Application research of self-adapting output feedback controller based on RBF neural network on WECS

2004 ◽  
Author(s):  
Mengli ◽  
Xingjia Yao
Keyword(s):  
Neural Network ◽  
Output Feedback ◽  
Rbf Neural Network ◽  
Feedback Controller ◽  
Application Research ◽  
Output Feedback Controller

scholarly journals Adaptive Filtering Backstepping for Ships Steering Control without Velocity Measurements and with Input Constraints

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Guoqing Xia ◽  
Huiyong Wu ◽  
Xingchao Shao
Keyword(s):  
Adaptive Filtering ◽  
Output Feedback ◽  
Rbf Neural Network ◽  
Uniform Boundedness ◽  
High Gain ◽  
Feedback Controller ◽  
Input Constraints ◽  
Steering Control ◽  
Output Feedback Controller ◽  
Unknown Disturbances

We consider the problem of course tracking for ships with uncertainties and unknown external disturbances, in the presence of input magnitude and rate saturation. The combination of approximation-based adaptive technique and radial basis function (RBF) neural network allows us to handle the unknown disturbances from the environment and uncertain ship dynamics. By employing the adaptive filtering backstepping, the full-state feedback controller is first derived. Then the output feedback controller is designed with the unmeasurable state estimated by using a high-gain observer. In order to cope with the input constraints, an auxiliary system is introduced to the output feedback controller, and the semiglobal uniform boundedness of the modified control solution is verified. Simulation results are presented for the course tracking of a cargo ship, which are demonstrative of the excellent performance of the proposed controller.

Robust H2 Output Feedback Controller Design for Damping Power System Oscillations

2017 ◽  
Vol 6 (10) ◽  
pp. 8
Author(s):  
Kho Hie Kwee ◽  
Hardiansyah .
Keyword(s):  
Power System ◽  
Output Feedback ◽  
Controller Design ◽  
Sufficient Conditions ◽  
Feedback Controller ◽  
Linear Matrix ◽  
Parameter Uncertainties ◽  
Worst Case ◽  
Output Feedback Controller ◽  
Power System Oscillations

This paper addresses the design problem of robust H2 output feedback controller design for damping power system oscillations. Sufficient conditions for the existence of output feedback controllers with norm-bounded parameter uncertainties are given in terms of linear matrix inequalities (LMIs). Furthermore, a convex optimization problem with LMI constraints is formulated to design the output feedback controller which minimizes an upper bound on the worst-case H2 norm for a range of admissible plant perturbations. The technique is illustrated with applications to the design of stabilizer for a single-machine infinite-bus (SMIB) power system. The LMI based control ensures adequate damping for widely varying system operating.

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