Study of time delay compensation in multivariable systems with uncertainties: FSP/MPC

Author(s):  
Ernesto Estremera ◽  
Irina Bausa ◽  
Ania Cervantes ◽  
Reinel Aguedo
2015 ◽  
Vol 135 (7) ◽  
pp. 755-764 ◽  
Author(s):  
Shuhei Shimizu ◽  
Yoshiki Ohno ◽  
Takahiro Nozaki ◽  
Kouhei Ohnishi

2014 ◽  
Vol 2014 ◽  
pp. 1-8
Author(s):  
Jie Jiang ◽  
Changlin Ma

In networked control systems with multi-step delay, long time-delay causes vacant sampling and controller design difficulty. In order to solve the above problems, comprehensive control methods are proposed in this paper. Time-delay compensation control and linear-quadratic-Guassian (LQG) optimal control are adopted and the systems switch different controllers between two different states. LQG optimal controller is used with probability1-αin normal state, which is shown to render the systems mean square exponentially stable. Time-delay compensation controller is used with probabilityαin abnormal state to compensate vacant sampling and long time-delay. In addition, a buffer window is established at the actuator of the systems to store some history control inputs which are used to estimate the control state of present sampling period under the vacant sampling cases. The comprehensive control methods simplify control design which is easier to be implemented in engineering. The performance of the systems is also improved. Simulation results verify the validity of the proposed theory.


2018 ◽  
Vol 14 (11) ◽  
pp. 155014771881069 ◽  
Author(s):  
Ying He ◽  
Xiafu Peng ◽  
Xiaoli Zhang ◽  
Xiaoqiang Hu

Estimation and compensation for hull deformation is an indispensable step for the ship to establish a unified space attitude. The existing hull deformation measurement methods are dependent on the pre-established deformation model, and an inaccurate deformation model will reduce the deformation estimation accuracy. To solve this problem, a hull deformation estimation method without deformation model is proposed in this article, which utilizes the neural network to fit the hull deformation. To train the neural network online, connection weights of the neural network are regarded as system state variables which can be estimated by the Unscented Kalman Filter. Simultaneously, considering the time delay problem of inertial data, a time delay compensation method based on the quaternion attitude matrix is proposed. The simulation results show that the proposed method can obtain high estimation accuracy without any deformation model even when the inertial data are asynchronous.


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