Design of state-feedback control for polynomial systems with quadratic performance criterion and control input constraints

2018 ◽  
Vol 117 ◽  
pp. 53-59 ◽  
Author(s):  
Tanagorn Jennawasin ◽  
David Banjerdpongchai
Keyword(s):  
Feedback Control ◽  
State Feedback ◽  
Polynomial Systems ◽  
Performance Criterion ◽  
State Feedback Control ◽  
Control Input ◽  
Input Constraints ◽  
Quadratic Performance ◽  
And Control

Distributed LPV State-Feedback Control Under Control Input Saturation

2017 ◽  
Vol 62 (5) ◽  
pp. 2450-2456 ◽  
Author(s):  
Azita Dabiri ◽  
Balazs Kulcsar ◽  
Hakan Koroglu
Keyword(s):  
Feedback Control ◽  
State Feedback ◽  
Input Saturation ◽  
State Feedback Control ◽  
Control Input

scholarly journals Optimisation of dynamic quantisation and control for quantised state feedback control system

2020 ◽  
Vol 2020 (7) ◽  
pp. 251-258
Author(s):  
Than Zaw Soe ◽  
Tadanao Zanma ◽  
Atsuki Tokunaga ◽  
Kenta Koiwa ◽  
Kang Zhi Liu
Keyword(s):  
Control System ◽  
Feedback Control ◽  
State Feedback ◽  
State Feedback Control ◽  
Feedback Control System ◽  
And Control

scholarly journals Model Based Robust Predictive Control of Ship Roll/Yaw Motions with Input Constraints

2020 ◽  
Vol 10 (10) ◽  
pp. 3377
Author(s):  
Zhongjia Jin ◽  
Sheng Liu ◽  
Lincheng Jin ◽  
Wei Chen ◽  
Weilin Yang
Keyword(s):  
Predictive Control ◽  
State Feedback ◽  
State Feedback Control ◽  
Linear Matrix ◽  
Control Input ◽  
Input Constraints ◽  
Control Performance ◽  
Parameter Uncertainties ◽  
Yaw Control ◽  
Control Gain

A robust H∞-type state feedback model predictive control (H∞-SFMPC) with input constraints is proposed to optimize the control performance during the ship sailing. Specifically, the approach employed in this paper is able to optimize the closed-loop performance with respect to an H∞-type cost function which predicts the system performance based on the actual model instead of the ideal model. As a result, the effect caused by disturbances is attenuated. The state feedback control gain for the control input of the rudder-fin joint roll/yaw control system is obtained by solving a constrained convex optimization problem in terms of linear matrix inequalities. Simulations are carried out, which reveal that the proposed approach has outstanding control performance. Furthermore, it is found that the approach also has significant robustness with respect to parameter uncertainties.

scholarly journals The Parameter Variation Problem in State Feedback Control Systems

1965 ◽  
Vol 87 (1) ◽  
pp. 120-124 ◽  
Author(s):  
W. R. Perkins ◽  
J. B. Cruz
Keyword(s):  
Feedback Control ◽  
State Feedback ◽  
Parameter Variation ◽  
Open Loop ◽  
State Feedback Control ◽  
Optimal Feedback Control ◽  
Variation Problem ◽  
Quadratic Performance ◽  
New Interpretation ◽  
Low Sensitivity

The plant-parameter variation problem in multivariable linear systems described by state-vector equations is formulated using a new sensitivity measure. This formulation involves a direct comparison of open-loop and state-feedback performance in the presence of parameter variations and provides a basis for guaranteeing the superiority of the feedback design. Results are obtained for both continuous and discrete multi-input, multi-output systems. Furthermore, it is shown for single-input, multi-output plants that a low-sensitivity design is also an optimal feedback-control design with respect to a quadratic performance index. This provides a new interpretation of a similar result previously obtained by Kalman.

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