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

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.

Robust Nonlinear Control of Parametric Uncertain Systems With Unknown Friction and Its Application to a Pneumatic Control Valve

1997 ◽  
Vol 122 (2) ◽  
pp. 257-262 ◽  
Author(s):  
Tielong Shen ◽  
Katsutoshi Tamura ◽  
Hiroshi Kaminaga ◽  
Noriaki Henmi ◽  
Toru Nakazawa
Keyword(s):  
Nonlinear Control ◽  
Parameter Uncertainty ◽  
Uncertain Systems ◽  
Direct Method ◽  
Tracking Error ◽  
Control Valve ◽  
Robust Nonlinear Control ◽  
Pneumatic Control ◽  
Control Approach ◽  
Second Order Systems

A robust nonlinear control approach is presented for parametric uncertain systems with unknown friction. First- and second-order systems are considered, respectively. A model reference controller is developed such that the tracking error is bounded and converges to zero in the presence of the parameter uncertainty and the unknown friction. Then, the controller is extended to general case with any order. To design the controller, exact friction force is not required, only the upper bound for the level. Lyapunov’s direct method is used to prove robust global convergence of the tracking error. Finally, experimental results are given by applying the proposed controller to a pneumatic control valve. [S0022-0434(00)01802-5]

Experimental application of robust nonlinear control law to pH control

1994 ◽  
Vol 49 (2) ◽  
pp. 199-207 ◽  
Author(s):  
Y.H. Wong ◽  
P.R. Krishnaswamy ◽  
W.K. Teo ◽  
B.D. Kulkarni ◽  
P.B. Deshpande
Keyword(s):  
Nonlinear Control ◽  
Ph Control ◽  
Control Law ◽  
Robust Nonlinear Control ◽  
Experimental Application ◽  
Nonlinear Control Law

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

2020 ◽  
Vol 38 (3) ◽  
pp. 540-549
Author(s):  
Fuxiang Qiao ◽  
Jingping Shi ◽  
Weiguo Zhang ◽  
Yongxi Lyu ◽  
Xiaobo Qu
Keyword(s):  
Nonlinear Control ◽  
High Precision ◽  
Control Method ◽  
Digital Simulation ◽  
Tracking Error ◽  
Approximation Error ◽  
Control Law ◽  
Morphing Aircraft ◽  
Back Stepping Control ◽  
Nonlinear Control Law

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.

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

2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
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.

Analysis of a Nonlinear Control Law with Cubic Nonlinearity

2021 ◽  
Author(s):  
Melnikov Vitaly ◽  
Melnikov Gennady ◽  
Dudarenko Natalia
Keyword(s):  
Nonlinear Control ◽  
Control Law ◽  
Cubic Nonlinearity ◽  
Nonlinear Control Law
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