Simultaneous automatic tuning of cascade control systems from closed-loop step response data

2012 ◽  
Vol 22 (6) ◽  
pp. 1020-1033 ◽  
Author(s):  
Jyh-Cheng Jeng ◽  
Ming-Wei Lee
Keyword(s):  
Control Systems ◽  
Closed Loop ◽  
Cascade Control ◽  
Automatic Tuning ◽  
Step Response ◽  
Response Data

Data-driven I-PD Gain Tuning using Closed-loop Step Response Data

2019 ◽  
Vol 139 (8) ◽  
pp. 882-888
Author(s):  
Shiro Masuda ◽  
Jongho Park ◽  
Yoshihiro Matsui
Keyword(s):  
Closed Loop ◽  
Data Driven ◽  
Step Response ◽  
Response Data

Analysis of Reset Control Systems Consisting of a FORE and Second-Order Loop1

2001 ◽  
Vol 123 (2) ◽  
pp. 279-283 ◽  
Author(s):  
Qian Chen ◽  
Yossi Chait ◽  
C. V. Hollot
Keyword(s):  
Control Systems ◽  
Closed Loop ◽  
Second Order ◽  
Step Response ◽  
Steady State Response ◽  
First Order ◽  
State Response ◽  
Loop Transfer Function ◽  
Performance Specifications ◽  
Reset Control

Reset controllers consist of two parts—a linear compensator and a reset element. The linear compensator is designed, in the usual ways, to meet all closed-loop performance specifications while relaxing the overshoot constraint. Then, the reset element is chosen to meet this remaining step-response specification. In this paper, we consider the case when such linear compensation results in a second-order (loop) transfer function and where a first-order reset element (FORE) is employed. We analyze the closed-loop reset control system addressing performance issues such as stability, steady-state response, and transient performance.

Estimation of the Order and Parameters of a Fractional Order Model From a Noisy Step Response Data1

2014 ◽  
Vol 136 (3) ◽  
Author(s):  
Mahsan Tavakoli-Kakhki ◽  
Mohammad Saleh Tavazoei
Keyword(s):  
Numerical Simulation ◽  
Fractional Order ◽  
Closed Loop ◽  
Open Loop ◽  
Measurement Noise ◽  
Step Response ◽  
Order Model ◽  
Response Data ◽  
Fractional Order Model ◽  
Simulation Results

This paper deals with integral based methods to estimate the order and parameters of simple fractional order models from the extracted noisy step response data of a process. This data can be obtained from both open-loop and closed-loop tests. Numerical simulation results are presented to verify the robustness of these proposed methods in the presence of the measurement noise.

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