scholarly journals Data-Driven Model-Free Adaptive Attitude Control Approach for Launch Vehicle With Virtual Reference Feedback Parameters Tuning Method

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 54106-54116 ◽  
Author(s):  
Li Duan ◽  
Zhongsheng Hou ◽  
Xian Yu ◽  
Shangtai Jin ◽  
Kunfeng Lu
Keyword(s):  
Attitude Control ◽  
Launch Vehicle ◽  
Data Driven ◽  
Virtual Reference ◽  
Control Approach ◽  
Tuning Method ◽  
Model Free ◽  
Parameters Tuning

Simple model-free attitude control design for flexible spacecraft with prescribed performance

2018 ◽  
Vol 233 (8) ◽  
pp. 2760-2771 ◽  
Author(s):  
Chao Zhang ◽  
Guangfu Ma ◽  
Yanchao Sun ◽  
Chuanjiang Li
Keyword(s):  
Control System ◽  
Attitude Control ◽  
Control Design ◽  
Relevant Information ◽  
Tracking Accuracy ◽  
Attitude Control System ◽  
Prescribed Performance ◽  
Control Approach ◽  
Model Free ◽  
Flexible Vibrations

In this paper, a model-free attitude control approach is proposed for the spacecraft in the presence of external disturbances and flexible vibrations with both complexity and performance concerns. By utilizing prescribed performance and backstepping techniques, the controller is constructed in a simple form without requiring any relevant information of the attitude control system dynamics. Moreover, fuzzy/neural network approximations, observers, or adaptive laws are not adopted into the control design, so that the related problems introduced by these estimation structures can be avoided. Numerical simulations in different cases show that the control system can obtain quick and smooth dynamic process and expected tracking accuracy despite the influence of disturbances and flexible vibrations, which demonstrates the effectiveness of the proposed scheme. Owing to the above good features, it is suitable for practical engineering.

Model Free Adaptive Attitude Control for a Launch Vehicle

2019 ◽  
Author(s):  
Jingbang Liu ◽  
Xian Yu ◽  
Shangtai Jin ◽  
Zhongsheng Hou
Keyword(s):  
Attitude Control ◽  
Launch Vehicle ◽  
Model Free

scholarly journals Data-driven Control of the Activated Sludge Process: IMC plus Feedforward Approach

2016 ◽  
Vol 11 (4) ◽  
pp. 522 ◽  
Author(s):  
Jose David Rojas ◽  
Orlando Arrieta ◽  
Montse Meneses ◽  
Ramon Vilanova
Keyword(s):  
Activated Sludge ◽  
Substrate Concentration ◽  
Internal Model ◽  
Internal Model Control ◽  
Data Driven ◽  
Activated Sludge Process ◽  
Virtual Reference ◽  
Model Free ◽  
Model Control ◽  
Feedforward Controller

<p>In the work presented in this paper, data-driven control is used to tune an Internal Model Control. Despite the fact that it may be contradictory to apply a model-free method to a model-based controller, this methodology has been successfully applied to a Activated Sludge Process (ASP) based wastewater treatment. In addition a feedforward controller over the influent substrate concentration was also computed using the virtual reference feedback tuning and applied to the same wastewater process to see the effect over the dissolved oxygen and the substrate concentration at the effluent.</p>

Virtual Reference Feedback Tuning for Cascade Control Systems

2016 ◽  
Vol 28 (5) ◽  
pp. 739-744 ◽  
Author(s):  
Huy Quang Nguyen ◽  
◽  
Osamu Kaneko ◽  
Yoshihiko Kitazaki ◽  
Keyword(s):  
Control Systems ◽  
Cascade Control ◽  
Data Driven ◽  
Experiment Data ◽  
Feedback Controllers ◽  
Virtual Reference ◽  
Text Data ◽  
Tuning Method ◽  
Data Driven Approach ◽  
The Cost

[abstFig src='/00280005/17.jpg' width='300' text='Data-driven approach to cascade control systems' ] Virtual Reference Feedback Tuning (VRFT), proposed by Campi et al., is an effective data-driven tuning method used in feedback controllers because the desired parameters implemented in the controller are obtained by using only one-shot experiment data. In this paper, we apply VRFT to cascade control systems. We also discuss the meaning of the cost function to be minimized. A numerical example is demonstrated to show an effectiveness and validity of our proposed method.

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