Engineering topics
Publications and source records attributed to Adami, Tony.
A group of encounter sets is evaluated as a standard for defining and refining both performance-based and functional-based terminal area MOPS requirements. DAIDALUS-alerting is used together with a variety of sensor configurations: (1) ADS-B level surveillance, (2) TCAS II, (3) ground-based RADAR with three different sets of error parameters.
Detect-and-Avoid (DAA) systems are essential to the safe operations of Unmanned Aircraft Systems, and have the objectives of mitigating collisions with and remaining Well Clear of manned aircraft. This paper analyzes four candidate DAA Well Clear definitions for non-cooperative aircraft using mitigated performance metrics of DAA systems. These DAA Well Clear definitions were proposed in previous work based on their unmitigated collision risk and maneuver initiation range. In this work they are evaluated using safety and operational suitability metrics computed from a large number of representative encounters. Results suggest that although the four candidate DAA Well Clear definitions provide comparable safety, the alerting characteristics give preference for the DAA Well Clear definition without a temporal parameter.
Detect-and-Avoid (DAA) systems are essential to the safe operations of Unmanned Aircraft Systems, and have the objectives of mitigating collisions with and remaining Well Clear of manned aircraft. This paper analyzes four candidate DAA Well Clear definitions for non-cooperative aircraft using mitigated performance metrics of DAA systems. These DAA Well Clear definitions were proposed in previous work based on their unmitigated collision risk and maneuver initiation range. In this work they are evaluated using safety and operational suitability metrics computed from a large number of representative encounters. Results suggest that although the four candidate DAA Well Clear definitions provide comparable safety, the alerting characteristics give preference for the DAA Well Clear definition without a temporal parameter.
Recently, a robust and practical adaptive control scheme for launch vehicles [ [1] has been introduced. It augments a classical controller with a real-time loop-gain adaptation, and it is therefore called Adaptive Augmentation Control (AAC). The loop-gain will be increased from the nominal design when the tracking error between the (filtered) output and the (filtered) command trajectory is large; whereas it will be decreased when excitation of flex or sloshing modes are detected. There is a need to determine the range and rate of the loop-gain adaptation in order to retain (exponential) stability, which is critical in vehicle operation, and to develop some theoretically based heuristic tuning methods for the adaptive law gain parameters. The classical launch vehicle flight controller design technics are based on gain-scheduling, whereby the launch vehicle dynamics model is linearized at selected operating points along the nominal tracking command trajectory, and Linear Time-Invariant (LTI) controller design techniques are employed to ensure asymptotic stability of the tracking error dynamics, typically by meeting some prescribed Gain Margin (GM) and Phase Margin (PM) specifications. The controller gains at the design points are then scheduled, tuned and sometimes interpolated to achieve good performance and stability robustness under external disturbances (e.g. winds) and structural perturbations (e.g. vehicle modeling errors). While the GM does give a bound for loop-gain variation without losing stability, it is for constant dispersions of the loop-gain because the GM is based on frequency-domain analysis, which is applicable only for LTI systems. The real-time adaptive loop-gain variation of the AAC effectively renders the closed-loop system a time-varying system, for which it is well-known that the LTI system stability criterion is neither necessary nor sufficient when applying to a Linear Time-Varying (LTV) system in a frozen-time fashion. Therefore, a generalized stability metric for time-varying loop=gain perturbations is needed for the AAC.