Sperling, R. | Search NASA

NASA NTRS1994

Automated maneuver planning using a fuzzy logic algorithm

Spacecraft orbital control requires intensive interaction between the analyst and the system used to model the spacecraft trajectory. For orbits with right mission constraints and a large number of maneuvers, this interaction is difficult or expensive to accomplish in a timely manner. Some automation of maneuver planning can reduce these difficulties for maneuver-intensive missions. One approach to this automation is to use fuzzy logic in the control mechanism. Such a prototype system currently under development is discussed. The Tropical Rainfall Measurement Mission (TRMM) is one of several missions that could benefit from automated maneuver planning. TRMM is scheduled for launch in August 1997. The spacecraft is to be maintained in a 350-km circular orbit throughout the 3-year lifetime of the mission, with very small variations in this orbit allowed. Since solar maximum will occur as early as 1999, the solar activity during the TRMM mission will be increasing. The increasing solar activity will result in orbital maneuvers being performed as often as every other day. The results of automated maneuver planning for the TRMM mission will be presented to demonstrate the prototype of the fuzzy logic tool.

Conway, D.↗

NASA NTRS1993

Solar flux forecasting using mutual information with an optimal delay

Solar flux F(sub 10.7) directly affects the atmospheric density, thereby changing the lifetime and prediction of satellite orbits. For this reason, accurate forecasting of F(sub 10.7) is crucial for orbit determination of spacecraft. Our attempts to model and forecast F(sub 10.7) uncovered highly entangled dynamics. We concluded that the general lack of predictability in solar activity arises from its nonlinear nature. Nonlinear dynamics allow us to predict F(sub 10.7) more accurately than is possible using stochastic methods for time scales shorter than a characteristic horizon, and with about the same accuracy as using stochastic techniques when the forecasted data exceed this horizon. The forecast horizon is a function of two dynamical invariants: the attractor dimension and the Lyapunov exponent. In recent years, estimation of the attractor dimension reconstructed from a time series has become an important tool in data analysis. In calculating the invariants of the system, the first necessary step is the reconstruction of the attractor for the system from the time-delayed values of the time series. The choice of the time delay is critical for this reconstruction. For an infinite amount of noise-free data, the time delay can, in principle, be chosen almost arbitrarily. However, the quality of the phase portraits produced using the time-delay technique is determined by the value chosen for the delay time. Fraser and Swinney have shown that a good choice for this time delay is the one suggested by Shaw, which uses the first local minimum of the mutual information rather than the autocorrelation function to determine the time delay. This paper presents a refinement of this criterion and applies the refined technique to solar flux data to produce a forecast of the solar activity.

Ashrafi, S.↗