A High Precision Adaptive Back-Stepping Control Method for Morphing Aircraft Based on RBFNN Method

To overcome the uncertainties of the nonlinear model of a morphing aircraft, this paper presents a high-precision adaptive back-stepping control method based on the radial basis function neural network (RBFNN). Firstly, based on the analysis of static and dynamic aerodynamic parameters of the morphing aircraft, its nonlinear control law is designed by using the conventional back-stepping method. The RBFNN is introduced to approximate online the uncertain terms of the nonlinear control law so as to improve its robustness. The robust term is designed to eliminate the approximation error caused by the RBFNN. Secondly, the tracking differentiator is designed through solving the virtual control variables, thus solving the "differential expansion" problem existing in the traditional back-stepping method. The Lyapunov stability analysis proves that our method can ensure that the tracking error of a closed-loop system converges finally and that its signals are uniformly bounded. Finally, the digital simulation model of the morphing aircraft is established with the MATLAB/Simulink; our method is compared with the conventional back-stepping control method. The simulation results show that our method has a higher control precision and stronger robustness.

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Synthetic Jet Actuator-Based Aircraft Tracking Using a Continuous Robust Nonlinear Control Strategy

International Journal of Aerospace Engineering ◽

10.1155/2017/4934281 ◽

2017 ◽

Vol 2017 ◽

pp. 1-13

Author(s):

N. Ramos-Pedroza ◽

W. MacKunis ◽

M. Reyhanoglu

Keyword(s):

Nonlinear Control ◽

Trajectory Tracking ◽

Parameter Uncertainty ◽

Tracking Error ◽

Synthetic Jet ◽

Parameter Estimates ◽

Control Law ◽

Robust Nonlinear Control ◽

Trajectory Tracking Control ◽

Nonlinear Control Law

A robust nonlinear control law that achieves trajectory tracking control for unmanned aerial vehicles (UAVs) equipped with synthetic jet actuators (SJAs) is presented in this paper. A key challenge in the control design is that the dynamic characteristics of SJAs are nonlinear and contain parametric uncertainty. The challenge resulting from the uncertain SJA actuator parameters is mitigated via innovative algebraic manipulation in the tracking error system derivation along with a robust nonlinear control law employing constant SJA parameter estimates. A key contribution of the paper is a rigorous analysis of the range of SJA actuator parameter uncertainty within which asymptotic UAV trajectory tracking can be achieved. A rigorous stability analysis is carried out to prove semiglobal asymptotic trajectory tracking. Detailed simulation results are included to illustrate the effectiveness of the proposed control law in the presence of wind gusts and varying levels of SJA actuator parameter uncertainty.

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Nonlinear control of chaotic systems:A switching manifold approach

Discrete Dynamics in Nature and Society ◽

10.1155/s1026022600000248 ◽

2000 ◽

Vol 4 (4) ◽

pp. 257-267 ◽

Cited By ~ 3

Author(s):

Jin-Qing Fang ◽

Yiguang Hong ◽

Huashu Qin ◽

Guanrong Chen

Keyword(s):

Nonlinear Control ◽

Chaotic Systems ◽

Lorenz System ◽

Control Method ◽

Initial Conditions ◽

Design Strategy ◽

Control Law ◽

The Lorenz System ◽

Bang Bang Control ◽

Nonlinear Control Law

In this paper, a switching manifold approach is developed for nonlinear feed-back control of chaotic systems. The design strategy is straightforward, and the nonlinear control law is the simple bang–bang control. Yet, this control method is very effective; for instance, several desired equilibria can be stabilized by using one control law with different initial conditions. Its effectiveness is verified by both theoretical analysis and numerical simulations. The Lorenz system simulation is shown for the purpose of illustration.

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Robust Synchronization of Delayed Chaotic FitzHugh-Nagumo Neurons under External Electrical Stimulation

Computational and Mathematical Methods in Medicine ◽

10.1155/2012/230980 ◽

2012 ◽

Vol 2012 ◽

pp. 1-11 ◽

Cited By ~ 15

Author(s):

Muhammad Rehan ◽

Keum-Shik Hong

Keyword(s):

Electrical Stimulation ◽

Nonlinear Control ◽

Control Law ◽

Input Control ◽

Control Schemes ◽

Multiple Input ◽

Cognitive Diseases ◽

Single Input ◽

Error Dynamics ◽

Nonlinear Control Law

Synchronization of chaotic neurons under external electrical stimulation (EES) is studied in order to understand information processing in the brain and to improve the methodologies employed in the treatment of cognitive diseases. This paper investigates the dynamics of uncertain coupled chaotic delayed FitzHugh-Nagumo (FHN) neurons under EES for incorporated parametric variations. A global nonlinear control law for synchronization of delayed neurons with known parameters is developed. Based on local and global Lipschitz conditions, knowledge of the bounds on the neuronal states, the Lyapunov-Krasovskii functional, and theL2gain reduction, a less conservative local robust nonlinear control law is formulated to address the problem of robust asymptotic synchronization of delayed FHN neurons under parametric uncertainties. The proposed local control law guarantees both robust stability and robust performance and provides theL2bound for uncertainty rejection in the synchronization error dynamics. Separate conditions for single-input and multiple-input control schemes for synchronization of a wide class of FHN systems are provided. The results of the proposed techniques are verified through numerical simulations.

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Active disturbance rejection control of servo platform using improved nonlinear control law

Fifth International Conference on Intelligent Control and Information Processing ◽

10.1109/icicip.2014.7010348 ◽

2014 ◽

Author(s):

Hang Zhang

Keyword(s):

Nonlinear Control ◽

Disturbance Rejection ◽

Control Law ◽

Active Disturbance Rejection Control ◽

Active Disturbance Rejection ◽

Disturbance Rejection Control ◽

Nonlinear Control Law

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Finite-Time Switching Control of Nonholonomic Mobile Robots for Moving Target Tracking Based on Polar Coordinates

Complexity ◽

10.1155/2018/7360643 ◽

2018 ◽

Vol 2018 ◽

pp. 1-9 ◽

Cited By ~ 7

Author(s):

Hua Chen ◽

Shen Xu ◽

Lulu Chu ◽

Fei Tong ◽

Lei Chen

Keyword(s):

Mobile Robots ◽

Finite Time ◽

Control Method ◽

Tracking Error ◽

Switching Control ◽

Polar Coordinates ◽

Control Law ◽

Moving Target ◽

Nonholonomic Mobile Robots ◽

Time Switching

In this paper, finite-time tracking problem of nonholonomic mobile robots for a moving target is considered. First of all, polar coordinates are used to characterize the distance and azimuth between the moving target and the robot. Then, based on the distance and azimuth transported from the sensor installed on the robot, a finite-time tracking control law is designed for the nonholonomic mobile robot by the switching control method. Rigorous proof shows that the tracking error converges to zero in a finite time. Numerical simulation demonstrates the effectiveness of the proposed control method.

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