Generation of discrete and continuous time transfer function coefficients

1994 ◽  
Vol 59 (5) ◽  
pp. 1159-1172 ◽  
Author(s):  
D. P. STOTEN ◽  
A. J. L. HARRISON
Keyword(s):  
Transfer Function ◽  
Continuous Time ◽  
Time Transfer

scholarly journals Z Transformation by Pascal Matrix and its Applications in the Design of IIR Filters

2011 ◽  
Vol 9 (03) ◽  
Author(s):  
F. J. García-Ugalde ◽  
B. Psenicka ◽  
M.O. Jiménez-Salinas
Keyword(s):  
Transfer Function ◽  
Continuous Time ◽  
Direct Method ◽  
Time Transfer ◽  
Iir Filters ◽  
Pascal Matrix ◽  
Low Pass ◽  
Z Transformation ◽  
A Direct Method

In this work, we summarize a direct method to transform the low-pass continuous-time transfer function

Bias Distribution in Continuous-Time Transfer Function Estimates by Prediction Error Method

1993 ◽  
Vol 26 (2) ◽  
pp. 637-641
Author(s):  
V.N. Bapat ◽  
S. Mukhopadhyay ◽  
A. Patra ◽  
D.C. Saha
Keyword(s):  
Transfer Function ◽  
Continuous Time ◽  
Prediction Error ◽  
Time Transfer ◽  
Error Method

scholarly journals Hardware as for Teaching Modeling and Control

2016 ◽  
Vol 138 (06) ◽  
pp. S12-S16
Author(s):  
Joseph D. Steinmeyer ◽  
Jacob K. White
Keyword(s):  
Transfer Function ◽  
Continuous Time ◽  
Time Transfer ◽  
Design Problems ◽  
Modeling And Control ◽  
Staff Members ◽  
Introductory Classes ◽  
And Control

This article explores the introduction and use of new control classes that focus as much on modeling as on control. The paper describes several aspects of design problems with an emphasis on how to keep the process pedagogically efficient. The introductory classes in newer engineering curricula, at MIT and elsewhere, seek to empower students by avoiding highly customized devices, and instead rely on collections of easily composed and readily available sensors, actuators, and micro-controllers. The 15-week on-campus modeling and control class begins with classical material, discrete- and continuous-time transfer function modeling combined with PID and lead-lag controllers. With a combination of guidance and insights gained from constructing their artefacts, students determine a set of experiments and measurements that inform a model. Then they focus on designing and testing controllers, while answering impromptu questions from the roaming staff members.

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