine control system (QRECS). Specifically, this will be addressed by enhancing rocket engine control using SCT, innovative data mining tools, and sound software engineering practices used in Marshall's Flight Software Group (FSG). The principle goals for addressing the issue of quality are to improve software management, software development time, software maintenance, processor execution, fault tolerance and mitigation, and nonlinear control in power level transitions. The intent is not to discuss any shortcomings of existing engine control methodologies, but to provide alternative design choices for control, implementation, performance, and sustaining engineering, all relative to addressing the issue of reliability. The approaches outlined in this paper will require knowledge in the fields of rocket engine propulsion (system level), software engineering for embedded flight software systems, and soft computing technologies (i.e., neural networks, fuzzy logic, data mining, and Bayesian belief networks); some of which are briefed in this paper. For this effort, the targeted demonstration rocket engine testbed is the MC-1 engine (formerly FASTRAC) which is simulated with hardware and software in the Marshall Avionics & Software Testbed (MAST) laboratory that currently resides at NASA's Marshall Space Flight Center, building 4476, and is managed by the Avionics Department. A brief plan of action for design, development, implementation, and testing a Phase One effort for QRECS is given, along with expected results. Phase One will focus on development of a Smart Start Engine Module and a Mainstage Engine Module for proper engine start and mainstage engine operations. The overall intent is to demonstrate that by employing soft computing technologies, the quality and reliability of the overall scheme to engine controller development is further improved and vehicle safety is further insured. The final product that this paper proposes is an approach to development of an alternative low cost engine controller that would be capable of performing in unique vision spacecraft vehicles requiring low cost advanced avionics architectures for autonomous operations from engine pre-start to engine shutdown.

Trevino, Luis↗

NASA NTRS1998

A Table-Driven Control Method to Meet Continuous, Near-Real-Time Observation Requirements for the Solar X-Ray Imager

The design of the Solar X-Ray Imager (SXI) for the Geostationary Operational Environmental Satellite (GOES) presents an unusual scenario for controlling the observing sequences. The SXI is an operational instrument, designed not primarily for scientific research, but for providing "operational" data used by the National Oceanic and Atmospheric Administration (NOAA) to forecast the near-term space weather. To this end, a sequence of images selected to cover the full dynamic range of the sun will be executed routinely. As the dynamics of the sun have differing temporal cadences, the frequency of various images will differ. These images must be routinely received at the forecast center in near real-time, 24-hours a day, with a minimum of interruptions. While these requirements clearly lead to a 'routine patrol' of images, the parameters for each do not form a static set. The dynamics of the sun will change with the I 1-year solar cycle. The performance of the imaging will vary with on-orbit conditions and time. And while the SXI is not intended as a research instrument, forecasting techniques may change with time, which in turn will further alter the imaging sequences. An additional complication is the highly restricted commanding window, and a very slow commanding rate. To fulfill these requirements, the SXI was designed to utilize a table-driven approach. Sequences are defined using structured loops, with nested repetitions and delays. These sequences reference combinations of imaging parameters which in turn reference tables of parameters than can be loaded by ground commands. Multiple sequences can be built and stored in preparation for execution when determined appropriate by the NOAA forecasters. The result is an approach that can be used to provide a flexible, yet autonomous SXI capable of meeting both arbitrary forecasting requirements, and operating within the commanding constraints.

Wallace, Shawn↗