Flapping Wing Micro Aerial Vehicle Attitude Control with Fuzzy Sliding Mode Controller Based on RBF Neural Network

2012 ◽  
Vol 443-444 ◽  
pp. 177-182
Author(s):  
Sheng Bin Hu ◽  
Wen Hua Lu ◽  
Min Xun Lu
Keyword(s):  
Neural Network ◽  
Sliding Mode Control ◽  
Attitude Control ◽  
Sliding Mode ◽  
Flapping Wing ◽  
Micro Aerial Vehicle ◽  
Mode Control ◽  
Attitude Tracking ◽  
Aerial Vehicle ◽  
Fuzzy Sliding Mode

A adaptive fuzzy Sliding Mode Control (SMC) scheme based on Radial Basis Function Neural Network (RBFNN) for attitude tracking control of Flapping Wing Micro Aerial Vehicle (FWMAV) is proposed in this paper. A RBFNN is used to compute the equivalent control of sliding mode control, An adaptive algorithm is used for weight adaptation of the RBFNN and A Lyapunov function is selected for the design of the SMC. The simulation results of FWMAV demonstrate that the control scheme is effective.

Attitude Control of Flapping Wing Micro Aerial Vehicle Based on Double Fuzzy Sliding Mode Control

2012 ◽  
Vol 468-471 ◽  
pp. 704-707
Author(s):  
Sheng Bin Hu ◽  
Wen Hua Lu ◽  
Zhi Yi Chen ◽  
Lei Lei ◽  
Yi Xuan Zhang
Keyword(s):  
Sliding Mode Control ◽  
Attitude Control ◽  
Fuzzy Controller ◽  
Sliding Mode ◽  
Micro Aerial Vehicle ◽  
Fuzzy Sliding Mode Control ◽  
Mode Control ◽  
Control Scheme ◽  
Aerial Vehicle ◽  
Fuzzy Sliding Mode

An adaptive Double Fuzzy Sliding Mode Control scheme for attitude control of Flapping Wing Micro Aerial Vehicle is proposed in this paper. Based on the feedback linearization technique, a sliding mode controller is designed. To faster response speed, a fuzzy controller is designed to adaptively tune the slope of sliding mode surface. To reduce the chattering, another fuzzy controller is designed to adaptively tune the switch part of sliding mode control. The system stability is proved by Lyapunov principle. Simulation results show that the proposed control scheme is effective.

Fuzzy Sliding Mode Control for Attitude of Flapping Wing Micro Aerial Vehicle Based on Variable Rate Reaching Law

2012 ◽  
Vol 178-181 ◽  
pp. 2801-2804
Author(s):  
Sheng Bin Hu ◽  
Wen Hua Lu ◽  
Zhi Yi Chen ◽  
Lei Lei ◽  
Yi Xuan Zhang
Keyword(s):  
Attitude Control ◽  
Sliding Mode ◽  
Flapping Wing ◽  
Variable Rate ◽  
Micro Aerial Vehicle ◽  
Fuzzy Sliding Mode Control ◽  
Reaching Law ◽  
Control Scheme ◽  
Aerial Vehicle ◽  
Fuzzy Sliding Mode

A fuzzy sliding mode control scheme based on variable rate reaching law for attitude control of flapping wing micro aerial vehicle is proposed in this paper. Based on the feedback linearization technique, a sliding mode controller is designed. To faster response speed, a fuzzy controller is designed to adaptively tune the slope of sliding mode surface. To reduce the chattering, the variable rate reaching law is proposed. The variable rate reaching law is composed of the distance from current point to sliding mode surface in phase plane. The simulation studies for attitude control of a flapping wing micro aerial vehicle have been carried out. Simulation results show that the proposed control scheme is effective.

Fast Terminal Fuzzy Sliding Mode Control for Attitude of Flapping Wing Micro Aerial Vehicle

2013 ◽  
Vol 427-429 ◽  
pp. 1179-1182
Author(s):  
Sheng Bin Hu ◽  
Jin Yuan Xu ◽  
Xuan Wu ◽  
Chi Zhang ◽  
Yi Hao He
Keyword(s):  
Sliding Mode ◽  
Flapping Wing ◽  
Sliding Mode Controller ◽  
Terminal Sliding Mode ◽  
Micro Aerial Vehicle ◽  
Fuzzy Sliding Mode Control ◽  
Control Scheme ◽  
Fast Terminal Sliding Mode ◽  
Aerial Vehicle ◽  
Fuzzy Sliding Mode

A fast terminal fuzzy sliding mode control scheme for the attitude of flapping wing micro aerial vehicle is proposed in this paper. Based on the feedback linearization technique, a fast terminal sliding mode controller is designed. To diminish the chattering in the control input, a fuzzy controller is designed to adjust the generalized gain of fast terminal fuzzy sliding mode controller according to fast terminal sliding mode surface. The stability of the control algorithm is verified by using Lyapunov theory. Simulation results show that the proposed control scheme is effective.

scholarly journals Adaptive Neural Network Sliding Mode Control for Quad Tilt Rotor Aircraft

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Yanchao Yin ◽  
Hongwei Niu ◽  
Xiaobao Liu
Keyword(s):  
Neural Network ◽  
Sliding Mode Control ◽  
Sliding Mode ◽  
Approximation Error ◽  
Model Parameters ◽  
Control Law ◽  
The Novel ◽  
Adaptive Neural Network ◽  
Mode Control ◽  
Attitude Tracking

A novel neural network sliding mode control based on multicommunity bidirectional drive collaborative search algorithm (M-CBDCS) is proposed to design a flight controller for performing the attitude tracking control of a quad tilt rotors aircraft (QTRA). Firstly, the attitude dynamic model of the QTRA concerning propeller tension, channel arm, and moment of inertia is formulated, and the equivalent sliding mode control law is stated. Secondly, an adaptive control algorithm is presented to eliminate the approximation error, where a radial basis function (RBF) neural network is used to online regulate the equivalent sliding mode control law, and the novel M-CBDCS algorithm is developed to uniformly update the unknown neural network weights and essential model parameters adaptively. The nonlinear approximation error is obtained and serves as a novel leakage term in the adaptations to guarantee the sliding surface convergence and eliminate the chattering phenomenon, which benefit the overall attitude control performance for QTRA. Finally, the appropriate comparisons among the novel adaptive neural network sliding mode control, the classical neural network sliding mode control, and the dynamic inverse PID control are examined, and comparative simulations are included to verify the efficacy of the proposed control method.

L1 neural network adaptive fault-tolerant controller for unmanned aerial vehicle attitude control system

2021 ◽  
pp. 095441002098409
Author(s):  
Yan Zhou ◽  
Huiying Liu ◽  
Huijuan Guo ◽  
Jing Li
Keyword(s):  
Neural Network ◽  
Control System ◽  
Unmanned Aerial Vehicle ◽  
Attitude Control ◽  
Fault Tolerant ◽  
Sliding Mode ◽  
Attitude Control System ◽  
Attitude Tracking ◽  
Nonlinear Uncertainties ◽  
Aerial Vehicle

In this article, a L1 neural network adaptive fault-tolerant controller is exploited for an unmanned aerial vehicle attitude control system in presence of nonlinear uncertainties, such as system uncertainties, external disturbances, and actuator faults. A nonlinear dynamic inversion controller with sliding mode control law is designed as the outer-loop controller to track the attitude angles quickly and accurately which reduces dependence on model accuracy. A L1 neural network adaptive controller of the inner loop is introduced to compensate the nonlinear uncertainties and have a good attitude tracking. The radial basis function neural network technique is introduced to approximate a lumped nonlinear uncertainty and guarantee the stability and transient performance of the closed-loop system, instead of converting it to a half-time linear system by the parametric linearization method. Simulation results demonstrate the effectiveness of the proposed controller.

scholarly journals Nonsingular Integral Sliding Mode Attitude Control for Rigid-Flexible Coupled Spacecraft with High-Inertia Rotating Appendages

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Gaowang Zhang ◽  
Xueqin Chen ◽  
Ruichen Xi ◽  
Huayi Li
Keyword(s):  
Sliding Mode Control ◽  
Control Problem ◽  
Attitude Control ◽  
Sliding Mode ◽  
Control Law ◽  
Solar Panels ◽  
Integral Sliding Mode ◽  
Complex Control ◽  
Mode Control ◽  
Attitude Tracking

This study addresses the challenge of attitude tracking control for a rigid-flexible spacecraft with high-inertia rotating appendages. The Lagrange method was used to establish the kinematic and dynamic models of the spacecraft. The translation and rotation of the spacecraft, vibrations of solar panels, and imbalance caused by the rotating appendages, which cause a complex control problem, were considered. To address the complex control problem, a novel, fast nonsingular integral sliding mode control method is proposed to perform the attitude tracking function of spacecraft. A sliding mode control law was established for the high-inertia appendages to maintain an appropriate angular velocity during rotation. Finally, the effectiveness of the proposed attitude control law was verified by numerical simulations for a spacecraft with high-inertia rotating appendages and symmetrical flexible solar panels.

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