Observer-based fixed-time continuous nonsingular terminal sliding mode control of quadrotor aircraft under uncertainties and disturbances for robust trajectory tracking: Theory and experiment

Mechali, Omar; Xu, Limei; Huang, Ya; Shi, Mengji; Xie, Xingyu

doi:10.1016/j.conengprac.2021.104806

Cited by 73 publications

(57 citation statements)

References 60 publications

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“…For the simulated and real-world experiments, PX4 [31] and DJI A3 controllers were employed, respectively. The second experiment was devoted to demonstrating the behaviour of the proposed approach in a real-world condition 3 , where the initial reference trajectory passes through a cluttered environment followed by open space and back to a cluttered environment where the terminal pose was placed in an obstacle zone. Map update range (update range) was kept 4m from the center of the MAV and max speed set to 0.6m/s for the safety of MAV.…”

Section: Experimental Procedures and Resultsmentioning

confidence: 99%

“…Such a behaviour is due the 2 tracking accuracy without considering obstacles: https://www.youtube. com/watch?v=pKVeGdr8crU 3 behaviour of the proposed approach in a challenging environment https: //youtu.be/g6xHvkcrYcQ Fig. 7.…”

Section: Experimental Procedures and Resultsmentioning

confidence: 99%

“…T He reference trajectory tracking for multi-rotor aerial vehicles (MAVs) is used in various domains, e.g., cinematography, or landing on a moving platform. Even though many approaches have been proposed for tracking specified reference trajectories [1]- [3], it remains an open research problem due to several reasons: achieving real-time performance, avoiding close-in obstacles, adhering to different weather conditions, etc. Subsequently, generating a near-optimal control policy for maneuvering through a cluttered unknown environment is a rather challenging task when enforcing the dynamic Fig.…”

Section: Introductionmentioning

confidence: 99%

“…The functions and characteristics of a local planner are: it plans for a local near-optimal trajectory based on the currently perceived information within the close vicinity with higher accuracy [3], [19]; it generates near-optimal control policy in an online fashion in every iteration; it performs trajectory smoothing and feasibility checking to ensure the differential/dynamic constraints; the trajectories are planned consecutively, depending on the way they handle the next set of information that comes in, e.g., how they react to dynamic and static obstacles and how they decide whether to incorporate previous information [1], [2]; long horizon-based trajectory planning may generate wasteful unnecessary long trajectories [4].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Optimization-based Trajectory Tracking Approach for Multi-rotor Aerial Vehicles in Unknown Environments

Kulathunga¹,

Hamed²,

Devitt³

et al. 2022

Preprint

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The goal of this paper is to develop a continuous optimization-based refinement of the reference trajectory to 'push it out' of the obstacle-occupied space in the global phase for Multi-rotor Aerial Vehicles in unknown environments. Our proposed approach comprises two planners: a global planner and a local planner. The global planner refines the initial reference trajectory when the trajectory goes either through an obstacle or near an obstacle and lets the local planner calculate a near-optimal control policy. The global planner comprises two convex programming approaches: the first one helps to refine the reference trajectory, and the second one helps to recover the reference trajectory if the first approach fails to refine. The global planner mainly focuses on real-time performance and obstacles avoidance, whereas the proposed formulation of the constrained nonlinear model predictive control-based local planner ensures safety, dynamic feasibility, and the reference trajectory tracking accuracy for low-speed maneuvers, provided that local and global planners have mean computation times 0.06s (15Hz) and 0.05s (20Hz), respectively, on an NVIDIA Jetson Xavier NX computer. The results of our experiment confirmed that, in cluttered environments, the proposed approach outperformed three other approaches: sampling-based pathfinding followed by trajectory generation, a local planner, and graph-based pathfinding followed by trajectory generation.

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Section: Experimental Procedures and Resultsmentioning

confidence: 99%

Section: Experimental Procedures and Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Optimization-based Trajectory Tracking Approach for Multi-rotor Aerial Vehicles in Unknown Environments

Kulathunga¹,

Hamed²,

Devitt³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…Проте у даних дослідженнях не враховані важливість зон території та ймовірність виявлення об'єктів у зонах, тобто території розглядаються як однор ідні. Відповідно до методології, що представлена у [5], термінальне упра вління рухом динамічних датчиків слід будувати поетапно. Насамперед необхідно побудувати просторову траєкторію руху центру мас літального апарата.…”

Section: аналіз сучасних досліджень та постановка проблемиunclassified

Optimization of the Trajectory of Sensors Motion Taking Into Account the Importance of the Areas of the Monitoring Area Segments and the Probability of Detection of Objects

Petrivskyi¹,

Petrivskyi²,

Шевченко³

et al. 2022

JAIS

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Due to the widespread use of sensors in data collection and processing, one of the key criteria is the amount of information accumulated and energy efficiency. While monitoring the territory, the movement of research objects is common. As a result there is a change in the probability of their detection in the segment of the territory. Also, segments may be of varying importance. Taking these factors into account will significantly increase the amount of information accumulated. The article presents a method of constructing the optimal trajectory of sensors motion taking into account the importance of territory segments and the probability of detection of objects. The method is based on the representation of distribution of the probability of detection of objects and the importance of territory segments in the form of layers and their integration into a layer of the probable value of detected objects. Seven classes of the probable value of detected objects with corresponding numerical and graphical equivalents are considered. As optimal trajectory of sensors motion the trajectory which provides minimum energy expenditure is meant. Energy efficiency is achieved by constructing a trajectory of minimum length as a solution to the salesman’s problem. The set of points at which the trajectory is built is formed on the basis of the layer of the probable value of the detected objects after the procedure of replacing the nodes. A separate node replacement class, or superposition of node replacement classes, is proposed for each class of probable value of detected objects. Replacement of five, three and two nodes is described. A genetic algorithm with modification of crossing and selection rules was used to find a solution to this problem. A set of trajectories is constructed using the proposed algorithm. The analysis of the obtained results confirmed the efficiency of the developed method and allowed to increase the energy efficiency when covering a given area by 76 %.

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Obstacle Avoidance and Trajectory Tracking Control of a Quadrotor UAV Under Wind Disturbance

Cai

Hao

Zhao

et al. 2023

Lecture Notes in Electrical Engineering

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Observer-based fixed-time continuous nonsingular terminal sliding mode control of quadrotor aircraft under uncertainties and disturbances for robust trajectory tracking: Theory and experiment

Cited by 73 publications

References 60 publications

Optimization-based Trajectory Tracking Approach for Multi-rotor Aerial Vehicles in Unknown Environments

Optimization-based Trajectory Tracking Approach for Multi-rotor Aerial Vehicles in Unknown Environments

Optimization of the Trajectory of Sensors Motion Taking Into Account the Importance of the Areas of the Monitoring Area Segments and the Probability of Detection of Objects

Obstacle Avoidance and Trajectory Tracking Control of a Quadrotor UAV Under Wind Disturbance

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