An Optimized Fuzzy-Padé Controller Applied to Attitude Stabilization of a Quadrotor

Salehfard, Sepideh; Abdollahi, Taleb; Chen, Xiong; Ai, Yong-Heng

doi:10.1007/s12555-017-0141-z

Cited by 10 publications

(5 citation statements)

References 15 publications

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“…As it can be observed, the tracking of variables x, y, z illustrated that both controllers drive the system towards the prescribed trajectory. The proposed methods have a higher level of accuracy compared to those presented in (Salehfard, 2018) and .…”

Section: Spiral Trajectory Trackingmentioning

confidence: 84%

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Neural Network and Fuzzy-logic-based Self-tuning PID Control for Quadcopter Path Tracking

Hamidi¹,

Mjahed²,

Kari³

et al. 2019

SIC

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The purpose of this research is to design adaptive control methods for addressing the stabilization and trajectory tracking problems in a quadcopter unmanned aerial vehicle (UAV). To accomplish these tasks, a comparative study of the Proportional Integral Derivative (PID) and PD controllers is performed. Intelligent algorithms (IAs) have been used to tune the conventional structure of PID/PD controllers. The proposed hybrid intelligent controllers consist of the neural network PID/PD (NNPID/PD) and the Optimized Fuzzy PID/PD based on the Particle Swarm Optimization (FPID/PD-PSO). Adaptive neural networks are deployed to schedule PID/PD gains, the improved back-propagation algorithm is used to update the weights of the neural network. Then, an effective control approach based on adaptive PID Fuzzy logic and Particle Swarm Optimization (PSO) algorithm has been applied. PSO algorithm is introduced to adjust the scaling factors for improving the convergence speed and production rate. Finally, in order to demonstrate the robustness of the proposed control methods, disturbances in the quadcopter system are added. The results so obtained demonstrate the effectiveness of the proposed control strategy.

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Section: Spiral Trajectory Trackingmentioning

confidence: 84%

“…The control techniques for UAV platforms have witnessed a rapidly expanding research in order to achieve not only autonomous hovering and orientation but also trajectory tracking (Salehfard et. al, 2018, Rendón & Martins, 2017.…”

Section: Introductionmentioning

confidence: 99%

Neural Network and Fuzzy-logic-based Self-tuning PID Control for Quadcopter Path Tracking

Hamidi¹,

Mjahed²,

Kari³

et al. 2019

SIC

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“…The angular speed of the hexarotor with respect to the inertial frame expressed in the frame B is indicated with ω ¼ ½p; q; r� T ∈ R 3 , which can be expressed using Equation (2) in terms of Euler angles [23].…”

Section: Hexarotor Modelmentioning

confidence: 99%

“…The angular speed of the hexarotor with respect to the inertial frame expressed in the frame

B

is indicated with

\boldsymbol{\omega }={[p,q,r]}^{\mathrm{T}}\in {\mathbb{R}}^{3}

, which can be expressed using Equation () in terms of Euler angles [23].

p=\dot{\phi }-\dot{\psi }\mathrm{sin}(\theta ),\,q=\dot{\theta }\mathrm{cos}(\phi )+\dot{\psi }\mathrm{cos}(\theta )\mathrm{sin}(\phi ),\,r=\dot{\psi }\mathrm{cos}(\theta )\mathrm{cos}(\phi )-\dot{\theta }\mathrm{sin}(\phi ).

…”

Section: Hexarotor Modelmentioning

confidence: 99%

“…However, disturbances and uncertainties may still cause substantial performance degradation or even instability. Two appropriate non‐linear approaches to resolve these problems are robust and adaptive controllers, some of which have been proposed based on the sliding mode control method [11–13], backstepping approach [14–16], robust compensation technique [17, 18], non‐linear

{H}_{\infty }

control method [19, 20], immersion and invariance approach [21], disturbance observers [22], and fuzzy logic control approach [23, 24].…”

Section: Introductionmentioning

confidence: 99%

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Robust optimal attitude control for hexarotors with disturbances, uncertainties, and delays

Abdollahi

Salehfard

2022

IET Cyber-Phy Sys Theory & Ap

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A robust optimal attitude controller for hexarotor helicopters is proposed. Compared to the previous research studies on hexarotors, the current study takes account of the influences of non‐linear and coupling dynamics, structured and unstructured uncertainties, external time‐varying disturbances, and input time delays. A linear time‐invariant system is derived for each Euler angle by considering the actual rotational dynamic model as a nominal non‐linear system plus an equivalent perturbation, including non‐linear and coupling dynamics, uncertainties, disturbances, and time delays. Using this approach, a Linear Quadratic Regulation controller is first designed for the nominal linear system of each angle to accomplish the desired tracking performances. Then, a robust compensator based on the robust compensation method is proposed to counteract the effects of the equivalent perturbation on the system. Moreover, the robust attitude tracking property and uniform asymptotical stability of the closed‐loop hexarotor system are proved using Lyapunov stability theory. Several simulations have been performed to demonstrate the effectiveness and robustness of the proposed controller. Finally, experimental results are provided to confirm the robust performance of the proposed controller.

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Adaptive fuzzy global sliding mode control for trajectory tracking of quadrotor UAVs

et al. 2019

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An Optimized Fuzzy-Padé Controller Applied to Attitude Stabilization of a Quadrotor

Cited by 10 publications

References 15 publications

Neural Network and Fuzzy-logic-based Self-tuning PID Control for Quadcopter Path Tracking

Neural Network and Fuzzy-logic-based Self-tuning PID Control for Quadcopter Path Tracking

Robust optimal attitude control for hexarotors with disturbances, uncertainties, and delays

Adaptive fuzzy global sliding mode control for trajectory tracking of quadrotor UAVs

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