Generic single-input observability of continuous-time polynomial systems

1978 ◽  
Author(s):  
Hector Sussmann
Keyword(s):  
Continuous Time ◽  
Polynomial Systems ◽  
Single Input

REALIZATION PROBLEM FOR POSITIVE CONTINUOUS-TIME SYSTEMS WITH DELAYS

2006 ◽  
Vol 06 (02) ◽  
pp. 289-298 ◽  
Author(s):  
KACZOREK TADEUSZ
Keyword(s):  
Continuous Time ◽  
Sufficient Conditions ◽  
Realization Problem ◽  
Single Input Single Output ◽  
Single Output ◽  
Continuous Time Systems ◽  
Single Input ◽  
Minimal Realizations ◽  
Time Systems ◽  
Time Linear

The realization problem for positive, continuous-time linear single-input, single-output systems with delays is formulated and solved. Sufficient conditions for the existence of positive realizations of a given proper transfer function are established. A procedure for computation of positive minimal realizations is presented and illustrated by an example.

scholarly journals Control of Ensembles of Single-Input Continuous-Time Linear Systems

2013 ◽  
Vol 46 (27) ◽  
pp. 122-129 ◽  
Author(s):  
Michael Schönlein ◽  
Uwe Helmke
Keyword(s):  
Linear Systems ◽  
Continuous Time ◽  
Single Input ◽  
Time Linear

Dynamic logarithmic state and control quantization for continuous-time linear systems

Robotica ◽  
2022 ◽  
pp. 1-16
Author(s):  
Jiashuo Wang ◽  
Shuo Pan ◽  
Zhiyu Xi
Keyword(s):  
Feedback Control ◽  
Linear System ◽  
Linear Systems ◽  
Continuous Time ◽  
Control Law ◽  
Quantized Feedback ◽  
Single Input ◽  
Simulation Results ◽  
And Control ◽  
Time Linear

Abstract This paper addresses logarithmic quantizers with dynamic sensitivity design for continuous-time linear systems with a quantized feedback control law. The dynamics of state quantization and control quantization sensitivities during “zoom-in”/“zoom-out” stages are proposed. Dwell times of the dynamic sensitivities are co-designed. It is shown that with the proposed algorithm, a single-input continuous-time linear system can be stabilized by quantized feedback control via adopting sensitivity varying algorithm under certain assumptions. Also, the advantage of logarithmic quantization is sustained while achieving stability. Simulation results are provided to verify the theoretical analysis.

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