Spatial Modeling and Robust Flight Control Based on Adaptive Sliding Mode Approach for a Quadrotor MAV

Castañeda, Herman; Gordillo, José Luís

doi:10.1007/s10846-018-0819-3

Cited by 18 publications

(16 citation statements)

References 18 publications

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“…14(a)) and velocity ( Fig. 14 (b)), which signifies not only the steady-state error converges to zero asymptotically, but also the first-order consensus (16) has been achieved.…”

Section: B Simulation Of Consensus Formation Tracking Control For Mumentioning

confidence: 87%

“…Theorem 3: Distributed consensus control for system (23) can be decomposed into the form of formation control and the weighted sum form of all adjacent formation distance controllers, as given in (33), which can achieve the finite-time first-order consensus shown in (15) and (16).…”

Section: Distributed Consensus Control Algorithm For Multiple Quadmentioning

confidence: 99%

“…An adaptive SMC is designed in [15] based on the back-stepping technique with the advantages of simplicity in design and ease of application. An adaptive super-twisting sliding model algorithm (STA) is provided in [16] to reduce the control effort as well as the chattering effect. In addition, finite-time SMC for quad rotor control gets more attention for its advantages in terms of fast response, better robustness and perturbation attenuation [2], [17]- [19].…”

Section: Introductionmentioning

confidence: 99%

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An Adaptive Distributed Consensus Control Algorithm Based on Continuous Terminal Sliding Model for Multiple Quad Rotors’ Formation Tracking

Jiu

Sun

et al. 2019

IEEE Access

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Distributed consensus formation tracking problem of slow convergence and low accuracy for multiple quad rotors are solved in this paper. Continuous nonsingular terminal sliding model algorithm (CNTSMA) under Inner-Outer loop control structure is considered to deal with the control problem of nonlinear, strong coupling and underactuated characteristic of a quad rotor. For better convergence and higher tracking accuracy, an adaptive algorithm (denoted by ACNTSMA) further focused on coupling of x and y directions, with sliding model observer (SMO) to compensate system disturbances and uncertainties is proposed. Furthermore, to solve the consensus formation tracking problem, a consensus control protocol under a full-connected topology based on ACNTSMA is proposed, including formation pattern consensus controller and formation distance consensus controller. Stability theory and simulation results prove the proposed control algorithm is able to accurately achieve the first-order (position and velocity) consensus for multiple quad rotors' formation tracking. Besides, stability analysis of the proposed consensus control protocol illustrates that all sliding modes with finite-time stability applicable to second-order integral models are supposed to be established. And the proposed controller also has better convergence and faster response speed with no chattering for trajectory tracking. INDEX TERMS Distributed formation tracking, consensus, continuous terminal sliding model algorithm, adaptive algorithm, multiple quad rotors, convergence.

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“…14(a)) and velocity ( Fig. 14 (b)), which signifies not only the steady-state error converges to zero asymptotically, but also the first-order consensus (16) has been achieved.…”

Section: B Simulation Of Consensus Formation Tracking Control For Mumentioning

confidence: 87%

Section: Distributed Consensus Control Algorithm For Multiple Quadmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An Adaptive Distributed Consensus Control Algorithm Based on Continuous Terminal Sliding Model for Multiple Quad Rotors’ Formation Tracking

Jiu

Sun

et al. 2019

IEEE Access

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“…The dynamics of the quad-rotor aircraft used for the mathematical modelling and the kinematic equation of Euler angles of the UAV taken from [11] and [12];…”

Section: Modelling Of the Uavmentioning

confidence: 99%

PSO with Robust Disturbance Rejection Controller for Maneuvering Control the Altitude of UAV

2020

GJET

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In this research article, particle swarm optimization (PSO) algorithm with variable weights and robust disturbance rejection (RDR) controller used to control the height of unmanned aerial vehicle (UAV). To solve the problem of controller parameters and robustness in obtaining a set of optimal solutions for the attitude control movements of the quadrotor UAV. The algorithm designed in this article is mainly composed of two parts; the first one in accordance with the iterative process, the distance of swarm particles with the variable weight of the dynamic change in the particle size of the global optimum set the coefficient to control its impact on the degree of inertial weight. The global optimal value of the result shows that the optimization algorithm is effective to adjust the parameters of the designed controller, which in result guarantee the quality in the control of the UAV and improve the design efficiency.

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“…The algorithm is robust to bounded and derivative bounded perturbations, but the magnitude of these bounds must be known in order to guarantee stability. On the other hand, adaptive strategies have arisen to deal with the control effort such as in [19,20]. However, the tuning of these algorithms is very difficult.…”

Section: Introductionmentioning

confidence: 99%

Embedded Flight Control Based on Adaptive Sliding Mode Strategy for a Quadrotor Micro Air Vehicle

Castañeda

Gordillo

2019

Electronics

Self Cite

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The design of an embedded flight controller for a quadrotor micro air vehicle, which is subject to uncertainties and perturbations, is addressed. In order to obtain robustness against bounded uncertainties and disturbances, an adaptive sliding mode controller is proposed. The control adaptive gains allow using only necessary control to satisfy the task, reducing the chattering effect and at the same time reject external perturbations. Furthermore, a stability analysis of the closed-loop system is given. Finally, simulations and experimental results carried out on a commercial micro air vehicle demonstrate the feasibility and advantages of the proposed flight controller.

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Spatial Modeling and Robust Flight Control Based on Adaptive Sliding Mode Approach for a Quadrotor MAV

Cited by 18 publications

References 18 publications

An Adaptive Distributed Consensus Control Algorithm Based on Continuous Terminal Sliding Model for Multiple Quad Rotors’ Formation Tracking

An Adaptive Distributed Consensus Control Algorithm Based on Continuous Terminal Sliding Model for Multiple Quad Rotors’ Formation Tracking

PSO with Robust Disturbance Rejection Controller for Maneuvering Control the Altitude of UAV

Embedded Flight Control Based on Adaptive Sliding Mode Strategy for a Quadrotor Micro Air Vehicle

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