backstepping control
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Author(s):  
Nguyen Thai Duong ◽  
Nguyen Quang Duy

<span>Adaptive backstepping control based on disturbance observer and neural network for ship nonlinear active fin system is proposed. One disturbance observer is given to observe the disturbances of the system, by this way, the response time is shorten and the negative impact of disturbance and uncertain elements of the system is reduced. In addition, radial basic function neural network (RBFNN) is proposed to approach the unknown elements in the ship nonlinear active fin system, therefor the system can obtain good roll reduction effectiveness and overcome the uncertainties of the model, the designed controller can maintain the ship roll angle at desired value. Finally, the simulation results are given for a supply vessel to verify the successfulness of the proposed controller.</span>


Author(s):  
Asma Charaabi ◽  
Abdelaziz Zaidi ◽  
Oscar Barambones ◽  
Nadia Zanzouri

2022 ◽  
Vol 32 (2) ◽  
pp. 923-936
Author(s):  
Wei-Lung Mao ◽  
Yu-Ying Chiu ◽  
Chao-Ting Chu ◽  
Bing-Hong Lin ◽  
Jian-Jie Hung

Author(s):  
H Demirel ◽  
A Doğrul ◽  
S Sezen ◽  
F Alarçin

A backstepping control design procedure for nonlinear fin roll control of a trawler is presented in this paper. A roll equation consisting of linear and nonlinear damping and restoring moment on the roll response is expressed. Flow analyses are carried out for a scaled model of trawler type fishing vessel including fin stabilizers on both sides of the hull. The fin stabilizer geometry is chosen as NACA 0015 foil section which is widely used in the literature. The flow analyses are performed by using a commercial computational fluid dynamics (CFD) software based on finite volume method. The flow problem is modeled in a 3-dimensional manner while the flow is considered as steady, incompressible and fully turbulent. The numerical model consists of the ship wetted surface and the fin stabilizer in order to investigate the hull-fin interaction. Non-dimensional lift coefficients of the fin stabilizer for different angles of attack are gained. Both controlled and uncontrolled roll motions are examined and simulated in time domain for the maximum lift coefficient. Backstepping controller for roll motion has given a rapid and precise result.


Author(s):  
Zoubir Zeghdi ◽  
Linda Barazane ◽  
Youcef Bekakra ◽  
Abdelkader Larabi

In this paper, an improved Backstepping control based on a recent optimization method called Ant Lion Optimizer (ALO) algorithm for a Doubly Fed Induction Generator (DFIG) driven by a wind turbine is designed and presented. ALO algorithm is applied for obtaining optimum Backstepping control (BCS) parameters that are able to make the drive more robust with a faster dynamic response, higher accuracy and steady performance. The fitness function of the ALO algorithm to be minimized is designed using some indexes criterion like Integral Time Absolute Error (ITAE) and Integral Time Square Error (ITSE). Simulation tests are carried out in MATLAB/Simulink environment to validate the effectiveness of the proposed BCS-ALO and compared to the conventional BCS control. The results prove that the objectives of this paper were accomplished in terms of robustness, better dynamic efficiency, reduced harmonic distortion, minimization of stator powers ripples and performing well in solving the problem of uncertainty of the model parameter.


Processes ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 2209
Author(s):  
Gexin Chen ◽  
Huilong Liu ◽  
Pengshuo Jia ◽  
Gengting Qiu ◽  
Haohui Yu ◽  
...  

A nonlinear adaptive backstepping control method was proposed to address the system parameter uncertainty problem in the position control process of an electro-hydraulic servo closed-pump control system. This control strategy fully considers the parameter uncertainty of the nonlinear system and establishes the adaptive rate of the uncertain parameter to adjust the parameter disturbance online in real time, thereby improving the accuracy and robustness of the control system. A pump control system experiment platform was used to verify the feasibility of the controller. The experimental results showed that the proposed control strategy provided a good control effect. The pump control system can be controlled with high precision, with a steady-state control accuracy of ±0.02 mm, which serves as a good foundation for the engineering application and promotion of the pump control system.


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