2015
DOI: 10.1016/j.isatra.2015.10.011
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An indirect adaptive neural control of a visual-based quadrotor robot for pursuing a moving target

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Cited by 46 publications
(15 citation statements)
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“…Another way for neural adapting is based on the Jacobian information, the sensitivity of the system output to each control input ∂y/∂u. Shirzadeh et al [61] proposed a control for a quadrotor type aerial robot that is in pursuit of a mov-ing target. One feed-forward model is used for identification of the Jacobian information and the second model is designed for the generation of the control signal.…”
Section: Neural Feedback Controlmentioning
confidence: 99%
“…Another way for neural adapting is based on the Jacobian information, the sensitivity of the system output to each control input ∂y/∂u. Shirzadeh et al [61] proposed a control for a quadrotor type aerial robot that is in pursuit of a mov-ing target. One feed-forward model is used for identification of the Jacobian information and the second model is designed for the generation of the control signal.…”
Section: Neural Feedback Controlmentioning
confidence: 99%
“…where d , together with P d is selected as the designated trajectory, whereas the desired angles d and d , being treated as the control inputs for translational subsystem, can be solved by equations (16) and (18), where 4À6 will be given as equation 43in subsequent analysis. Therefore, the three equations (10) to (12) contains only three unknown factors, Figure 2.…”
Section: Control Schemementioning
confidence: 99%
“…9 adopted an extended state observer to estimate the state and the aerodynamic disturbances, which is considered in both the attitude and trajectory control. Others, such as H, 10,11 feedback control, 12,13 intelligent control, 1416 and hybrid strategies 1522 have been attempted for the flight robust control of quadrotor to improve the performance. Nevertheless, more attentions should be devoted to the smooth control inputs generated by controller, which is essential for the stability and reliability of the controlled system.…”
Section: Introductionmentioning
confidence: 99%
“…However, the above-mentioned control synchronization study on the exciters is only in the linear vibration system, the control synchronization study of the exciters in the nonlinear vibration system have barely been studied. The sliding mode control combined with radial basis neural network approximation can suppress the system's chattering and make the system's response more stable, which is very suitable for control of nonlinear systems [34]- [36]. Motivated by the above observations, this paper establishes an RBFN-AGSMA controller for the synchronization problem of two homodromy exciters in nonlinear vibration systems.…”
Section: Introductionmentioning
confidence: 95%