Browsing by Author "Lee, Hae-In"

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    Approximation of achievable robustness limit based on sensitivity inversion
    (AIAA, 2023-11-07) Cho, Namhoon; Lee, Hae-In
    Introduction: The sensitivity function, defined as the closed-loop transfer function from the exogenous input to the tracking error, is central to the multi-objective design and analysis of a feedback control system. Its frequency response determines many performance characteristics of the closed-loop system, such as disturbance attenuation, reference tracking, and robustness against uncertainties and noise. It is well known that the nominal sensitivity peak, i.e., the H∞ -norm of the sensitivity function, is a direct measure of stability robustness, because the sensitivity magnitude quantifies both the attenuation of the effect of external disturbances on the closed-loop output and the variations of the closed-loop system with respect to the plant perturbations.
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    Concurrent learning adaptive control with directional forgetting
    (IEEE, 2019-04-17) Lee, Hae-In; Shin, Hyosang; Tsourdos, Antonios
    This paper proposes a new concurrent learning-based adaptive control algorithm. The main objective behind our proposition is to relax the persistent excitation requirement for the stability guarantee, while providing the ability to identify time-varying parameters. To achieve the objective, this paper designs a directional forgetting algorithm, which is then integrated with the adaptive law. The theoretical stability analysis shows that the tracking and parameter estimation error is exponentially stable with the signal only finitely excited, not persistently excited. The analysis also shows that the proposed algorithm can guarantee the stability under time-varying parameters. Moreover, the necessary and sufficient conditions for the stability given the time-varying parameters are derived. The results of numerical simulations confirm the validity of the theoretical analysis results and demonstrate the performance of the proposed algorithm.
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    Cooperative control of multi-uavs under communication constraints.
    (2018-10) Lee, Hae-In; Shin, Hyo-Sang; Tsourdos, Antonios
    This research aims to develop an analysis and control methodology for the multiple un-manned aerial vehicles (UAVs), connected over a communication network. The wireless communication network between the UAVs is vulnerable to errors and time delays, which may lead to performance degradation or even instability. Analysis on the effects of the potential communication constraints in the multiple UAV control is a critical issue for successful operation of multiple UAVs. Therefore, this thesis proposes a systematic method by incorporating three steps: proposing the analysis method and metrics considering the wireless communication dynamics, designing the structure of the cooperative controller for UAVs, and applying the analysis method to the proposed control in representative applications. For simplicity and general insights on the effect of communication topology, a net-worked system is first analysed without considering the agent or communication dynamics. The network theory specifies important characteristics such as robustness, effectiveness, and synchronisability with respect to the network topology. This research not only reveals the trade-off relationship among the network properties, but also proposes a multi-objective optimisation (MOO) method to find the optimal network topology considering these trade-offs. Extending the analysis to the networked control system with agent and communication dynamics, the effect of the network topology with respect to system dynamics and time delays should be considered. To this end, the effect of communication dynamics is then analysed in the perspective of robustness and performance of the controller. The key philosophy behind this analysis is to approximate the networked control system as a transfer function, and to apply the concepts such as stability margin and sensitivity function in the control theory. Through the analysis, it is shown that the information sharing between the agents to determine their control input deteriorates the robustness of their stability against system uncertainties. In order to compensate the robustness and cancel out the effect of uncertainties, this thesis also develops two different adaptive control methods. The proposed adaptive control methods in this research aim to cope with unmatched uncertainty and time-varying parameter uncertainty, respectively. The effect of unmatched uncertainty is reduced on the nominal performance of the controller, using the parameter-robust linear quadratic Gaussian method and adaptive term. On the other hand, time-varying parameter uncertainty is estimated without requiring the persistent excitation using concurrent learning with the directional forgetting algorithm. The stability of the tracking and parameter estimation error is proved using Lyapunov analysis. The proposed analysis method and control design are demonstrated in two application examples of a formation control problem without any physical interconnection between the agents, and an interconnected slung-load transportation system. The performance of the proposed controllers and the effect of topology and delay on the system performance are evaluated either analytically or numerically.
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    EuroDRONE, A European unmanned traffic management testbed for U-space
    (MDPI, 2022-02-18) Lappas, Vaios; Zoumponos, Giorgos; Kostopoulos, Vassilis; Lee, Hae-In; Shin, Hyosang; Tsourdos, Antonios; Tantardini, Marco; Shomko, Dennis; Munoz, Jose; Amoratis, Epameinondas; Maragkakis, Aris; Machairas, Thomas
    EuroDRONE is an Unmanned Traffic Management (UTM) demonstration project, funded by the EU’s SESAR organization, and its aim is to test and validate key UTM technologies for Europe’s ‘U-Space’ UTM program. The EuroDRONE UTM architecture comprises cloud software (DroNav) and hardware (transponder) to be installed on drones. The proposed EuroDRONE system is a Highly Automated Air Traffic Management System for small UAVs operating at low altitudes. It is a sophisticated, self-learning system based on software and hardware elements, operating in a distributed computing environment, offering multiple levels of redundancy, fail-safe algorithms for conflict prevention/resolution and assets management. EuroDRONE focuses its work on functionalities which involve the use of new communication links, the use of vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) technology to communicate information between drones and operators for safe and effective UTM functionality. Practical demonstrations that took place in Patras/Messolonghi in 2019 are presented and show the benefits and shortcomings of near-term UTM implementation in Europe.
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    Parameter-robust linear quadratic Gaussian technique for multi-agent slung load transportation
    (Elsevier, 2017-09-14) Lee, Hae-In; Yoo, Dong-Wan; Lee, Byung-Yoon; Moon, Gun-Hee; Lee, Dong-Yeon; Tahk, Min-Jea; Shin, Hyosang
    This paper copes with parameter-robust controller design for transportation system by multiple unmanned aerial vehicles. The transportation is designed in the form of string connection. Minimal state-space realization of slung-load dynamics is obtained by Newtonian approach with spherical coordinates. Linear quadratic Gaussian / loop transfer recovery (LQG/LTR) is implemented to control the position and attitude of all the vehicles and payloads. The controller's robustness against variation of payload mass is improved using parameter-robust linear quadratic Gaussian (PRLQG) method. Numerical simulations are conducted with several transportation cases. The result verifies that LQG/LTR shows fast performance while PRLQG has its strong point in robustness against system variation.
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    A probabilistic–geometric approach for UAV detection and avoidance systems
    (MDPI, 2022-11-27) Lee, Hae-In; Shin, Hyosang; Tsourdos, Antonios
    This paper proposes a collision avoidance algorithm for the detection and avoidance capabilities of Unmanned Aerial Vehicles (UAVs). The proposed algorithm aims to ensure minimum separation between UAVs and geofencing with multiple no-fly zones, considering the sensor uncertainties. The main idea is to compute the collision probability and to initiate collision avoidance manoeuvres determined by the differential geometry concept. The proposed algorithm is validated by both theoretical and numerical analysis. The results indicate that the proposed algorithm ensures minimum separation, efficiency, and scalability compared with other benchmark algorithms.
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    Project-based learning course design for multi-agent autonomy using quadrotors
    (Elsevier BV, 2024-09-05) Lee, Hae-In; Ignatyev, Dmitry; Shin, Hyo-Sang; Tsourdos, Antonios
    This paper proposes a project-based learning course utilising multiple quadrotors, aiming to solidify and amplify technical knowledge and develop critical thinking capabilities. An engineering problem is provided as a surveillance mission with multiple quadrotors autonomously searching, detecting, and tracking ground vehicles. The course covers all stages of multi-agent autonomy development, from identifying system requirements, designing software and hardware, to conducting demonstrations in a drone flying arena. During the course, students improve their ability to critically formulate, solve and evaluate engineering problems as well as gain and apply technical knowledge in all aspects of autonomy such as flight dynamics, control, navigation, guidance, task allocation, situational awareness and communication. The paper details the problem design, course timeline, outcomes, and key lessons learnt from the course.
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    Sample greedy based task allocation for multiple robot systems
    (Springer, 2022-08-13) Shin, Hyosang; Li, Teng; Lee, Hae-In; Tsourdos, Antonios
    This paper addresses in-schedule dependent task allocation problems for multi-robot systems. One of the main issues with those problems is the inherent NP-hardness of combinatorial optimisation. To handle this issue, this paper develops a decentralised task allocation algorithm by leveraging the submodularity concept and a sampling process of task sets. Our theoretical analysis reveals that the proposed algorithm can provide an approximation guarantee of 1/2 of the optimal solution for the monotone submodular case and 1/4 for the non-monotone submodular case, both with polynomial time complexity. To examine the performance of the proposed algorithm and validate the theoretical analysis, we introduce two task allocation scenarios and perform numerical simulations. The simulation results confirm that the proposed algorithm achieves a solution quality which is comparable to state-of-the-art algorithms in the monotone case and much better quality in the non-monotone case with significantly lower computational complexity.
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    UAV collision avoidance considering no-fly-zones
    (Elsevier, 2021-04-14) Lee, Hae-In; Shin, Hyosang; Tsourdos, Antonios
    This paper proposes a collision avoidance algorithm that ensures minimum separation between the vehicles considering multiple no-fly-zones. The proposed algorithm aims to provide a practical and efficient tactical de-confliction solution for Unmanned Aerial Vehicles (UAVs). The main idea is to utilise the differential geometry concept that computes the minimum heading angle change to avoid the obstacles, and to expand its applicability to polygonal obstacles. This paper validates the minimum separation and efficiency of the proposed algorithm both analytically and numerically
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    Unmanned aerial system concept design for rail yard monitoring
    (AIAA, 2023-01-19) Kirenga, Alain; Lee, Hae-In; Zolotas, Argyrios
    Safety and security monitoring in large yard areas, typical in rail yard environments, is an important task and any trespassing or vandalizing incidents can cause significant disruptions to routine activities and possibly to staff safety. This can impact normal rail network operation. This paper investigates the feasibility of using low-cost unmanned aerial systems (UAS) for monitoring rail yards. A rigorous literature survey on unmanned aerial vehicles (UAV) platforms for monitoring in various sectors is conducted. Given the large area of the rail yard, a concept of multiple rotor-based UAVs is explored with a particular eye on energy-efficiency. The proposed concept is validated hardware-wise through multiple flights conducted to monitor a scale-down setup of a "yard" concept in the lab's indoor flying arena. Analysis of the results showcases the potential of using low-cost multirotor UAV solutions for monitoring assistance in large yards.