Coordinated control of unmanned aerial vehicle (UAV)

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Coordinated control of unmanned aerial vehicle
(UAV)

• Presented by Urmila Prakash
• Graduate Student
• Electrical and Computer
  Engineering
• Utah State University

2
References

• An Intelligent Approach to Coordinated Control of
  Multiple Unmanned Aerial Vehicles-George
  Vachtsevanos, Liang Tang, Johan Reimann, School
  of Electrical and Computer Engineering, Georgia
  Institute of Technology, Atlanta, GA, 30332.
  U.S.A.
• Coordinated control of unmanned aerial vehicle -
  Peter Joseph Seiler, Doctor of Philosophy
• In Engineering-Mechanical Engineering in
  the GRADUATE DIVISION of the UNIVERSITY OF
  CALIFORNIA, BERKELEY, Fall 2001
• Intelligent flying robots and wireless sensor
  networks in dynamic environment- H Jin Kim, EECS
  department, University of California, Berkeley,
  UKC 2004

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Overview

• Introduction to coordinated control
• Architecture for coordinated control
• Formation flight control problem

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Introduction

• Received significant attention in the controls
  community due to its numerous applications
• Applications
• Space science mission
• Surveillance
• Terrain Mapping
• Formation flight
• In these applications, unmanned vehicles are used
  because they can outperform human pilots, they
  remove humans from dangerous situations, or
  because they perform repetitive tasks that can be
  automated

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Why Coordinated Control ?

• The future urban warfare will utilize an
  unprecedented level of automation in which
  human-operated, autonomous, and semi -autonomous
  air and ground platforms will be linked through a
  coordinated control system.
• Networked UAVs bring a new dimension to future
  combat systems that must include adaptable
  operational procedures, planning and
  deconfliction of assets coupled with the
  technology to realize such concepts.
• The technical challenges the control designer is
  facing for autonomous collaborative operations
  stem from real-time sensing, computing and
  communications requirements, environmental and
  operational uncertainty, hostile threats and the
  emerging need for improved UAV and UAV team
  autonomy and reliability

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Formation Flight

• The problem of finding a control algorithm, which
  will ensure that multiple autonomous vehicles can
  maintain a formation while traversing a desired
  path and avoid intervehicle collisions, will be
  referred to as the formation control problem. The
  formation control problem has recently received
  considerable attention due in part to its wide
  range of applications in aerospace and robotics.
• Moreover, formation flight itself has many
  applications.
• For example, flying in formation can reduce fuel
  consumption by 30. However, this requires tight
  tracking to realize these fuel savings.
• For airborne refueling and quick deployment of
  troops and vehicles
• Cooperating vehicles may also perform tasks
  typically done by large, independent platforms.
  Gains in flexibility and reliability are
  envisioned by replacing large platforms with
  smaller vehicles operating in a formation.

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Architecture

• A novel architecture for the coordinated control
  of multiple UAVs acting as intelligent agents
• A commander is placed at the highest level of
  the hierarchy. At the current level of autonomy,
  the system under development is acting as a
  decision support tool for the commander.
• The architecture is generic and flexible to
  facilitate the fusion of diverse technologies.

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A Generic Hierarchical Multi-agent System
ArchitectureSource An Intelligent Approach to
Coordinated Control of Multiple Unmanned Aerial
Vehicles- George Vachtsevanos, Liang Tang, Johan
Reimann,School of Electrical and Computer
Engineering,Georgia Institute of Technology,
Atlanta, GA, 30332. U.S.A
9

• While networked and autonomous UAVs can be
  centrally controlled, this requires that each UAV
  communicates all the data from its sensors to a
  central location and receives all the control
  signals back. Network failures and communication
  delays are one of the main concerns in the design
  of cooperative control systems.
• On the other hand, distributed intelligent agent
  systems provide an environment in which agents
  autonomously coordinate, cooperate, negotiate,
  make decisions and take actions to meet the
  objectives of a particular application or
  mission.
• The autonomous nature of agents allows for
  efficient communication and processing among
  distributed resources.
• For the purpose of coordinated control of
  multiple UAVs, each individual UAV in the team is
  considered as an agent with particular
  capabilities engaged in executing a portion of
  the mission.
• The primary task of a typical team of UAVs is to
  execute faithfully and reliably a critical
  mission while satisfying local survivability
  conditions.

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• Consider two possible distributed control
  architectures
• each vehicle could use a control law that
  depends on measurements from all vehicles in the
  formation. This architecture allows us to design
  centralized controllers but requires the vehicles
  to communicate large amounts of information.
• distributed control architecture where each
  vehicle uses only sensor information about
  neighboring vehicles. This architecture does not
  require communication, but it may lead to
  disturbance propagation. Specially, disturbances
  acting on one vehicle will propagate and, if
  amplified, may have a large effect on another
  vehicle. This amplification of disturbances is
  commonly called string instability.

Source Coordinated control of unmanned aerial
vehicle - Peter Joseph Seiler, Doctor of
Philosophy In Engineering-Mechanical
Engineering in the GRADUATE DIVISION of the
UNIVERSITY OF CALIFORNIA, BERKELEY, Fall 2001
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Formation Control Problem

• The formation control problem is viewed as a
  Pursuit Game of n pursuers and n evaders.
  Stability of the formation of vehicles is
  guaranteed if the vehicles can reach their
  destinations within a specified time, assuming
  that the destination points are avoiding the
  vehicles in an optimal fashion.
• Vehicle model is simplified to point mass with
  acceleration limit. Collision avoidance is
  achieved by designing the value function so that
  it ensures that the two vehicles move away from
  one another when they come too close to each one.

Source An Intelligent Approach to Coordinated
Control of Multiple Unmanned Aerial Vehicles-
George Vachtsevanos, Liang Tang, Johan
Reimann,School of Electrical and Computer
Engineering,Georgia Institute of Technology,
Atlanta, GA, 30332. U.S.A
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• The most natural way to represent the information
  topology is through directed graphs.
• A directed graph consists of a set of vertices
  and a set of directed edges pointing from one
  vertex to another. The vertices represent the
  vehicles in the formation.
• The communication channels and sensing
  capabilities generate the edges of the graph. In
  general, these edges may be directed or
  bidirectional depending on the capabilities of
  the vehicle

Source Coordinated control of unmanned aerial
vehicle - Peter Joseph Seiler, Doctor of
Philosophy In Engineering-Mechanical
Engineering in the GRADUATE DIVISION of the
UNIVERSITY OF CALIFORNIA, BERKELEY, Fall 2001
13
Left Blue Angels in Delta formation Right Graph
representing a possibleinformation topology for
the Delta formationSource Coordinated control
of unmanned aerial vehicle - Peter Joseph Seiler,
Doctor of Philosophy In Engineering-Mechani
cal Engineering in the GRADUATE DIVISION of the
UNIVERSITY OF CALIFORNIA, BERKELEY, Fall 2001
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• Graphs are not only useful as a representation of
  the information topology, but also as a tool for
  control design. Give each edge of the graph a
  cost and find the optimal topology with respect
  to these costs using the Dijkstra algorithm.
• The Laplacian matrix of a graph to state a
  Nyquist-like stability criterion for a formation
  .However, if the Laplacian condition shows a
  small stability margin, it is not clear if you
  need to change the information topology (keeping
  the controller fixed), change the controller
  (keeping the information topology fixed) or some
  combination of the two.
• The use of combinatorial optimization over valid
  graphs as a tool for control synthesis.

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Wireless Sensor Network

• Whats a Sensor Network?
• Its a network of devices (nodes)
• Many nodes 1.000-100.000
• Multi-hop wireless communication with adjacent
  nodes
• Ad-hoc, i.e. dynamic and self-organizing
• Suite of sensors
• Temperature, Magnetometer,Chemical,
• A small computer (CPU memory DSP)
• Advantages
• Large-scale fine-grain monitoring of the
  environment
• Robustness
• Inexpensive and disposable
• Self-configurable
• Easily deployable
• Very small (targeting 1mm3 with Smart Dust)

Source Intelligent flying robots and wireless
sensor networks in dynamic environment- H Jin
Kim, EECS Department, University of California
Berkeley, UKC 2004
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Source Intelligent flying robots and wireless
sensor networks in dynamic environment- H Jin
Kim, EECS Department, University of California
Berkeley, UKC 2004
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Source Intelligent flying robots and wireless
sensor networks in dynamic environment- H Jin
Kim, EECS Department, University of California
Berkeley, UKC 2004
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Source Intelligent flying robots and wireless
sensor networks in dynamic environment- H Jin
Kim, EECS Department, University of California
Berkeley, UKC 2004
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Control Issues in Sensor Network

• Packet loss and random delay
• Bandwidth limitation
• Quantization error and compression
• Estimation and distributed signal reconstruction
• Distributed tracking of multiple evaders
• Coordinated control or multiple pursuers

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Conclusion

• By viewing the formation control problem as a
  differential game, important performance
  information about the formation can be
  determined, for example, the existence of
  solutions for any given set of initial
  conditions, the time to reach the target and
  whether a designated formation flight path is
  reachable.
• Moreover, the analysis of one formation of
  vehicles cannot always be translated onto another
  formation with different dynamics.

Source An Intelligent Approach to Coordinated
Control of Multiple Unmanned Aerial Vehicles-
George Vachtsevanos, Liang Tang, Johan
Reimann,School of Electrical and Computer
Engineering,Georgia Institute of Technology,
Atlanta, GA, 30332. U.S.A
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• The errors are amplified as they propagate and
  hence these strategies are sensitive to
  disturbances. This motivated a control design
  procedure for formation flight that required
  communicated leader information.
• We then determined how often this information
  must be communicated for acceptable control. The
  'how often' is determined by the sample rate of
  the system as well as the packet loss
  characteristics of the network.

Source Coordinated control of unmanned aerial
vehicle - Peter Joseph Seiler, Doctor of
Philosophy In Engineering-Mechanical
Engineering in the GRADUATE DIVISION of the
UNIVERSITY OF CALIFORNIA, BERKELEY, Fall 2001
22
Source Intelligent flying robots and wireless
sensor networks in dynamic environment- H Jin
Kim, EECS Department, University of California
Berkeley, UKC 2004
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Future work

• Investigate different distributed control
  architectures
• Explore design aspects for networked control
  systems

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Thank You