Non-linear stochastic controllers for semiactive and regenerative systems with guaranteed quadratic performance bounds—Part 1: State feedback control

2007 ◽  
Vol 14 (8) ◽  
pp. 1101-1120 ◽  
Author(s):  
J. T. Scruggs ◽  
A. A. Taflanidis ◽  
W. D. Iwan
Keyword(s):  
Feedback Control ◽  
State Feedback ◽  
State Feedback Control ◽  
Performance Bounds ◽  
Non Linear ◽  
Quadratic Performance ◽  
Regenerative Systems

High‐precision state feedback control systems for linear and non‐linear plants

Kybernetes ◽  
2008 ◽  
Vol 37 (5) ◽  
pp. 608-622
Author(s):  
Adam Łozowicki ◽  
Teresa Łozowicka Stupnicka ◽  
Dorota Łozowicka
Keyword(s):  
Feedback Control ◽  
Control Systems ◽  
High Precision ◽  
State Feedback ◽  
State Feedback Control ◽  
Non Linear ◽  
Feedback Control Systems

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.

NN approach to state-feedback control of high-order non-linear time-delay systems with time-varying control coefficient

2016 ◽  
Vol 40 (1) ◽  
pp. 163-170 ◽  
Author(s):  
Min Huifang ◽  
Duan Na
Keyword(s):  
Neural Network ◽  
Feedback Control ◽  
State Feedback ◽  
Linear Time ◽  
High Order ◽  
State Feedback Control ◽  
Delay Systems ◽  
Time Varying ◽  
Control Coefficient ◽  
Non Linear

This paper considers the adaptive state-feedback control problem for a class of high-order non-linear systems with unknown control coefficient and time delays. By applying the neural network approximation method and the Nussbaum function approach, the restrictions on non-linear functions and the conditions on the time-varying control coefficient are largely relaxed. In addition, an adaptive neural network state-feedback controller with only one adaptive parameter is successfully constructed by introducing proper Lyapunov–Krasovskii functionals and using the backstepping technique. The proposed scheme guarantees the closed-loop system to be semi-globally uniformly ultimately bounded. Finally, a simulation example demonstrates the effectiveness of the controller.

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