Adaptive robust backstepping attitude control for a multi-rotor unmanned aerial vehicle with time-varying output constraints

Fu, Chunyang; Wei, Hong; Lu, Huiqiu; Zhang, Lei; Guo, Xiaojun; Tian, Yantao

doi:10.1016/j.ast.2018.05.021

Cited by 93 publications

(46 citation statements)

References 33 publications

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“…Theorem 4.1: For the quadrotor UAV with quantized inputs when the Assumptions 2.1-2.2 satisfied, the actual controllers (18), (37) with the virtual control signals (12),…”

Section: Stability Analysismentioning

confidence: 99%

“…Subsequently, many researchers focused on developing the trajectory tracking control schemes of quadrotor UAV based on DSC technique, see [16]- [20] and references therein. In [18], adaptive DSC algorithm was proposed under time-varying output constraints and model uncertainties. The adaptive prescribed performance DSC scheme was given in [20], which made the tracking error satisfy the predefined performance indexes.…”

mentioning

confidence: 99%

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Finite-Time Adaptive Fuzzy Quantized Control for a Quadrotor UAV

Yang

Cui

et al. 2020

IEEE Access

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In this paper, a finite-time command filtered backstepping (FTCFB) adaptive trajectory tracking control strategy is proposed for a quadrotor unmanned aerial vehicle (UAV) with quantized inputs and external disturbances. For the position subsystem and attitude subsystem, a finite-time command filter is introduced to faster approximate the derivative of virtual control signal, which can effectively avoid the problem of explosion of complexity inherent in the traditional backstepping design procedure. The fractional order error compensation mechanism is designed to remove the filter error, and it further improves control performance. From the Lyapunov stability theory, the boundedness of all signals in the closed-loop system is rigorously proved, and the position and attitude tracking errors can converge to a small neighborhood of the origin in finite-time. Finally, a numerical example is conducted to intuitively show the validity of the developed control scheme.

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“…Theorem 4.1: For the quadrotor UAV with quantized inputs when the Assumptions 2.1-2.2 satisfied, the actual controllers (18), (37) with the virtual control signals (12),…”

Section: Stability Analysismentioning

confidence: 99%

mentioning

confidence: 99%

Finite-Time Adaptive Fuzzy Quantized Control for a Quadrotor UAV

Yang

Cui

et al. 2020

IEEE Access

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“…At this time, PID controller often hit a bottleneck. Therefore, many advanced control methods such as adaptive control (AC) [ 7 , 8 , 9 , 10 ], sliding mode control (SMC) [ 11 , 12 , 13 , 14 , 15 ], neural network control (NNC) [ 10 , 16 , 17 ], fuzzy control (FC) [ 6 , 18 , 19 ], active disturbance rejection control (ADRC) [ 20 , 21 ], Disturbance Observer-Based Control [ 22 , 23 ], and Extended State Observer (ESO) [ 7 , 24 , 25 ] have been studied to deal with nonlinear and uncertain problems. Among them, SMC has been widely praised in nonlinear control systems because of its good dynamic performance, insensitive to nonlinear disturbances and robustness to parameter perturbation.…”

Section: Introductionmentioning

confidence: 99%

“…As we all know that the adaptive control (AC) can estimate the uncertainty online by constructing an appropriate adaptive law without prior knowledge of the upper bound of uncertainty [ 7 , 8 , 9 , 10 , 15 ], which can improve the robustness of the control system. Because of this, the hybrid control of AC and SMC does not need high gain to obtain fast convergence performance, which can effectively solve the chattering problem and has great potential to deal with nonlinear disturbance and uncertainty.…”

Section: Introductionmentioning

confidence: 99%

High Performance Both in Low-Speed Tracking and Large-Angle Swing Scanning Based on Adaptive Nonsingular Fast Terminal Sliding Mode Control for a Three-Axis Universal Inertially Stabilized Platform

Wang

Yang

Kuang

et al. 2020

Sensors

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In order to improve the performance in the practical engineering applications including so called low-speed video tracking and large-angle swing scanning imaging at the same time for a three-axis universal inertially stabilized platform (UISP), we propose an adaptive nonsingular fast terminal sliding mode control (ANFTSMC) strategy subjected to the uncertain disturbances and input saturation constraints. First of all, a second-order dynamic model is established with uncertain disturbances and input saturation constraints. Secondly, a nonsingular fast terminal sliding mode controller (NTSMC) is constructed to ensure the system error converges to zero fast in a finite time; meanwhile, a novel reaching law based on a modified normal distribution function is designed to adjust the control gain. Thirdly, an adaptive control law is designed to online estimate the parameters of the lumped uncertain disturbances. Additionally, the stability of the control system is proved by Lyapunov theory. Finally, extensive comparative simulations and experiments are carried out, the results comprehensively show the effectiveness and superiority of the proposed control method, which can accelerate convergence, weaken the chattering, and has the better control accuracy and robust performance both in the low-speed tracking and large-angle swing scanning applications. Moreover, the exact dynamic model and the prior knowledge of the upper bounds of the disturbances are not required during the procedure of the controller design, which make it have more extensive application value in practical engineering.

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“…Despite the popularity and advantage of the backstepping method, it is sensitive to the disturbances, and control performances will be degraded when the parameter uncertainties and external perturbations occur. To overcome the drawback of the sensitivity to the uncertainties, further efforts have been made on the enhanced backstepping approaches [40]- [45], among which the observers based one has been extensively used. The robustness of the observers based control stems from the satisfactory performances of the observer in estimating and compensating uncertainties and disturbances [46], [47].…”

Section: Introductionmentioning

confidence: 99%

Robust and Adaptive Backstepping Control for Hexacopter UAVs

Zhang

Deng

et al. 2019

IEEE Access

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A nonlinear robust and adaptive backstepping control strategy is hierarchically proposed to solve the trajectory tracking problem of hexacopter UAVs. Due to the under-actuated and coupled properties of the hexacopter dynamics, the nominal backstepping control approach is fully designed as the main controller. Considering the model uncertainties and external disturbances perturbing the system stability, a robust 2 nd-order linear extended state observer (LESO) with more reliable velocity feedback is devised to observe and suppress the instabilities, and peaking phenomena in the observation are removed. Usually, large observer gains are selected to reduce the tracking errors but will amplify the measurement noise. To further enhance the system robustness, an adaptive switching function based compensator is introduced to eliminate the observation errors, through which the requirement on large observer gains is relaxed, and high gain behaviors of the LESO are avoided. Stability analysis proves that the nonlinear control scheme can ensure the hexacopter UAV asymptotic tracking along the designated trajectory. Comparative simulations under different controllers are carried out to demonstrate the efficiency and superiority of the proposed control scheme. INDEX TERMS Hexacopter UAV, trajectory tracking, robust backstepping control, 2 nd-order LESO, hierarchical compensators.

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Adaptive robust backstepping attitude control for a multi-rotor unmanned aerial vehicle with time-varying output constraints

Cited by 93 publications

References 33 publications

Finite-Time Adaptive Fuzzy Quantized Control for a Quadrotor UAV

Finite-Time Adaptive Fuzzy Quantized Control for a Quadrotor UAV

High Performance Both in Low-Speed Tracking and Large-Angle Swing Scanning Based on Adaptive Nonsingular Fast Terminal Sliding Mode Control for a Three-Axis Universal Inertially Stabilized Platform

Robust and Adaptive Backstepping Control for Hexacopter UAVs

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