Quadrotor Helicopter Trajectory Tracking Control

Hoffmann, Gabriel; Waslander, Steven L.; Tomlin, Claire J.

doi:10.2514/6.2008-7410

Cited by 276 publications

(174 citation statements)

References 16 publications

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“…The same statement can be found in [12]. Taking into account the amount of attention put into blade flapping phenomena in helicopter analysis, it is interesting why this aspect is frequently neglected in quadrotor modelling, apart from the work described in [7,[12][13][14][15][16].…”

Section: Introductionmentioning

confidence: 77%

Modelling and optimal control system design for quadrotor platform – an extended approach

Zawiski¹,

Błachuta²

2014

Bulletin of the Polish Academy of Sciences Technical Sciences

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Abstract. This article presents the development of a mathematical model of a quadrotor platform and the design of a dedicated control system based on an optimal approach. It describes consecutive steps in development of equations forming the model and including all its physical aspects without commonly used simplifications. Aerodynamic phenomena, such as Vortex Ring State or blade flapping are accounted for during the modelling process. The influence of rotors' gyroscopic effect is exposed. The structure of a control system is described with an application of the optimal LQ regulator and an intuitive way of creating various flight trajectories. Simulation tests of the control system performance are conducted. Comparisons with models available in the literature are made. Based on above, conclusions are drawn about the level of insight necessary in creation of control-oriented and useable model of a quadrotor platform. New possibilities of designing and verifying models of quadrotor platforms are also discussed.

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Section: Introductionmentioning

confidence: 77%

Modelling and optimal control system design for quadrotor platform – an extended approach

Zawiski¹,

Błachuta²

2014

Bulletin of the Polish Academy of Sciences Technical Sciences

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“…На первом этапе перед началом полета строится траектория полета -непрерывная кривая Неподвижные препятствия могут задаваться в виде трехмерных объектов [12,15,24,31].…”

Section: задача управления полетом квадрокоптера по заданному маршрутуunclassified

“…Движение квадрокоптера описывает плоская система дифференциальных уравнений [9,15,24], позволяющая заменить нелинейную систему уравнений линеаризованной системой в окрестности положения равновесия [12,17,26]. Для линейной системы строится асимптотически устойчивое решение с ограничением на угол крена.…”

Section: обзор работunclassified

“…Далее траектория параметризуется временем так, чтобы траектория была осуществима, а общее время полета стало минимальным [12,15,31].…”

Section: обзор работunclassified

“…Планирование оптимальных траекторий с учетом препятствий реализуется методом графа видимости [12], быстрым маршевым методом [12] или алгоритмом RRT* [24].…”

Section: обзор работunclassified

See 2 more Smart Citations

Requirement Specification of Quad-Rotor Flight Control System

Tumurov¹,

Shelekhov²

2015

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Определяется типовая архитектура системы управления вида human-in-the-loop.Набор функциональных требований к системе управления беспилотным 4-х винтовым вертолетом -квадрокоптером -определяется как конкретизация типовой архитектуры.Рассматривается две задачи: управление полетом квадрокоптера по заданной траектории и слежение за движущимся объектом.

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Experience replay–based output feedback Q‐learning scheme for optimal output tracking control of discrete‐time linear systems

Rizvi

Lin

2019

Adaptive Control & Signal

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This paper focuses on solving the adaptive optimal tracking control problem for discrete-time linear systems with unknown system dynamics using output feedback. A Q-learning-based optimal adaptive control scheme is presented to learn the feedback and feedforward control parameters of the optimal tracking control law. The optimal feedback parameters are learned using the proposed output feedback Q-learning Bellman equation, whereas the estimation of the optimal feedforward control parameters is achieved using an adaptive algorithm that guarantees convergence to zero of the tracking error. The proposed method has the advantage that it is not affected by the exploration noise bias problem and does not require a discounting factor, relieving the two bottlenecks in the past works in achieving stability guarantee and optimal asymptotic tracking. Furthermore, the proposed scheme employs the experience replay technique for data-driven learning, which is data efficient and relaxes the persistence of excitation requirement in learning the feedback control parameters. It is shown that the learned feedback control parameters converge to the optimal solution of the Riccati equation and the feedforward control parameters converge to the solution of the Sylvester equation. Simulation studies on two practical systems have been carried out to show the effectiveness of the proposed scheme.

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Quadrotor Helicopter Trajectory Tracking Control

Cited by 276 publications

References 16 publications

Modelling and optimal control system design for quadrotor platform – an extended approach

Modelling and optimal control system design for quadrotor platform – an extended approach

Requirement Specification of Quad-Rotor Flight Control System

Experience replay–based output feedback Q‐learning scheme for optimal output tracking control of discrete‐time linear systems

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