Simultaneous Design of Linear Time-Invariant Systems using Generalized Sampled-Data Hold Functions

1988 ◽  
Author(s):  
Pierre T. Kabamba ◽  
Chang Yang
Keyword(s):  
Linear Time ◽  
Sampled Data ◽  
Linear Time Invariant ◽  
Simultaneous Design ◽  
Linear Time Invariant Systems ◽  
Time Invariant

scholarly journals On Fault Detection in Linear Discrete-Time, Periodic, and Sampled-Data Systems

2008 ◽  
Vol 2008 ◽  
pp. 1-18 ◽  
Author(s):  
P. Zhang ◽  
S. X. Ding
Keyword(s):  
Fault Detection ◽  
Linear Time ◽  
Periodic Systems ◽  
Data Systems ◽  
Sampled Data ◽  
Linear Time Invariant ◽  
Linear Time Invariant Systems ◽  
Problem Formulations ◽  
Time Invariant ◽  
Time Periodic

This paper gives a review of some standard fault-detection (FD) problem formulations in discrete linear time-invariant systems and the available solutions. Based on it, recent development of FD in periodic systems and sampled-data systems is reviewed and presented. The focus in this paper is on the robustness and sensitivity issues in designing model-based FD systems.

scholarly journals Data-Driven Optimal Control of Linear Time-Invariant Systems

2020 ◽  
Vol 53 (2) ◽  
pp. 7191-7196
Author(s):  
Dzmitry Kastsiukevich ◽  
Natalia Dmitruk
Keyword(s):  
Optimal Control ◽  
Linear Time ◽  
Data Driven ◽  
Linear Time Invariant ◽  
Linear Time Invariant Systems ◽  
Time Invariant

Continuous control of sampled data systems with robustness against bounded measurement errors

2017 ◽  
Vol 40 (10) ◽  
pp. 3125-3133
Author(s):  
Milad Ghanbari ◽  
Masoud Bahraini ◽  
Mohammad Javad Yazdanpanah
Keyword(s):  
Measurement Errors ◽  
Control Method ◽  
Linear Time ◽  
Continuous Control ◽  
Data Systems ◽  
Sampled Data ◽  
Linear Time Invariant ◽  
Experimental Implementation ◽  
Time Invariant ◽  
Ultimate Bound

This paper considers the design of a generalized hold function to be used for the control of sampled-data systems. The proposed method suggests a continuous controller for sampled data systems. Ultimate boundedness of the proposed method in the presence of bounded measurement errors is also shown for linear and nonlinear systems. In linear time invariant cases, a cost function is suggested for the sake of ultimate bound minimization. In addition, this can answer how we choose a sensor for a real system to get a desired control outcome. Eventually, the effectiveness of the proposed control method is investigated through simulation and experimental implementation.

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