Feedback linearization vs. adaptive sliding mode control for a quadrotor helicopter

Lee, Daewon; Kim, H. Jin; Sastry, S. Shankar

doi:10.1007/s12555-009-0311-8

Cited by 605 publications

(325 citation statements)

References 18 publications

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“…Thus, the total reactive torque by the six propellers is given as follow: 6 ( ) Therefore, according to Fig. 2 and (5), it is easy to obtain the airframe torques generated by the six propellers given by: 2 2 2 2 2 2 2 4 6 1 3 1 5 2 2 2 2 2 2 3 1 4 3 6 2 2 2 2 2 2 3 4 5 1 2 6 sin (…”

Section: C S C S S C S C C S S R C S S S S C C S S C C S S C S C Cmentioning

confidence: 99%

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Adaptive Command Filtered Backstepping Trajectory Tracking Control of Hexarotor UAV

Cui¹,

Zhong²

2017

Proceedings of the 2017 International Conference on Applied Mathematics, Modelling and Statistics Application (AMMSA 2017)

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Abstract-In this paper, a hexarotor unmanned aerial vehicle (UAV) is concerned to solve such problems as smaller payload capacity, lack of both hardware redundancy and anti-crosswind capability for quad-rotor. Considering the under-actuated and strong coupling nonlinear system with external disturbance and parameter uncertainty properties of the hexarotor UAV, a nested double-loops trajectory tracking control strategy is proposed. A position error PID controller is designed as the outer-loop controller, of which the task is to compare the desired trajectory with real position of the hexarotor UAV and export the desired attitude angles to the inner-loop. And, an adaptive commandfiltered backstepping controller is designed as the inner-loop controller which makes use of parameter update laws to estimate the disturbances of the hexarotor UAV. The simulation results show that the proposed control strategy enhances the trajectory tracking performance by controlling the external disturbance and parameter uncertainty.

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Section: C S C S S C S C C S S R C S S S S C C S S C C S S C S C Cmentioning

confidence: 99%

“…In the approach of attitude controller design, dynamic inversion [5], feed linearization and sliding mode control [6], model reference adaptive [7] have been widely used.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Command Filtered Backstepping Trajectory Tracking Control of Hexarotor UAV

Cui¹,

Zhong²

2017

Proceedings of the 2017 International Conference on Applied Mathematics, Modelling and Statistics Application (AMMSA 2017)

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“…Compensation-type controllers [16][17][18][19][20][21], optimal 2 International Journal of Aerospace Engineering control [22][23][24][25], adaptive control [26,27], robust control [28], feedback linearization [27,[29][30][31], and behavioral [32] approaches have all been developed for formation flight applications for fixed wing aircraft and quadrotors.…”

Section: Introductionmentioning

confidence: 99%

Autonomous Close Formation Flight Control with Fixed Wing and Quadrotor Test Beds

Rice

Huo

et al. 2016

International Journal of Aerospace Engineering

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Autonomous formation flight is a key approach for reducing energy cost and managing traffic in future high density airspace. The use of Unmanned Aerial Vehicles (UAVs) has allowed low-budget and low-risk validation of autonomous formation flight concepts. This paper discusses the implementation and flight testing of nonlinear dynamic inversion (NLDI) controllers for close formation flight (CFF) using two distinct UAV platforms: a set of fixed wing aircraft named "Phastball" and a set of quadrotors named "NEO." Experimental results show that autonomous CFF with approximately 5-wingspan separation is achievable with a pair of low-cost unmanned Phastball research aircraft. Simulations of the quadrotor flight also validate the design of the NLDI controller for the NEO quadrotors.

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“…The approach is different from most of the controllers suggested in the literature in that it optimizes a general feedback control gain (feedback operator) which eventually provides the optimal control inputs to the system. Unlike similar counterparts [28][29][30], it does not require any linearization of the system model.…”

Section: Introductionmentioning

confidence: 99%

Optimal time-varying P-controller for a class of uncertain nonlinear systems

Miah

Gueaieb

2014

Int. J. Control Autom. Syst.

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In this manuscript, an optimal time-varying P-controller is presented for a class of continuous-time underactuated nonlinear systems in the presence of process noise associated with systems' inputs. This is a state feedback control strategy where the optimization is performed on a time-varying feedback operator (herein called the feedback control gain). The main goal of the current manuscript is to provide a framework for multi-input multi-output nonlinear systems which yields a satisfactory tracking performance based on the optimal time-varying feedback control gain. Unlike other feedback control techniques that perform dynamic linearization of system models, the proposed time-varying P-controller provides the full-state feedback control to the original nonlinear system model. Hence, this P-controller guarantees global asymptotic statetracking. Furthermore, the bounded system's process noise is taken into consideration to measure the controller's robustness. The proposed P-controller is tested for its nonlinear trajectory tracking and fixed-point stabilization capabilities with two nonholonomic systems in the presence of actuators' noise.

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Feedback linearization vs. adaptive sliding mode control for a quadrotor helicopter

Cited by 605 publications

References 18 publications

Adaptive Command Filtered Backstepping Trajectory Tracking Control of Hexarotor UAV

Adaptive Command Filtered Backstepping Trajectory Tracking Control of Hexarotor UAV

Autonomous Close Formation Flight Control with Fixed Wing and Quadrotor Test Beds

Optimal time-varying P-controller for a class of uncertain nonlinear systems

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