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Persson, Linnea
Biography [eng]

PhD student at the department of Automatic Control, with a M.Sc in Systems Control and Robotics and a B.Sc in Engineering Physics from KTH.  My research interests include collaborative control, optimization based control, autonomous systems and aerospace applications.

Publications (4 of 4) Show all publications
Persson, L. (2019). Autonomous and Cooperative Landings Using Model Predictive Control. (Licentiate dissertation). Stockholm: KTH Royal Institute of Technology
Open this publication in new window or tab >>Autonomous and Cooperative Landings Using Model Predictive Control
2019 (English)Licentiate thesis, monograph (Other academic)
Abstract [en]

Cooperation is increasingly being applied in the control of interconnected multi-agent systems, and it introduces many benefits. In particular, cooperation can improve the efficiency of many types of missions, and adds flexibility and robustness against external disturbances or unknown obstacles. This thesis investigates cooperative maneuvers for aerial vehicles autonomously landing on moving platforms, and how to safely and robustly perform such landings on a real system subject to a variety of disturbances and physical and computational constraints. Two specific examples are considered: the landing of a fixed-wing drone on top of a moving ground carriage; and the landing of a quadcopter on a boat. The maneuvers are executed in a cooperative manner where both vehicles are allowed to take actions to reach their common objective while avoiding safety based spatial constraints. Applications of such systems can be found in, for example, autonomous deliveries, emergency landings, and search and rescue missions. Particular challenges of cooperative landing maneuvers include the heterogeneous and nonlinear dynamics, the coupled control, the sensitivity to disturbances, and the safety criticality of performing a high-velocity landing maneuver.

The thesis suggests the design of a cooperative control algorithm for performing autonomous and cooperative landings. The algorithm is based on model predictive control, an optimization-based method where at every sampling instant a finite-horizon optimal control problem is solved. The advantages of applying this control method in this setting arise from its ability to include explicit dynamic equations, constraints, and disturbances directly in the computation of the control inputs. It is shown how the resulting optimization problem of the autonomous landing controller can be decoupled into a horizontal and a vertical sub-problem, a finding which significantly increases the efficiency of the algorithm. The algorithm is derived for two different autonomous landing systems, which are subsequently implemented in realistic simulations and on a drone for real-world flight tests. The results demonstrate both that the controller is practically implementable on real systems with computational limitations, and that the suggested controller can successfully be used to perform the cooperative landing under the influence of external disturbances and under the constraint of various safety requirements.

Abstract [sv]

Samarbete tillämpas i allt högre utsträckning vid reglering av sammankopplade multiagentsystem, vilket medför både ökad robusthet och flexibilitet mot yttre störningar, samt att många typer av uppgifter kan utföras mer effektivt. Denna licentiatavhandling behandlar kooperativa och autonoma landningar av drönare på mobila landingsplatformar, och undersöker hur sådana landningar kan implementeras på ett verkligt system som påverkas av externa störningar och som samtidigt arbetar under fysiska och beräkningsmässiga begränsningar. Två exempel betraktas särskilt: först landingen av ett autonomt flygplan på en bil, därefter landning av en quadcopter på en båt. Landningarna utförs kooperativt, vilket innebär att båda fordonen har möjlighet att påverka systemet för att fullborda landningen. Denna typ av system har applikationer bland annat inom autonoma leveranser, nödlandningar, samt inom eftersöknings- och räddningsuppdrag. Forskningen motiveras av ett behov av effektiva och säkra autonoma landingsmanövrar, för fordon med heterogen och komplex dynamik som samtidigt måste uppfylla en mängd säkerhetsvillkor.

I avhandlingen härleds  kooperativa regleralgoritmer för landningsmanövern. Reglermetoden som appliceras är modell-prediktiv reglerteknik, en optimeringsbaserad metod under vilken ett optimalt reglerproblem med ändlig horisont löses  varje samplingsperiod. Denna metod tillför här fördelar såsom explicit hantering av systemdynamik, och direkt inkludering av störningshantering och bivillkor vid beräkning av insignaler. På så sätt kan vi direkt i optimeringslösaren hantera säkerhetsvillkor och externa störningar. Det visas även hur lösningstiden för optimeringen kan effektiviseras genom att separera den horisontella och den vertikala dynamiken till två subproblem som löses sekvensiellt. Algoritmen implementeras därefter för två olika landingssystem, för att därefter tillämpas och utvärderas i realistiska simuleringsmiljöer med olika typer av störningar, samt med flygtester på en verklig plattform. Resultaten visar dels att reglermetoden ger önskade resultat med avseende både på störningshantering och uppfyllande av bivillkor från säkerhetskrav, och dels att algoritmen är praktiskt implementerbar även på system med begränsad beräkningskraft.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2019. p. 123
Series
TRITA-EECS-AVL ; 2019:18
Keywords
cooperative control, autonomous landings, rendezvous, UAV, drone, USV
National Category
Control Engineering
Research subject
Electrical Engineering
Identifiers
urn:nbn:se:kth:diva-246194 (URN)978-91-7873-141-1 (ISBN)
Presentation
2019-04-12, Q2, Malvinas väg 10, Stockholm, 10:00 (English)
Opponent
Supervisors
Funder
Wallenberg AI, Autonomous Systems and Software Program (WASP)
Note

QC 20190315

Available from: 2019-03-15 Created: 2019-03-15 Last updated: 2019-03-15Bibliographically approved
Persson, L. & Wahlberg, B. (2018). Verification of Cooperative Maneuvers in FlightGear using MPC and Backwards Reachable Sets. In: 2018 European Control Conference, ECC 2018: . Paper presented at 16th European Control Conference, ECC 2018, Limassol, Cyprus, 12 June 2018 through 15 June 2018 (pp. 1411-1416). Institute of Electrical and Electronics Engineers (IEEE), Article ID 8550247.
Open this publication in new window or tab >>Verification of Cooperative Maneuvers in FlightGear using MPC and Backwards Reachable Sets
2018 (English)In: 2018 European Control Conference, ECC 2018, Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 1411-1416, article id 8550247Conference paper, Published paper (Refereed)
Abstract [en]

In this paper we develop a simulation setup for testing and analyzing cooperative maneuvers and corresponding control algorithms. We also find feasible initial sets using backwards reachable set computations for the cooperative control problem, which we then test using the simulation setup. The particular example considered is a cooperative rendezvous between a fixed-wing unmanned aerial vehicle and a unmanned ground vehicle. The open-source software FlightGear and JSBSim are used for the vehicle dynamics, enabling testing of algorithms in a realistic environment. The aircraft models include nonlinear, state-dependent dynamics, making it possible to capture complex behaviors like stall and spin. Moreover, environmental effects such as wind gusts and turbulence are directly integrated into the simulations. From the simulations we get a comprehensive understanding of the controller performance and feasibility when tested in a real-time scenario. Results from several landing simulations are presented, and demonstrate that the MPC solution for the cooperative rendezvous problem is a promising method also for use in complex, safety-critical systems.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018
National Category
Control Engineering
Identifiers
urn:nbn:se:kth:diva-241397 (URN)10.23919/ECC.2018.8550247 (DOI)2-s2.0-85059813264 (Scopus ID)9783952426982 (ISBN)
Conference
16th European Control Conference, ECC 2018, Limassol, Cyprus, 12 June 2018 through 15 June 2018
Note

QC 20190121

Available from: 2019-01-21 Created: 2019-01-21 Last updated: 2019-01-21Bibliographically approved
Muskardin, T., Balmer, G., Persson, L., Wlach, S., Laiacker, M., Ollero, A. & Kondak, K. (2017). A Novel Landing System to Increase Payload Capacity and Operational Availability of High Altitude Long Endurance UAVs. Journal of Intelligent and Robotic Systems, 88(2-4), 597-618
Open this publication in new window or tab >>A Novel Landing System to Increase Payload Capacity and Operational Availability of High Altitude Long Endurance UAVs
Show others...
2017 (English)In: Journal of Intelligent and Robotic Systems, ISSN 0921-0296, E-ISSN 1573-0409, Vol. 88, no 2-4, p. 597-618Article in journal (Refereed) Published
Abstract [en]

Unmanned stratospheric aircraft capable of staying aloft for long periods of time have become a topic of interest in the past years. Several problems are still to be solved to allow for a profitable commercial use of such aircraft. The inherent lightweight design leads to fragile structures with low payload capacities and a high wind sensitivity. The weather dependence significantly reduces the system's operational availability. To address these drawbacks a novel landing system is proposed in this paper. The landing gear can be removed from the aircraft and a ground-based mobile landing platform is introduced. The main technical challenges consist in the precise relative state estimation and cooperative control of the involved vehicles. A reliable simulation model of the overall system was developed and a number of simulation experiments performed before the actual landing was attempted with an experimental system setup. Multiple successful landing experiments demonstrate the validity of the proposed system.

Place, publisher, year, edition, pages
SPRINGER, 2017
Keywords
Aerial robotics, Cooperative control, UAV, UAS, Multi-robot systems
National Category
Embedded Systems
Identifiers
urn:nbn:se:kth:diva-217015 (URN)10.1007/s10846-017-0475-z (DOI)000412972000023 ()2-s2.0-85010755566 (Scopus ID)
Note

QC 20171101

Available from: 2017-11-01 Created: 2017-11-01 Last updated: 2017-11-01Bibliographically approved
Persson, L., Muskardin, T. & Wahlberg, B. (2017). Cooperative Rendezvous of Ground Vehicle and Aerial Vehicle using Model Predictive Control. In: 2017 IEEE 56TH ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC): . Paper presented at 56th IEEE Annual Conference on Decision and Control, CDC 2017, Melbourne Convention and Exhibition Centre (MCEC)Melbourne, Australia, 12 December 2017 through 15 December 2017 (pp. 2819-2824). IEEE
Open this publication in new window or tab >>Cooperative Rendezvous of Ground Vehicle and Aerial Vehicle using Model Predictive Control
2017 (English)In: 2017 IEEE 56TH ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC), IEEE , 2017, p. 2819-2824Conference paper, Published paper (Refereed)
Abstract [en]

This paper considers the problem of controlling a fixed-wing unmanned aerial vehicle and a cooperating unmanned ground vehicle to rendezvous by making the aerial vehicle land on top the ground vehicle. Both vehicles are actively taking part in the control effort, where they coordinate positions and velocities to complete the landing. The rendezvous time and the terminal state are kept free to increase the flexibility of the solution. There are two main challenges with this maneuver. First, the controller must force the system to stay within a safe set such that the aerial vehicle approaches the ground vehicle directly from above. Second, the rendezvous must occur within some finite distance. A model predictive control algorithm is proposed to achieve these objectives. The choice is motivated by recent experimental results showing how the landing safety and efficiency could benefit from including safety margins already in the computation of the control inputs. A controller, which steers the agents towards rendezvous and which indirectly provides safety guarantees through non-convex optimization constraints, is derived. Simulations are provided showing the ability of the controller to plan a safe trajectory online, even under the disturbance of wind gusts.

Place, publisher, year, edition, pages
IEEE, 2017
Series
IEEE Conference on Decision and Control, ISSN 0743-1546
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-223866 (URN)10.1109/CDC.2017.8264069 (DOI)000424696902117 ()2-s2.0-85046284814 (Scopus ID)978-1-5090-2873-3 (ISBN)
Conference
56th IEEE Annual Conference on Decision and Control, CDC 2017, Melbourne Convention and Exhibition Centre (MCEC)Melbourne, Australia, 12 December 2017 through 15 December 2017
Funder
Knut and Alice Wallenberg Foundation
Note

QC 20180306

Available from: 2018-03-06 Created: 2018-03-06 Last updated: 2018-11-13Bibliographically approved
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