Publications

Excessive deceleration forces experienced during high speed deployment of parachute systems can cause damage to the payload and the canopy fabric. Conventional reefing lines offer limited relief by temporarily restricting canopy inflation and limiting the peak deceleration load. However, the open-loop control provided by existing reefing devices restrict their use to a specific set of deployment conditions. In this paper, the sensing, processing, and actuation that are characteristic of adaptive structures form the basis of three concepts for active control of parachute inflation. These active control concepts are incorporated into a computer simulation of parachute inflation. Initial investigations indicate that these concepts promise enhanced performance as compared to conventional techniques for a nominal release. Furthermore, the ability of each controller to adapt to off-nominal release conditions is examined.

This paper focuses on the development of an approximate time-optimal feedback strategy for conducting rest-to-rest maneuvers of a magnetically levitated table. Classical switching curves are modified to account for the complexities of magnetic actuation as well as the coupling of the rigid body modes through the control. A smooth blend of time-optimal and proportional-derivative controls is realized near the destination point to correct for inaccuracies produced by the approximate time-optimal strategy. Detailed computer simulations of the system indicate that this hybrid control strategy provides a significant reduction in settling time as compared to proportional-derivative control alone.

This paper examines the role of the control objective and the control time in determining fuel-optimal actuator placement for structural vibration suppression. A general theory is developed that can be easily extended to include alternative performance metrics such as energy and time-optimal control. The performance metric defines a convex admissible control set which leads to a max-min optimization problem expressing optimal location as a function of initial conditions and control time. A solution procedure based on a nested Genetic Algorithm is presented and applied to an example problem. Results indicate that the optimal locations vary widely as a function of control time and initial conditions.