Nonlinear forward path tracking controller for helicopter with slung load

El-Férik, Sami; Syed, Asim H.; Omar, Hanafy M.; Deriche, Mohamed

doi:10.1016/j.ast.2017.07.028

Cited by 27 publications

(7 citation statements)

References 4 publications

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“…To simplify writing, define

s_{*}

and

c_{*}

to represent

\sin (*)

and

\cos (*)

, respectively. The rotation matrix

R

from

I

B

is represented as 5

R = [\begin{array}{ccc} c_{ϕ} c_{θ} & s_{ϕ} s_{θ} s_{ψ} prefix- s_{ψ} c_{ϕ} & {normalc}_{ϕ} s_{θ} c_{ψ} + s_{ϕ} s_{ψ} \\ s_{ϕ} c_{θ} & s_{ϕ} s_{θ} s_{ψ} + c_{ϕ} c_{ψ} & c_{ϕ} s_{θ} s_{ψ} prefix- c_{ψ} s_{ϕ} \\ prefix- s_{θ} & c_{θ} s_{ϕ} & c_{θ} c_{ϕ} \end{array}] .

…”

Section: Problem Statementmentioning

confidence: 99%

“…The rotation matrix from angular velocity to the derivative of Euler angle is represented by

Q (Θ)

, which is expressed as 5

Q (Θ) = [\begin{array}{ccc} 1 & s_{ϕ} t_{θ} & c_{ϕ} t_{θ} \\ 0 & c_{ϕ} & prefix- s_{ϕ} \\ 0 & s_{ϕ} true/ c_{θ} & c_{ϕ} true/ c_{θ} \end{array}] .

…”

Section: Problem Statementmentioning

confidence: 99%

“…Therefore, the anti‐swing control of the unmanned helicopter slung‐load in various situations has naturally become a research hotspot 3,4 . For example, in Reference 5, a nonlinear forward path tracking controller for a skew‐loaded helicopter was designed, in which the anti‐swing delay feedback control term was utilized to suppress the load oscillation. A feedforward controller was proposed with input shaping to reduce the oscillation of slung‐load, which was used to enhance the existing helicopter controller in Reference 6.…”

Section: Introductionmentioning

confidence: 99%

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An adaptive anti‐swing control for the helicopter slung‐load system based on trajectory planning and neural network

Wei

2022

Adaptive Control & Signal

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In this article, an adaptive anti‐swing control method based on trajectory planning and radial basis function neural network (RBFNN) is proposed for the unmanned helicopter slung‐load system with the external disturbances and the continuous system uncertainty. An online trajectory planning method is designed to obtain the desired position, velocity, and acceleration signals of the unmanned helicopter. Then, combining with RBFNN and sliding mode control method, the position loop controller of the unmanned helicopter is designed to make the swing angle stable, and the unmanned helicopter can also track the desired trajectory. The attitude loop controller is designed by sliding mode backstepping method and RBFNN. In the process of controller design, the adaptive laws are designed to adjust the influence of approximation error of RBFNN and the external disturbance. The stability of the closed‐loop system is proved by Lyapunov analysis. Numerical simulation results show that the proposed control strategy is effective.

show abstract

“…To simplify writing, define

s_{*}

and

c_{*}

to represent

\sin (*)

and

\cos (*)

, respectively. The rotation matrix

R

from

I

B

is represented as 5

R = [\begin{array}{ccc} c_{ϕ} c_{θ} & s_{ϕ} s_{θ} s_{ψ} prefix- s_{ψ} c_{ϕ} & {normalc}_{ϕ} s_{θ} c_{ψ} + s_{ϕ} s_{ψ} \\ s_{ϕ} c_{θ} & s_{ϕ} s_{θ} s_{ψ} + c_{ϕ} c_{ψ} & c_{ϕ} s_{θ} s_{ψ} prefix- c_{ψ} s_{ϕ} \\ prefix- s_{θ} & c_{θ} s_{ϕ} & c_{θ} c_{ϕ} \end{array}] .

…”

Section: Problem Statementmentioning

confidence: 99%

“…The rotation matrix from angular velocity to the derivative of Euler angle is represented by

Q (Θ)

, which is expressed as 5

Q (Θ) = [\begin{array}{ccc} 1 & s_{ϕ} t_{θ} & c_{ϕ} t_{θ} \\ 0 & c_{ϕ} & prefix- s_{ϕ} \\ 0 & s_{ϕ} true/ c_{θ} & c_{ϕ} true/ c_{θ} \end{array}] .

…”

Section: Problem Statementmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An adaptive anti‐swing control for the helicopter slung‐load system based on trajectory planning and neural network

Wei

2022

Adaptive Control & Signal

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show abstract

“…It consists of two control systems: an antiswing controller and a tracking controller [22]. The quadcopter with a suspended load system can be considered as a multi-body dynamical system [20]. Two frames are typically used to describe the movements of a quadrotor vehicle.…”

Section: Quadrotor Controllermentioning

confidence: 99%

Hardware-In-the-Loop Simulation of Time-Delayed Anti-Swing Controller for Quadrotor with Suspended Load

Omar

2022

Applied Sciences

Self Cite

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Quadrotor flying vehicles with suspended loads have a lot of applications, such as mine detection and transferring loads for delivery, or through places where ground vehicles cannot reach. In these applications, the payload will be suspended underneath the vehicle and it is subjected to large oscillations due to external disturbances or the acceleration of the vehicle itself. These oscillations add additional forces and moments to the quadrotor, and this deteriorates its performance and stability. In this paper, we developed a hardware-in-the-loop (HIL) simulation platform for a quadrotor with a suspended load system using Gazebo. The developed platform can be used to understand the dynamics of the system and design control systems to suppress the oscillation of the suspended load. An anti-swing controller that is based on time-delayed feedback of the load swing angles is implemented in the designed HIL environment to show the usefulness of the newly developed system and the effectiveness of the anti-swing controller.

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“…1,2 Moreover, the helicopters have unique advantages in external load transportation due to their ability to take off or land vertically and hover at fixed points. 3,4 In addition, compared with the manned helicopters, the unmanned helicopters have wider flight envelope as well as better maneuverability without physiological limits of pilots and thus are more favorable for cooperative multi-lift. 5,6 There were many studies on the cooperative multi-lift.…”

Section: Introductionmentioning

confidence: 99%

Application of social spider optimization and improved active disturbance rejection controller in hierarchical control of cooperative multi-lift with four unmanned helicopters

Duan

Zhao

Tang

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part G:

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To achieve the three-dimensional free movement of the slung load, a load-leading hierarchical control strategy has been adopted recently which divides the cooperative multi-lift system into a load layer, a cable layer, and an aircraft layer. But there exists a non-convex optimization problem in the cable layer when computing the force of each cable, and more control difficulties of the aircraft due to the additional disturbances resulting from the load movement. To solve these problems, an application of the social spider optimization (SSO) algorithm and the improved active disturbance rejection controller (IADRC) in hierarchical control of cooperative multi-lift with four unmanned helicopters is proposed in this study. First, the unmanned helicopters as well as the load are modeled. Then the three layers mentioned above are designed, respectively. Specifically, an optimization method combining SSO with the MATLAB/fmincon function is proposed to solve the non-convex problem in the cable layer. And within the unmanned helicopter layer, the fuzzy theory is introduced into the nonlinear error feedback control strategy of the traditional active disturbance rejection controller (ADRC) to realize the control of the unmanned helicopter. At last, some simulations are carried out, and the results indicate that the system has higher calculation efficiency, smaller steady-state error, and better adaptability to trajectory change or load release with the designed hierarchical control strategy.

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Nonlinear forward path tracking controller for helicopter with slung load

Cited by 27 publications

References 4 publications

An adaptive anti‐swing control for the helicopter slung‐load system based on trajectory planning and neural network

An adaptive anti‐swing control for the helicopter slung‐load system based on trajectory planning and neural network

Hardware-In-the-Loop Simulation of Time-Delayed Anti-Swing Controller for Quadrotor with Suspended Load

Application of social spider optimization and improved active disturbance rejection controller in hierarchical control of cooperative multi-lift with four unmanned helicopters

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