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Irene M. Gregory

Publications and source records attributed to Irene M. Gregory.

A Model Predictive Control Approach for In-Flight Acoustic Constraint Compliance

Vehicle noise remains one of the major barriers to public acceptance of Urban Air Mobility-class aircraft. This work focuses on motion planning for aircraft in noise-sensitive areas. A nonlinear Model Predictive Path Integral~(MPPI) control law is used to generate a finite-horizon trajectory that satisfies acoustic level constraints at a set of observer locations. The MPPI framework places no restrictions on the class of state-dependent cost functionals that can be employed, making it well-suited for use with sophisticated acoustic models and metrics, in addition to dynamic and mission-relevant constraints. The proposed control law is also suitable for implementation in a real-time application. A simulation example demonstrates the ability of the controller to modify the flight trajectory in order to satisfy acoustic constraints at multiple measurement locations.

Aircraft motion planning

A Model Predictive Control Approach for In-Flight Acoustic Constraint Compliance

Vehicle noise remains one of the major barriers to public acceptance of Urban Air Mobility class aircraft. This work focuses on motion planning for aircraft in noise-sensitive areas. A nonlinear Model Predictive Path Integral (MPPI) control law is used to generate a finite horizon trajectory that satisfies acoustic level constraints at a set of (three-dimensional) observer locations. The MPPI framework places no restrictions on the class of state-dependent cost functionals that can be employed, making it well-suited for use with sophisticated acoustic models and metrics, in addition to dynamic and mission-relevant constraints. The model predictive control architecture is also suitable for implementation in a real-time application. A simulation example demonstrates the ability of the controller to modify the flight trajectory in order to satisfy acoustic constraints at multiple measurement locations.

acoustically-aware vehicle

Trajectory Generation for Distributed Electric Propulsion Vehicles with Propeller Synchronization

In this paper, we propose a method for generating dynamically feasible trajectories for an acoustically aware vehicle with propeller phase control. The trajectory generation procedure allows both propeller phase control and navigation objectives to be considered simultaneously. The presented method is demonstrated where the mission objectives are given as a desired position and phase trajectory. From these trajectories, the full desired state of the vehicle is calculated. Furthermore, the control inputs that realize the desired mission objectives are computed. The acoustic performance for the given trajectory is estimated in terms of sound pressure level as a function of tracking performance. The method is demonstrated in simulation, where the vehicle must navigate through an urban environment with both spatial and acoustic constraints. In the presented scenario, the vehicle must follow a given flight path, and can only reduce sound pressure level by changing the propeller phase targets.

acoustically-aware vehicle

Benchmark Problem Development for Testing Maturity of Intelligent Contingency Management Tools

Increasingly autonomous Advanced Air Mobility (AAM) vehicles will be required to handle diverse conditions with limited human intervention. Intelligent contingency management (iCM) approaches are under development to address how automated agents can handle unforeseen, unplanned, and unanticipated events. Benchmark scenario is needed to test the maturity of the developed iCM tools and techniques.

Jon Holbrook

Candidate Performance Metrics for Generalized Control for Autonomous Flight

Contingency management is the most challenging aspect of autonomous flight. In order to accommodate the most flexible response to unpredicted events and unexpected circumstances, i.e. contingencies, a new integrated path planning, trajectory following, flight control architecture is required that would maximize the safe operating envelope. For this highly integrated generalized control architecture, a new set of performance metrics that extends beyond traditional stability and performance is required. This paper proposes a candidate set of new performance metrics relevant to urban air mobility mission scenarios.

Control metrics

Candidate Performance Metrics for Generalized Control for Autonomous Flight

Contingency management is the most challenging aspect of autonomous flight. In order to accommodate the most flexible response to unpredicted events and unexpected circumstances, i.e. contingencies, a new integrated path planning, trajectory following, flight control architecture is required that would maximize the safe operating envelope. For this highly integrated generalized control architecture, a new set of performance metrics that extends beyond traditional stability and performance is required. This paper proposes a candidate set of new performance metrics relevant to urban air mobility mission scenarios.

Control metrics

Comparison of Acoustic Models and Trajectory Generation Methods for an Acoustically-Aware Aircraft

Motivation - Noise management is one of the major barriers to Urban Air Mobility - Approaches to noise mitigation (non-exhaustive) - Vehicle configuration - Directivity control via propeller phase synchronization - Trajectory optimization Objective - Create framework for trajectory generation integrating location-based acoustic metrics and vehicle performance limitations - Multiple trajectory optimization methods and acoustic noise models - Mission-relevant constraints - Mission duration, airspace restrictions, ... - Vehicle dynamic constraints - Aircraft structural limitations, min/max airspeed, ... - Vehicle separation/obstacle avoidance - Acoustic constraints at a number of discrete observer locations

Kasey A. Ackerman

Challenges and Opportunities in Autonomous Flight

This talk discusses the challenges and opportunities for autonomy in aviation. We cover the autonomy drivers, what we consider fundamental building blocks for autonomous flight and success of assigned mission. We provide some examples from our work of integrating different algorithms to deal with contingencies that arise in flight. We also discuss a potential need to assess progress to autonomy across various aviation niches and evolving sectors and propose a framework to do so.

autonomy

Community Benchmark Problem for Intelligent Contingency Management

This paper introduces a Community Benchmark Problem (CBP) for Intelligent Contingency Management (ICM) for Urban Air Mobility (UAM) aircraft. The CBP aims to provide a common framework for measuring and comparing the progress of autonomy solutions for UAM aircraft in handling emergency situations. The paper proposes a methodology for defining and quantifying five measures of complexity that capture the challenges and requirements of ICM for UAM: Mission, Environmental, Autonomy, Decision-Making, and Mission Fault. In addition, it proposes a methodology for defining and quantifying mission risk acceptability with the same goals: Contingency Management, Mission Success, Operational, Mission Redefinition, and Environmental. We describe how to use these measures to track progress of the development of ICM capability, as well as to create scenarios and evaluate the performance of different autonomy solutions.

autonomy