State-multiplicative Retarded Systems - Predictor-based State-feedback and Output-feedback control

2019 ◽  
Author(s):  
Eli Gershon ◽  
Uri Shaked
Keyword(s):  
Feedback Control ◽  
Output Feedback ◽  
State Feedback ◽  
Output Feedback Control ◽  
Retarded Systems

H ∞ Control for Continuous-Time Switched Linear Systems

2010 ◽  
Vol 132 (4) ◽  
Author(s):  
Grace S. Deaecto ◽  
José C. Geromel
Keyword(s):  
Feedback Control ◽  
Linear Systems ◽  
Output Feedback ◽  
Continuous Time ◽  
Design Problem ◽  
State Feedback ◽  
Output Feedback Control ◽  
Control Design ◽  
Linear Matrix ◽  
Switched Linear Systems

This paper deals with the output feedback H∞ control design problem for continuous-time switched linear systems. More specifically, the main goal is to design a switching rule together with a dynamic full order linear controller to satisfy a prespecified H∞ level defined by the L2 gain from the input to the output signal. Initially, the state feedback version of this problem is solved in order to put in evidence the main difficulties we have to face toward the solution of the output feedback control design problem. The results reported in this paper are based on the so called Lyapunov–Metzler inequalities, which express a sufficient condition for switched linear systems global stability. The solution of the previously mentioned output feedback control design problem through a linear matrix inequality based method is the main contribution of the present paper. An academic example borrowed from literature is used for illustration.

scholarly journals Designs of Feedback Controllers for Fluid Flows Based On Model Predictive Control and Regression Analysis

Energies ◽  
2020 ◽  
Vol 13 (6) ◽  
pp. 1325 ◽  
Author(s):  
Yasuo Sasaki ◽  
Daisuke Tsubakino
Keyword(s):  
Regression Analysis ◽  
Feedback Control ◽  
Predictive Control ◽  
Vortex Shedding ◽  
Ridge Regression ◽  
Output Feedback ◽  
State Feedback ◽  
Output Feedback Control ◽  
State Feedback Control ◽  
Control Laws

Complexity of online computation is a drawback of model predictive control (MPC) when applied to the Navier–Stokes equations. To reduce the computational complexity, we propose a method to approximate the MPC with an explicit control law by using regression analysis. In this paper, we extracted two state-feedback control laws and two output-feedback control laws for flow around a cylinder as a benchmark. The state-feedback control laws that feed back different quantities to each other were extracted by ridge regression, and the two output-feedback control laws, whose measurement output is the surface pressure, were extracted by ridge regression and Gaussian process regression. In numerical simulations, the state-feedback control laws were able to suppress vortex shedding almost completely. While the output-feedback control laws could not suppress vortex shedding completely, they moderately improved the drag of the cylinder. Moreover, we confirmed that these control laws have some degree of robustness to the change in the Reynolds number. The computation times of the control input in all the extracted control laws were considerably shorter than that of the MPC.

Stabilization of Inverted Pendulum on a Cart in the Presence of Uncertainties

2015 ◽  
Author(s):  
Joonho Lee ◽  
Jongeun Choi
Keyword(s):  
Feedback Control ◽  
Output Feedback ◽  
State Feedback ◽  
Inverted Pendulum ◽  
Output Feedback Control ◽  
Control Design ◽  
High Gain ◽  
State Feedback Control ◽  
Dynamic Inversion ◽  
Pass Through

This paper presents an output feedback control design to stabilize the inverted pendulum at the upright equilibrium as an extension of our previous work [1]. Compared to our previous work, we add one more time scale between a pendulum angle and angular velocity to reduce a traveled distance of the cart. State feedback control is designed to enable the pendulum to pass through input singularity configurations. Extended High-Gain Observers are used to estimate velocity and acceleration terms while dynamic inversion utilizes the estimates to deal with input coefficient uncertainties and singularity configurations. The proposed control is verified through numerical simulations.

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