2019
DOI: 10.17706/ijcee.2019.11.1.70-77
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Second Order Sliding Mode Control Using Homogeneity Approach to Control a Fixed-Wing UAV

Abstract: The purpose of this paper consists of developing a robust control law for a fixed wing Unmanned Aerial Vehicle (UAV). To reach such a goal, a homogeneous continuous super twisting algorithm is used to solve the problem of attitude control for an aircraft model known by its nonlinearity and its strong coupling. Being a class of high order sliding mode (HOSM) control, super twisting algorithm (STW) allows finite time output convergence and chattering minimization for systems having relative degree equal to one. … Show more

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Cited by 2 publications
(1 citation statement)
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“…To solve the challenge of attitude stability and proper flight of fixed-wing UAVs, many types of controllers have been proposed in the literature [5]. The reported controllers include designs based on robust PID [6], PID with robust compensator [7], PID with gain scheduling [8], artificial neural networks (ANN), fuzzy logic (FL), prediction-based control [9]- [10], sliding mode [11]- [12], backstepping [13]- [14], [15], linear quadratic Gaussian, [16] and model reference adaptive control (MRAC), which have been thoroughly researched for the task of recovering nominal performance in the presence of uncertainties or actuator failures [17], even though they were particularly susceptible to time delays [18]. A version of indirect MRAC with a low-pass filter, named adaptive control (L AC), was introduced in [19] and [20] to solve these issues and provide a more efficient adaptive solution [15]- [16].…”
Section: Introductionmentioning
confidence: 99%
“…To solve the challenge of attitude stability and proper flight of fixed-wing UAVs, many types of controllers have been proposed in the literature [5]. The reported controllers include designs based on robust PID [6], PID with robust compensator [7], PID with gain scheduling [8], artificial neural networks (ANN), fuzzy logic (FL), prediction-based control [9]- [10], sliding mode [11]- [12], backstepping [13]- [14], [15], linear quadratic Gaussian, [16] and model reference adaptive control (MRAC), which have been thoroughly researched for the task of recovering nominal performance in the presence of uncertainties or actuator failures [17], even though they were particularly susceptible to time delays [18]. A version of indirect MRAC with a low-pass filter, named adaptive control (L AC), was introduced in [19] and [20] to solve these issues and provide a more efficient adaptive solution [15]- [16].…”
Section: Introductionmentioning
confidence: 99%