Integral Backstepping Sliding Mode Control for Unmanned Autonomous Helicopters Based on Neural Networks

Wan, Min; Lungu, Mihai

doi:10.3390/drones7030154

Cited by 4 publications

(4 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Furthermore, to the authors' knowledge, this estimation technique has not been used for estimation of rotational and translational state variables of quadrotor. Although BSC technique combined with SMC has been explored by Jia et al (2017) and Wan et al (2023). However, the chattering issue inherited by SMC technique is of much concern.…”

Section: Introductionmentioning

confidence: 99%

Model-free low-power observer based robust trajectory tracking control of UAV quadrotor with unknown disturbances

Siddiqui,

Zhu,

Rasool

et al. 2024

AEAT

View full text Add to dashboard Cite

Purpose The purpose of this paper is to design an output-feedback algorithm based on low-power observer (LPO), robust chattering-free controller and nonlinear disturbance observer (DO) to achieve trajectory tracking of quadrotor in the Cartesian plane. Design/methodology/approach To achieve trajectory tracking control, firstly the decoupled rotational and translational model of quadrotor are modified by introducing backstepped state-space variables. In the second step, robust integral sliding mode control is designed based on the proportional-integral-derivative (PID) technique. In the third step, a DO is constructed. In next step, the measurable outputs, i.e. rotational and translational state variables, are used to design the LPO. Finally, in the control algorithm all state variables and its rates are replaced with its estimates obtained using the state-observer. Findings The finding includes output-feedback control (OFC) algorithm designed by using a LPO. A modified backstepping model for rotational and rotational systems is developed prior to the design of integral sliding mode control based on PID technique. Unlike traditional high-gain observers (HGO), this paper used the LPO for state estimation of quadrotor systems to solve the problem of peaking phenomenon in HGO. Furthermore, a nonlinear DO is designed such that it attenuates disturbance with unknown magnitude and frequency. Moreover, a chattering reduction criterion has been introduced to solve the inherited chattering issue of controllers based on sliding mode technique. Practical implications This paper presents input and output data-driven model-free control algorithm. That is, only input and output of the quadrotor model are required to achieve the trajectory tracking control. Therefore, for practical implementation, the number of on-board sensor is reduced. Originality/value Although extensive research has been done for designing OFC algorithms for quadrotor, LPO has never been implemented for the rotational and translational state estimations of quadrotor. Furthermore, the mathematical model of rotational and translational systems is modified by using backstepped variables followed by the controller designed using PID and integral sliding mode control technique. Moreover, a DO is developed for attenuation of disturbance with unknown bound, magnitude and frequency.

show abstract

Section: Introductionmentioning

confidence: 99%

Model-free low-power observer based robust trajectory tracking control of UAV quadrotor with unknown disturbances

Siddiqui,

Zhu,

Rasool

et al. 2024

AEAT

View full text Add to dashboard Cite

show abstract

“…With the purpose of taking the maximum benefit of the capabilities of these vehicles for tracking purposes, numerous controllers have been proposed [4][5][6]. In [7], successful implementation of linear control techniques, including the linear quadratic regulator (LQR), was achieved for low-speed indoor flights.…”

Section: Introductionmentioning

confidence: 99%

Saturated Trajectory Tracking Controller in the Body-Frame for Quadrotors

Madeiras,

Cardeira,

Oliveira

et al. 2024

Drones

View full text Add to dashboard Cite

This paper introduces a quadrotor trajectory tracking controller comprising a steady-state optimal position controller with a normed input saturation and modular integrative action coupled with a backstepping attitude controller. First, the translational and rotational dynamical models are designed in the body-fixed frame to avoid external rotations and are partitioned into an underactuated position system and a quaternion-based attitude system. Secondly, a controller is designed separately for each subsystem, namely, (i) the position controller synthesis is derived from the Maximum Principle, Lyapunov, and linear quadratic regulator (LQR) theory, ensuring the global exponential stability and steady-state optimality of the controller within the linear region, and global asymptotic stability is guaranteed for the saturation region when coupled with any local exponential stable attitude controller, and (ii) the attitude system, with the quaternion angles and the angular velocity as the controlled variables, is designed in the error space through the backstepping technique, which renders the overall system, position, and attitude, with desirable closed-loop properties that are almost global. The overall stability of the system is achieved through the propagation of the position interconnection term to the attitude system. To enhance the robustness of the tracking system, integrative action is devised for both position and attitude, with emphasis on the modular approach for the integrative action on the position controller. The proposed method is experimentally validated on board an off-the-shelf quadrotor to assess the resulting performance.

show abstract

“…However, the strong coupling and underactuation, cased by strong nonlinearity, have brought great challenges to study the flight control of the UAH. In recent years, research on UAH control systems has achieved a large number of elegant results [1][2][3][4][5]. For instance, in [3], the uncertain terms in the UAH system were approximated via neural networks, and an integral backstepping method combined with a sliding mode control were proposed by considering input saturation.…”

Section: Introductionmentioning

confidence: 99%

“…In recent years, research on UAH control systems has achieved a large number of elegant results [1][2][3][4][5]. For instance, in [3], the uncertain terms in the UAH system were approximated via neural networks, and an integral backstepping method combined with a sliding mode control were proposed by considering input saturation. In [4], an adaptive sliding mode fault-tolerant control strategy was proposed for the quadrotor UAV with variable loads, which can compensate for the faults via a neural network approximator.…”

Section: Introductionmentioning

confidence: 99%

Trajectory Tracking Control Based on a Composite Disturbance Observer for Unmanned Autonomous Helicopters under Multiple Disturbances

Pan,

Wang,

Zhang

et al. 2024

Machines

View full text Add to dashboard Cite

This paper studies the trajectory tracking anti-disturbance control of unmanned autonomous helicopters (UAHs) under matched disturbances and mismatched ones. Firstly, the six-degrees-of-freedom UAH nonlinear system is simplified via feedback linearization to handle strong coupling, in which the multiple disturbances are composed of modeled disturbances and time-varying bounded ones. Secondly, in order to estimate these disturbances, a new design method of a composite disturbance observer is proposed. On the one hand, for the mismatched disturbances, a normal disturbance observer (DO) combined with a backstepping control are utilized to handle their negative effect. On the other hand, two refined disturbance observers (RDOs) are constructed to estimate the matched disturbances, in which the coupling estimations are involved. Then, by designing two anti-disturbance composite controllers, the boundedness of the tracking errors is guaranteed by using the Lyapunov stability theory. Finally, some numerical simulations are provided to demonstrate the effectiveness and advantage of the proposed control scheme.

show abstract

Integral Backstepping Sliding Mode Control for Unmanned Autonomous Helicopters Based on Neural Networks

Cited by 4 publications

References 38 publications

Model-free low-power observer based robust trajectory tracking control of UAV quadrotor with unknown disturbances

Model-free low-power observer based robust trajectory tracking control of UAV quadrotor with unknown disturbances

Saturated Trajectory Tracking Controller in the Body-Frame for Quadrotors

Trajectory Tracking Control Based on a Composite Disturbance Observer for Unmanned Autonomous Helicopters under Multiple Disturbances

Contact Info

Product

Resources

About