Coordinated control of unmanned aerial vehicle (UAV)

1. 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

3. Overview • Introduction to coordinated control • Architecture for coordinated control • Formation flight control problem

4. 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

5. 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

6. 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.

7. 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.

8. 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.

10. 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

11. 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

12. 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-Mechanical Engineering in the GRADUATE DIVISION of the UNIVERSITY OF CALIFORNIA, BERKELEY, Fall 2001

14. 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.

15. Wireless Sensor Network Whats a Sensor Network? • It’s 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

16. Source: Intelligent flying robots and wireless sensor networks in dynamic environment- H Jin Kim, EECS Department, University of California Berkeley, UKC 2004

17. Source: Intelligent flying robots and wireless sensor networks in dynamic environment- H Jin Kim, EECS Department, University of California Berkeley, UKC 2004

18. Source: Intelligent flying robots and wireless sensor networks in dynamic environment- H Jin Kim, EECS Department, University of California Berkeley, UKC 2004

19. 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

20. 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

21. 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

23. Future work • Investigate different distributed control architectures • Explore design aspects for networked control systems

24. Thank You