Real-time attitude control of 3 DOF quadrotor UAV using modified Super Twisting algorithm

Kahouadji, Mouad; Mokhtari, Mohammed; Choukchou-Braham, Amal; Cherki, Brahim

doi:10.1016/j.jfranklin.2019.11.038

Cited by 38 publications

(13 citation statements)

References 11 publications

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“…In fact, the super‐twisting algorithm is essentially theorized as an important technique to eliminate the system chattering due to the discontinuous control action 57,58 . Hence, it becomes a robust technique that lessens the chattering phenomenon and guarantees the fast finite time convergence, while it does not need to differentiate the sliding surface 59 . The super‐twisting‐based surface can be defined by the following relationship:

([], \begin{array}{c} {\overset{truê}{S}}_{ST, 1} \\ {\overset{truê}{S}}_{ST, 2} \end{array}) = ([], \begin{array}{c} - c_{11} \sqrt{|{\overset{i}{true}}_{normalB} - i_{normalB}^{*}|} sat ((), {\overset{truê}{i}}_{B} - i_{B}^{*}) - c_{12} \int_{0}^{t} sat ((), {\overset{truê}{i}}_{B} - i_{B}^{*}) . italicdt \\ - c_{21} \sqrt{|{\overset{v}{true}}_{o} - v_{o}^{*}|} sat ((), {\overset{truê}{v}}_{o} - v_{o}^{*}) - c_{22} \int_{0}^{t} sat ((), {\overset{truê}{v}}_{o} - v_{o}^{*}) . italicdt \end{array})

…”

Section: Fractional‐order Super‐twisting Sliding Mode Control Design and Analysismentioning

confidence: 99%

Robust fractional‐order super‐twisting sliding mode control to accurately regulate lithium‐battery / super‐capacitor hybrid energy storage system

Falehi

Torkaman

2021

Int J Energy Res

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Summary One of the main challenges in front of the inventors and researchers to compensate the power quality problems is the existence of an efficient and reliable electric energy source for dynamic voltage restorer (DVR). Recent advances in the technologies of lithium‐battery (LB) and super‐capacitor (SC) have made them possible to be used as hybrid energy storage system (HESS) for DC‐power supply of DVR. But then, a robust and efficient controller must be essentially designed to compensate the intricate correlation between system components, unknown nonlinearities, parameter uncertainties related to the HESS. Hence, fractional‐order super‐twisting sliding mode control (FOSTSMC) is proposed for LB/SC‐HESS to smoothly and accurately smoothly track the current reference and control the DC‐link voltage of the asymmetric half‐cascaded multilevel inverter of DVR during different compensation conditions. As the primary controller, FOSTSMC has compensated the unknown nonlinear parts and parameter uncertainties related to LB/SC‐HESS through the real‐time disturbance estimation using sliding mode state and disturbance observer (SMSDO). Both the battery current and DC‐link voltage due to the physical measurability are chosen to design the control scheme based on the proposed FOSTSMC. The proposed controller has been compared with the proportional integral derivative and the sliding mode control under different probable scenarios to evaluate and validate its observability and controllability. To better present the effects of FOSTSMC, AHCMLI, and HESS‐based DVR, they have been quantified as follows: Three real‐time stability benchmarks that is, overshoot, undershoot and settling time are respectively attained for FOSTSMC: 0.6, 0.4, and 0.03; for sliding mode control: 1.1, 0.7 and 0.019; for proportional integral derivative: 0.9, 2, and 0.117. That is to say, FOSTSMC can smoothly and accurately track the current reference and control the DC‐link voltage during different compensation conditions as compared with other controllers. Asymmetric half‐cascaded multilevel inverter can provide 33 steps with consideration of 12 unidirectional switches, whereas binary, trinary, and other multilevel structures can provide less than 27 steps with consideration of 12 switches. The quasi‐AC voltage synthesizer‐based DVR can completely and accurately compensate the voltage sag and swell with THD of 2.12 and 2.35, respectively. The THD of mal‐compensation voltage sag and swell using the conventional DVR are respectively 11.57 and 13.86.

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([], \begin{array}{c} {\overset{truê}{S}}_{ST, 1} \\ {\overset{truê}{S}}_{ST, 2} \end{array}) = ([], \begin{array}{c} - c_{11} \sqrt{|{\overset{i}{true}}_{normalB} - i_{normalB}^{*}|} sat ((), {\overset{truê}{i}}_{B} - i_{B}^{*}) - c_{12} \int_{0}^{t} sat ((), {\overset{truê}{i}}_{B} - i_{B}^{*}) . italicdt \\ - c_{21} \sqrt{|{\overset{v}{true}}_{o} - v_{o}^{*}|} sat ((), {\overset{truê}{v}}_{o} - v_{o}^{*}) - c_{22} \int_{0}^{t} sat ((), {\overset{truê}{v}}_{o} - v_{o}^{*}) . italicdt \end{array})

…”

Section: Fractional‐order Super‐twisting Sliding Mode Control Design and Analysismentioning

confidence: 99%

Robust fractional‐order super‐twisting sliding mode control to accurately regulate lithium‐battery / super‐capacitor hybrid energy storage system

Falehi

Torkaman

2021

Int J Energy Res

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“…For this trajectory tracking scenario, we consider a practical and more realistic example. The quadrotor is required to accomplish a flight mission by following a set of waypoints listed in the form of ðx wp , y wp , z wp Þ triples as follows: (0,0,0), (0,0,1), (0,0,1), (10,0,5), (20,20,5), (25,35,5), (25,60,5), (20,80,10), (5,90,15), (-10,90,15), (-17,70,15), (-20,40,15), (-15,10,1), (0,0,1), (0,0,1). In practice, these waypoints can be set manually or can be generated by a specific path planning algorithm such as the well-known rapidly exploring random tree (RRT) algorithm [8] or A * Algorithm [61].…”

Section: Trajectory Trackingmentioning

confidence: 99%

“…In our recently published study [27], a finite-time observer-based robust continuous twisting control is proposed for an uncertain quadrotor system subjected to disturbances. Another work reported in [35] comes up with a modified super twisting algorithm that can ensure robustness and finite-time convergence for the quadrotor helicopter. In the work [36], the tracking errors are driven to zero in finite-time by employing a fractional-order controller based on nonsingular control law.…”

Section: Introductionmentioning

confidence: 99%

Robust Finite-Time Trajectory Tracking Control of Quadrotor Aircraft via Terminal Sliding Mode-Based Active Antidisturbance Approach: A PIL Experiment

Mechali

Iqbal

Xie

et al. 2021

International Journal of Aerospace Engineering

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This paper presents an accurate solution of finite-time Cartesian trajectory tracking control problem of a quadrotor system by designing and implementing a novel robust flight-control algorithm. The quadrotor is subject to nonlinearities, unmodeled dynamics, parameters’ uncertainties, and external time-varying disturbances. To reject the disturbances and enhance the control system’s robustness, a terminal sliding mode-based active antidisturbance control (TSMBAADC) approach is proposed for rotational and translational subsystems. To improve the tracking performance, a nonlinear continuous terminal sliding manifold and a fast reaching law are proposed in this work to quickly drive the systems’ states to the equilibrium point even in the presence of lumped disturbances. The convergence time of the states can be pretuned based on the parameters of the sliding manifold and the reaching law. Lyapunov theorem is used to provide a rigorous stability proof for the feedback control system. Numerical simulations and processor-in-the-loop (PIL) experiments are conducted to validate and implement the designed flight control algorithm on real autopilot hardware. The novelty of the proposed research lies in hardware implementation of a sophisticated version of modern control technique that exhibits a multitude of distinguishing features including but not limited to (i) finite-time tracking stability featuring fast convergence is ensured, (ii) chattering and singularity problems in sliding mode control (SMC) are avoided, and (iii) null steady-state error is achieved along with enhanced robustness. Finally, the proposed control law is compared with two recently reported research works. Results of performance comparison in term of the integral of square error (ISE) and the absolute value of the derivative of the input u t (IADU) dictate that the proposed technique overperforms by precision and chattering alleviation.

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“…The FACAC and ACAC controllers are compared to verify the effectiveness of the feedforward maintaining and tracking control law. The FACAC controller is compared with the conventional PID controller and the modified super twisting sliding mode control (MSTW) controller proposed in [38].…”

Section: A Performance With Attitude Settlingmentioning

confidence: 99%

Quadrotor Attitude Control via Feedforward All-Coefficient Adaptive Theory

et al. 2020

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The use of quadrotors is proliferating across many civil applications, including those in the areas of the Internet of Things (IoT) and communications. Attitude control plays an important role in these applications, and designing a quadrotor attitude controller is a challenging task. Recently, several design methods for the attitude controller were presented with an accurate model. However, during the flying state, the quadrotor may be affected by several factors that cause unpredictable disturbances to the model. As a result, an accurate model of disturbances is difficult to establish. To address this problem, in this paper, a novel linear feedforward all-coefficient adaptive control (FACAC) strategy based on characteristic modeling is proposed. The contributions of our work are as follows. First, a second-order characteristic model of the quadrotor attitude control is established based on the dynamic equations. Second, an all-coefficient adaptive control (ACAC) controller that consists of the golden-section adaptive control law, the logic integral, and logic differential control laws is designed. The feedforward maintaining and tracking control law is integrated into the ACAC controller to shorten the settling time. Finally, extensive simulation results demonstrate that the performance of the proposed FACAC controller outperforms the state-of-the arts.

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Real-time attitude control of 3 DOF quadrotor UAV using modified Super Twisting algorithm

Cited by 38 publications

References 11 publications

Robust fractional‐order super‐twisting sliding mode control to accurately regulate lithium‐battery / super‐capacitor hybrid energy storage system

Robust fractional‐order super‐twisting sliding mode control to accurately regulate lithium‐battery / super‐capacitor hybrid energy storage system

Robust Finite-Time Trajectory Tracking Control of Quadrotor Aircraft via Terminal Sliding Mode-Based Active Antidisturbance Approach: A PIL Experiment

Quadrotor Attitude Control via Feedforward All-Coefficient Adaptive Theory

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