Vehicle Systems & Control Laboratory

Research

Our research is focused on bridging the scientific gaps between traditional computer science topics and aerospace engineering topics, while achieving a high degree of closure between theory and experiment.  We focus on machine learning and multi-agent systems, intelligent autonomous control, nonlinear control theory, vision based navigation systems, fault tolerant adaptive control, and cockpit systems and displays.  What sets our work apart is a unique systems approach and an ability to seamlessly integrate different disciplines such as dynamics & control, artificial intelligence, and bio-inspiration.  Our body of work integrates these disciplines, creating a lasting impact on technical communities from smart materials to General Aviation flight safety to Unmanned Air Systems (UAS) to guidance, navigation & control theory.  Our research has been funded by AFOSR, ARO, ONR, AFRL, ARL, AFC, NSF, NASA, FAA, and industry.

Autonomous and Nonlinear Control of Cyber-Physical Air, Space and Ground Systems

Vision Based Sensors and Navigation Systems

Cybersecurity for Air and Space Vehicles

Air Vehicle Control and Management

Space Vehicle Control and Management

Advanced Cockpit/UAS Systems and Displays

Control of Bio-Nano Materials and Structures

Small VTOL Unmanned Air System Controller Design and Evaluation for Variable Wind Conditions, Phase I

Bell

1 October 2018 – 30 September 2019

Total award $154,759

Due to their design, rotorcraft are inherently sensitive to gust and turbulence in hover and transition.  With their relatively low disk loading, they are sensitive to gusts when compared with aircraft; that disk loading is the major design parameter affecting turbulence.  As the disk loading increases with forward flight, the sensitivity to turbulence dries.  Along with disk loading, Center of Gravity (CG) also plays a major role in gust tolerance.  Most rotorcraft have a low CG which acts as a pendulum and has the effect of creating added stability.  However, modern VTOL designs tend to have a very high CG location which makes them highly sensitive to gusts and turbulence.

The technical objectives of this work are to:

  1. Investigate and develop a control law and associated control system to that allows a VTOL vehicle to sense and correct for gust and turbulence induced instabilities
  2. Design and build a sub-scale demonstrator.
  3. Testing the sub-scale demonstrator under full control in the Oran W. Nicks Low Speed Wind Tunnel, and in the outdoor environment  of the Vehicle System & Control Laboratory’s UAS test site at the TAMU RELLIS Campus.

The basic control law will be a disturbance rejection enhanced version of the Proportional Integral Filter – Control Rate Weighting – Nonzero Setpoint (PIF-CRW-NZSP) control law structure.  The PIF-CRW-NZSP controller is a multi-input multi-output (MIMO) optimal control methodology that permits low-pass filtering (smoothing) of feedback signals.  It also permits the rate of servo actuation to be adjusted by the designer.  This is effective in preventing actuators from hitting and riding their rate limits, which often produces poor performance and can lead to pilot induced oscillations (PIO).  Control allocation will be used as needed to distribute the modulation of the gimballed rotors for the disturbance rejection capability.

Working with me on this project are:

Graduate Students:

   -Zeke Bowden, MENG AERO

Undergraduate Students:

    -Blake Krpec, AERO

    -Christopher Leshikar, AERO

Multi-Sensor Flight Test

VectorNav Technologies

15 May 2018 – 31 October 2018

Total award $11,748

Working with me on this project are:

Graduate Students:

    -Zeke Bowden, MENG  AERO

    -Garrett Jares, Ph.D. AERO

 

Intelligent and Safe Technologies for Enhanced UAS Autonomous Air Refueling Operations, Phase I

Air Force Research Laboratory through sub-contract with Barron Associates

1 September 2017 – 30 April 2018

Total award $49,982

Unmanned Aircraft System (UAS) platforms provide many important military roles that require long periods of time aloft.  Repeated returns to base for refueling is one scenario that can severely degrade mission operations.  There is a critical need to develop autonomous aerial refueling (AAR) capabilities in which both the tanker and receiver aircraft are unmanned.  One of the challenges in AAR is minimum airspeed. For this effort the focus will be Groups 4 and 5 UASs with maximum airspeeds of 130 KCAS. The main objective is to radically increase mission length and on-station availability of UAS platforms by developing the capability to reliably conduct (AAR) of Groups 4 and 5 UASs with calibrated airspeeds of 130 KCAS or less.

Additional key technical challenges associated with AAR of UAS are:

  1. The refueling procedure will require the UAS to operate in close proximity of the tanker aircraft. Relative location must be known with a high level of accuracy, employing collision avoidance procedures.
  2. One or both the tanker and UAS must respond quickly if an unsafe refueling condition occurs.
  3. AAR solutions should minimize modifications to both the tanker and the UAS due to cost, maintenance and SWaP considerations.
  4. The refueling system must operate under broad weather and day and night conditions.

Working with me on this project are:

Graduate Students:

    -Zeke Bowden, MENG  AERO

Human Performance Impacts of Head-Worn Displays For General Aviation, Phase I

Federal Aviation Administration, Civil Aerospace Medical Institute (CAMI)

1 August 2017 – 31 July 2018

Total award $227, 025

Many systems on the market or in the conceptual design phase for Enhanced Flight Vision Systems (EFVS) provide the capability of enhancing the visual capability of the pilot during flight, at near to eye distances similar to spectacles.  Although Head Worn Displays (HWDs) have been proposed for Civil Aviation (CA) flight operations by various organizations, rigorous qualitative and quantitative comparison of candidate devices and their impact on Human Factors is currently lacking.  The technical objective of the proposed effort is to develop a means for evaluating the human factors aspects of emerging Head Worn Displays (HMD) for Enhanced Vision System technologies, and then conduct a Human Factors study of their suitability for Civil Aviation (CA) with specific application to General Aviation.

The goal of this project is to collect data and information to be used in a Human Factors study that will quantify answers to the following questions:

  1. What are the CA operational impacts of a Head Worn Display?
  2. What CA pilot approach and landing tasks can be done, and what tasks cannot be done?
  3. Is it operationally suitable for CA pilot approach and landing tasks?
  4. Does use of this system allow CA pilots to adequately conduct Cat 2 approaches?

The expected results of this research will be increased understanding of the effects of enhanced vision systems on CA pilot safety and performance in Low Visibility Operations due to weather in the approach and landing phase for Cat 1, S.A. Cat 1, Cat 2, and Cat 3.

Working with me on this project are:

Co-PI

-Dr. Thomas Ferris, ISED

Graduate Students

-Emily Fojtik, MENG AERO

Undergraduate Students:

    -Allison Daveid, BSAE

    -Alexandra Heinimann, BSAE

    -Mia Brown, CSCE

 

State Constrained Adaptive Flight Control, Phase II

Air Force Research Laboratory, Air Vehicles Directorate

Principal Investigator and Technical Lead

3 February 2017 – 3 May 2018

Total award $85,389

The development of control architectures for hypersonic vehicles presents a significant challenge due to widely varying flight conditions in which these vehicles operate and certain aspects unique to hypersonic flight. One particular safety and operational concern in hypersonic flight is inlet unstart, which not only produce a significant decrease in the thrust but also can lead to loss of control and possibly the loss of the vehicle. One potential flight condition that can cause an inlet unstart is flying at a large angle-of-attack or sideslip angle. In Phase I, a nonlinear dynamic inversion (NDI) adaptive controller was developed with the ability to enforce state constraints in order to restrict the vehicle from approaching these large aerodynamic angles. In addition, due to the challenges associated with equipping hypersonic vehicles with traditional external sensor equipment, an observer-based feedback controller for the longitudinal axis of a generic hypersonic vehicle was developed. 

Phase II will investigate a single control framework that consists of an observer-based feedback controller capable of achieving tracking for a full 6 degree-of-freedom hypersonic vehicle model, and an NDI adaptive controller capable of enforcing state constraints without full-state measurements. Additionally, a sampled-data NDI control framework is being developed to not only achieve tracking but also include enforcing state constraints as well. The effect of slower sampling times on the ability to control the aircraft and enforce state constraints will be investigated.

TECHNICAL OBJECTIVES

  1. Develop theory for an observer based feedback controller capable of tracking commands that account for the full coupling dynamics, i.e. along both the longitudinal and lateral/directional axes of the aircraft.
  2. Develop theory for enforcing state constraints in the observer-feedback adaptive dynamic inversion architecture.
  3. Develop, implement and analyze a sampled-data control framework based on the continuous time controller previously developed.

Working with me on this program are Research Assistants:

  • Douglas Famularo, Ph.D student
  • Sean Whitney, B.S. student

 

Utilization of Unmanned Aerial Systems (UAS) for Crop Production and Weed Management Applications

Texas A&M; AgriLife Research and Cropping Systems Program
Co-Principal Investigator
1 September 2015 – 31 August 2017
Total award $240,000

The overall goal of this project is to generate preliminary data necessary for effective utilization of UAS-based imaging techniques for crop production and weed management applications. UAS can be equipped to include multi-spectral sensors (3 to 4 bands in the visible and near-infrared/NIR range), hyperspectral sensors (Headwall’s Standard Micro-Hyperspec VNIR 380-1000 nm spectral range), thermal sensors and LIDAR (Light Detection And Ranging), among others. These sensors have a multitude of applications, in areas such as soil, crop, water and weed management in agriculture. However, interpretation of data collected using UAS-based remotely sensed images requires careful consideration of several factors. What is not known is the error estimates between UAS and ground-level data. Such knowledge is key to validate the utility of UAS-based data collection for various applications in agriculture. One of the major limitations so far is the labor-intensive ground data collection and biomass sampling, which will be addressed in this research. We believe that layering UAS data with field measurements would provide rigorous validation of UAS data and provide required knowledge base for widespread implementation of UAS-based data collection. The team will use the state-of-the-art manned/ unmanned ground platform (UGP) in collecting required ground-truthing information.

TECHNICAL OBJECTIVES

  1. Quantification of the growth and development of field crops as affected by soil, irrigation and crop management strategies
  2. Identification and differentiation of weed/plant species, patterns of infestation, and herbicide injury on crops

Working with me on this program are Research Assistants:

  • James Henrickson, Ph.D student
  • Cameron Rogers, Ph.D student
  • Zeke Bowden, B.S. student