Second order sliding mode control for quadrotor

Sudhir,; Swamp, A.

doi:10.1109/cmi.2016.7413717

Cited by 15 publications

(4 citation statements)

References 16 publications

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“…Swamp (2016) introduced a second-order sliding mode control that was designed based on Lyapunov theory to stabilize the quadrotor. This second-order sliding mode controller demonstrated promising results comparing to the conventional sliding mode and ensures robustness as well [81]. A simple SMC has been portrayed in Figure 5.…”

Section: Sliding Modementioning

confidence: 96%

A Review on Comparative Remarks, Performance Evaluation and Improvement Strategies of Quadrotor Controllers

Roy

Islam

Sadman³

et al. 2021

Technologies

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The quadrotor is an ideal platform for testing control strategies because of its non-linearity and under-actuated configuration, allowing researchers to evaluate and verify control strategies. Several control strategies are used, including Proportional-Integral-Derivative (PID), Linear Quadratic Regulator (LQR), Backstepping, Feedback Linearization Control (FLC), Sliding Mode Control (SMC), and Model Predictive Control (MPC), Neural Network, H-infinity, Fuzzy Logic, and Adaptive Control. However, due to several drawbacks, such as high computation, a large amount of training data, approximation error, and the existence of uncertainty, the commercialization of those control technologies in various industrial applications is currently limited. This paper conducts a thorough analysis of the current literature on the effects of multiple controllers on quadrotors, focusing on two separate approaches: (i) controller hybridization and (ii) controller development. Besides, the limitations of the previous works are discussed, challenges and opportunities to work in this field are assessed, and potential research directions are suggested.

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Section: Sliding Modementioning

confidence: 96%

A Review on Comparative Remarks, Performance Evaluation and Improvement Strategies of Quadrotor Controllers

Roy

Islam

Sadman³

et al. 2021

Technologies

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“…The key problem in first order SMC was chattering effect which arises due to the control shift between two structures. Another study on second order sliding mode control (SOSMC) has been reported in [76], where the altitude of quadrotor UAV was tracked successfully. Another work on same control approach for quadrotor control was addressed in [77] where overall control problem was divided into five parts which simplifies the control design.…”

Section: Sliding Mode Controlmentioning

confidence: 99%

Nonlinear and Adaptive Intelligent Control Techniques for Quadrotor UAV – A Survey

Mo¹,

Farid²

2018

Asian Journal of Control

171

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Parametric uncertainties and coupled nonlinear dynamics are inherent in quadrotor configuration and infer adaptive nonlinear approaches to be used for flight control system. Numerous adaptive nonlinear and intelligent control techniques, which have been reported in the literature for designing quadrotor flight controller by various researchers, are investigated in this paper. As a priori, each conventional nonlinear control technique is discussed broadly and then its adaptive/observer based augmentation is conferred along with all possible variants. Among conventional nonlinear control approaches, feedback linearization, backstepping, sliding mode, and model predictive control, are studied. Intelligent control approaches incorporating fuzzy logic and neural networks are also discussed. In addition to adaption based parametric uncertainty handling, various other aspects of each control technique regarding stability, disturbance rejection, response time, asymptotic, exponential and finite time convergence etc., are discussed in sufficient depth. The contribution of this paper is the provision of detailed and in depth discussion on quadrotor nonlinear control approaches to the flight control designers.

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“…Hence, the literature review of the improvement of the SMC method is investigated as the following. To achieve control stability and desired tracking of quadcopters, sliding mode control in second-order was studied in [15,16] where a linear combination of position and velocity tracking errors composes a sliding manifold solved by using Hurwitz stability theory. In practical scenarios with external disturbances, the improvement of the SMC with observer-based in [17][18][19] addressed this limitation based on backstepping, which was used to design robust controllers.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Sliding Mode Control for Attitude and Altitude System of a Quadcopter UAV via Neural Network

et al. 2021

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In this paper, a sliding mode control based on neural networks is proposed for attitude and altitude system of quadcopter under external disturbances. First, the dynamic model of the quadcopter is considered under external disturbances. Sliding mode controllers are then integrated with neural network algorithm to achieve the time-varying sliding surface; their coefficients in sliding surface are adjusted through backpropagation law. The disturbance observer is also combined with sliding mode controllers to estimate and handle the external disturbances. Finally, the Lyapunov theory is applied to validate the stability of suggested control method. The performance of proposed sliding mode control has been evaluated using a numerical simulation. The results show that the attitude and altitude controller based on suggested algorithm has a better tracking performance and disturbance rejection.

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Second order sliding mode control for quadrotor

Cited by 15 publications

References 16 publications

A Review on Comparative Remarks, Performance Evaluation and Improvement Strategies of Quadrotor Controllers

A Review on Comparative Remarks, Performance Evaluation and Improvement Strategies of Quadrotor Controllers

Nonlinear and Adaptive Intelligent Control Techniques for Quadrotor UAV – A Survey

Adaptive Sliding Mode Control for Attitude and Altitude System of a Quadcopter UAV via Neural Network

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