Unmanned aerial vehicle trajectory tracking algorithm comparison

Wilburn, Brenton; Perhinschi, Mario G.; Moncayo, Hever; Karas, Ondřej; Wilburn, Jennifer

doi:10.1108/ijius-05-2013-0018

Cited by 25 publications

(26 citation statements)

References 38 publications

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“…This allows the use of high gains without the adverse effect on robustness. L1 has been successfully demonstrated on drilling systems [99], wing rock compensation [100], and other flight control systems [55]. Additionally, adaptive control has been successful tested on NASA's AirSTAR test vehicle […”

Section: Adaptive Controllersmentioning

confidence: 99%

“…The inner loop is expected to generate the aerodynamic control surface deflections necessary to achieve the commanded bank and pitch angles produced by the outer loop. Two different approaches for the inner loop are involved in this study: PPID [55], and L1 adaptive feedback [87] [79] [80]. The implemented L1 adaptive controller in WVU UAV Simulation environment is different from the previous implementations in terms of the design and parameters of the L1 filter as well as additional compensation on the yaw channel.…”

Section: Inner Loop Controllermentioning

confidence: 99%

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Fault Tolerance Analysis of L1 Adaptive Control System for Unmanned Aerial Vehicles

Krishnamoorthy¹

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Trajectory tracking is a critical element for the better functionality of autonomous vehicles. The main objective of this research study was to implement and analyze L1 adaptive control laws for autonomous flight under normal and upset flight conditions. The West Virginia University (WVU) Unmanned Aerial Vehicle flight simulation environment was used for this purpose. A comparison study between the L1 adaptive controller and a baseline conventional controller, which relies on position, proportional, and integral compensation, has been performed for a reduced size jet aircraft, the WVU YF-22. Special attention was given to the performance of the proposed control laws in the presence of abnormal conditions. The abnormal conditions considered are locked actuators (stabilator, aileron, and rudder) and excessive turbulence. Several levels of abnormal condition severity have been considered. The performance of the control laws was assessed over different-shape commanded trajectories. A set of comprehensive evaluation metrics was defined and used to analyze the performance of autonomous flight control laws in terms of control activity and trajectory tracking errors. The developed L1 adaptive control laws are supported by theoretical stability guarantees. The simulation results show that L1 adaptive output feedback controller achieves better trajectory tracking with lower level of control actuation as compared to the baseline linear controller under nominal and abnormal conditions.

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Section: Adaptive Controllersmentioning

confidence: 99%

Section: Inner Loop Controllermentioning

confidence: 99%

Fault Tolerance Analysis of L1 Adaptive Control System for Unmanned Aerial Vehicles

Krishnamoorthy¹

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“…Increased level of fault tolerance can be provided by modifying the previous control algorithms [43] as presented in Figure (52). An adaptive factor equation (63) can affect the six gains of the inner loop from equations (48) through (50).…”

Section: Adaptive Control Lawsmentioning

confidence: 99%

“…End Point in Quadrant IV with ϕtotal ≤ 0. did not produce identical results; this can be recognized sufficiently by a set of performance metrics produced by two initial performance objectives, developed in[43]. One is based on the minimum error of the commanded trajectory followed by the aircraft.…”

mentioning

confidence: 99%

“…The sum of the normalized components of each of the various performance parameters was calculated to determine the performance index for each tracking algorithm. The expected performance frontiers for each of these parameters were represented by an experimentally determined threshold, which was used to normalize each parameter and assign a relative grade from 0 to 1[43].…”

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confidence: 99%

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Analysis and Comparison of Clothoid and Dubins Algorithms for UAV Trajectory Generation

Nuaimi¹

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The differences between two types of pose based UAV path generation methods clothoid and Dubins are analyzed in this thesis. The Dubins path is a combination of circular arcs and straight line segments; therefore its curvature will exhibit sudden jumps between constant values. The resulting path will have a minimum length if turns are performed at the minimum possible turn radius. The clothoid path consists of a similar combination of arcs and segments but the difference is that the clothoid arcs have a linearly variable curvature and are generated based on Fresnel integrals. Geometrically, the generation of the clothoid arc starts with a large curvature that decreases to zero. The clothoid path results are longer than the Dubins path between the same two poses and for the same minimum turn radius. These two algorithms are the focus of this research because of their geometrical simplicity, flexibility, and low computational requirements. The comparison between clothoid and Dubins algorithms relies on extensive simulation results collected using an ad-hoc developed automated data acquisition tool within the WVU UAV simulation environment. The model of a small jet engine UAV has been used for this purpose. The experimental design considers several primary factors, such as different trajectory tracking control laws, normal and abnormal flight conditions, relative configuration of poses, and wind and turbulence. A total of five different controllers have been considered, three conventional with fixed parameters and two adaptive. The abnormal flight conditions include locked or damaged actuators (stabilator, aileron, or rudder) and sensor bias affecting roll, pitch, or yaw rate gyros that are used in the feedback control loop. The relative configuration of consecutive poses is considered in terms of heading (required turn angle) and relative location of start and end points (position quadrant). Wind and turbulence effects were analyzed for different wind speed and direction and several levels of turbulence severity. The evaluation and comparison of the two path generation algorithms are performed based on generated and actual path length and tracking performance assessed in terms of tracking errors and control activity. Although continuous position and velocity are ensured, the Dubins path yields discontinuous changes in path curvature and hence in commanded lateral accelerations at the transition points between the circular arcs and straight segments. The simulation results show that this generally leads to increased trajectory tracking errors, longer actual paths, and more intense control surface activity. The gradual (linear) change in clothoid curvature yields a continuous change in commanded lateral accelerations with general positive effects on the overall UAV performance based on the metrics considered. The simulation results show general similar trends for all factors considered. As a result, it may be concluded that, due to the continuous change in commanded lateral acceleration, the clothoid path generation ...

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An Intelligent Hybrid Artificial Neural Network-Based Approach for Control of Aerial Robots

Patel

Sarabakha

Kırcalı

et al. 2019

J Intell Robot Syst

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In this work, a learning model-free control method is proposed for accurate trajectory tracking and safe landing of unmanned aerial vehicles (UAVs). A realistic scenario is considered where the UAV commutes between stations at high-speeds, experiences a single motor failure while surveying an area, and thus requires to land safely at a designated secure location. The proposed challenge is viewed solely as a control problem. A hybrid control architecture -an artificial neural network (ANN)-assisted proportional-derivative controller -is able to learn the system dynamics online and compensate for the error generated during different phases of the considered scenario: fast and agile flight, motor failure, and safe landing. Firstly, it deals with unmodelled dynamics and operational uncertainties and demonstrates superior performance compared to a conventional proportionalintegral-derivative controller during fast and agile flight. Secondly, it behaves as a fault-tolerant controller for a single motor failure case in a coaxial hexacopter thanks to its proposed sliding mode control theory-based learning architecture. Lastly, it yields reliable performance for a safe landing at a secure location in case of an emergency condition. The tuning of weights is not required as the structure of the ANN controller starts to learn online, each time it is initialised, even when the scenario changes -thus, making it completely model-free. Moreover, the simplicity of the neural network-based controller allows for the implementation on a low-cost low-power onboard computer. Overall, the real-time experiments show that the proposed controller outperforms the conventional controller.

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Unmanned aerial vehicle trajectory tracking algorithm comparison

Cited by 25 publications

References 38 publications

Fault Tolerance Analysis of L1 Adaptive Control System for Unmanned Aerial Vehicles

Fault Tolerance Analysis of L1 Adaptive Control System for Unmanned Aerial Vehicles

Analysis and Comparison of Clothoid and Dubins Algorithms for UAV Trajectory Generation

An Intelligent Hybrid Artificial Neural Network-Based Approach for Control of Aerial Robots

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