A new procedure for discretization and state feedback control of uncertain linear systems

2013 ◽  
Author(s):  
Marcio F. Braga ◽  
Cecilia F. Morais ◽  
Eduardo S. Tognetti ◽  
Ricardo C. L. F. Oliveira ◽  
Pedro L. D. Peres
Keyword(s):  
Feedback Control ◽  
Linear Systems ◽  
State Feedback ◽  
State Feedback Control ◽  
Uncertain Linear Systems

scholarly journals Robust H∞ Switched State-feedback Control of Uncertain Linear Systems

2018 ◽  
Vol 51 (25) ◽  
pp. 67-72 ◽  
Author(s):  
Ivan F.Y. Tello ◽  
Lucas M. Esteves ◽  
Rodrigo Cardim ◽  
Marcelo C.M. Teixeira ◽  
Edvaldo Assunção ◽  
...  
Keyword(s):  
Feedback Control ◽  
Linear Systems ◽  
State Feedback ◽  
State Feedback Control ◽  
Switched State Feedback ◽  
Uncertain Linear Systems

Reliable State Feedback Control Synthesis For Uncertain Linear Systems

2008 ◽  
Vol 5 (2) ◽  
pp. 301-308 ◽  
Author(s):  
Guang-Hong Yang ◽  
Jian Liang Wang ◽  
Yeng Chai Soh ◽  
Kok-Yong Lou
Keyword(s):  
Feedback Control ◽  
Linear Systems ◽  
State Feedback ◽  
State Feedback Control ◽  
Control Synthesis ◽  
Uncertain Linear Systems

Optimal Sampled–Data State Feedback Control of Linear Systems

2014 ◽  
Vol 47 (3) ◽  
pp. 5556-5561 ◽  
Author(s):  
Matheus Souza ◽  
Gabriela W.G. Vital ◽  
José C. Geromel
Keyword(s):  
Feedback Control ◽  
Linear Systems ◽  
State Feedback ◽  
State Feedback Control ◽  
Sampled Data ◽  
Control Of Linear Systems

scholarly journals Robust H ∞ state-feedback control for linear systems

2017 ◽  
Vol 473 (2200) ◽  
pp. 20160934 ◽  
Author(s):  
Hao Chen ◽  
Zhenzhen Zhang ◽  
Huazhang Wang
Keyword(s):  
Feedback Control ◽  
Linear Systems ◽  
Control Algorithm ◽  
State Feedback ◽  
Convex Combination ◽  
State Feedback Control ◽  
Parameter Uncertainties ◽  
Globally Asymptotically Stable ◽  
Loop Control ◽  
Control Approach

This paper investigates the problem of robust H ∞ control for linear systems. First, the state-feedback closed-loop control algorithm is designed. Second, by employing the geometric progression theory, a modified augmented Lyapunov–Krasovskii functional (LKF) with the geometric integral interval is established. Then, parameter uncertainties and the derivative of the delay are flexibly described by introducing the convex combination skill. This technique can eliminate the unnecessary enlargement of the LKF derivative estimation, which gives less conservatism. In addition, the designed controller can ensure that the linear systems are globally asymptotically stable with a guaranteed H ∞ performance in the presence of a disturbance input and parameter uncertainties. A liquid monopropellant rocket motor with a pressure feeding system is evaluated in a simulation example. It shows that this proposed state-feedback control approach achieves the expected results for linear systems in the sense of the prescribed H ∞ performance.

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