Model-based proportional-integral-derivative autotuning improved with relay feedback identification

2005 ◽  
Vol 152 (2) ◽  
pp. 247-256 ◽  
Author(s):  
A. Leva
2019 ◽  
Vol 11 (11) ◽  
pp. 168781401989021
Author(s):  
Yang Luo ◽  
Jianguo Tao ◽  
Zhuang Hao ◽  
Hao Sun ◽  
Zhandong Li ◽  
...  

This article presents a centroid variability model–based controller of HITUWV (Underwater Welding Vehicle by Harbin Institute of Technology), an underwater welding vehicle, for automatic welding with high stability and accuracy. First, an accurate centroid variability model, which considers the coefficient changes of the HITUWV caused by the movements of a 3-degree-of-freedom manipulator, is presented to perform the dynamic characteristics of the HITUWV precisely. Second, a centroid variability model–based adaptive sliding model controller is developed for the HITUWV to complete centroid variability compensation. Experimental results indicate that the proposed centroid variability model–based adaptive sliding model controller demonstrates better performances in stability and accuracy than the conventional proportional–integral–derivative controller and the model-based proportional–integral–derivative controller. As a result, the centroid variability model–based adaptive sliding model controller holds great practicality and utility on the control of underwater operation with high stability and accuracy.


Author(s):  
Ayhan Özdemir ◽  
Zekiye Erdem

Parameters of digital proportional–integral/proportional–integral–derivative controllers are usually calculated using commonly known conventional methods or solution of discrete-time equations. In literature, a model-based compact form formulation for calculation of discrete-time proportional–integral/proportional–integral–derivative controller parameters has not been come across yet. The proposed model-based compact form formulations are introduced to calculate the proportional–integral parameters in discrete time as a new approach. Generally, different types of control techniques are chosen in similar studies for double-loop control for direct current–direct current boost converter control except proportional–integral/proportional–integral. In this study, double-loop proportional–integral controller is used as a different control method from literature. By this way, the most important advantages of the proposed study are to reduce different design methods to a unique proportional–integral design method and shorten all calculations. The accuracy of the double-loop proportional–integral controller’s parameters calculated using the model-based compact form formulations is validated both in simulation and experimental studies under various disturbance effects. Satisfactory performance of the proposed controller under model uncertainty and other cases are comparatively shown with the predefined performance criteria.


2004 ◽  
Vol 100 (3) ◽  
pp. 640-647 ◽  
Author(s):  
Michel M. R. F. Struys ◽  
Tom De Smet ◽  
Scott Greenwald ◽  
Anthony R. Absalom ◽  
Servaas Bingé ◽  
...  

Background Although automated closed-loop control systems may improve quality of care, their safety must be proved under extreme control conditions. This study describes a simulation methodology to test automated controllers and its application in a comparison of two published controllers for Bispectral Index (BIS)-guided propofol administration. Methods A patient simulator was developed to compare controllers. Using input scripts to dictate patient characteristics, target BIS values, and the time course of surgical events, the simulator continuously monitors the infusion pump under control and generates BIS values as a composite of modeled response to drug, perceived stimulation, and random noise. The simulator formats the output stream of BIS data as input to the controller under test to emulate the serial output of the actual BIS monitor. A published model-based controller and a classic proportional integral derivative controller were compared when using the BIS value as a controlled variable. Each controller was tested using a set of 10 virtual patients undergoing a fixed surgical profile that was repeated with BIS targets set at 30, 50, and 70. Controller performance was assessed using median (absolute) prediction error, divergence, wobble, and percentage time within BIS target range metrics. Results The median prediction error was significantly smaller for the proportional integral derivative controller than for the model-based controller. The median absolute prediction error was smaller for the model-based controller than for the proportional integral derivative controller for each BIS target, reaching statistical significance for targets 30 and 50. Conclusions When simulating closed-loop control of BIS using propofol, the use of a patient-individualized, model-based adaptive closed-loop system with effect site control resulted in better control of BIS compared with a standard proportional integral derivative controller with plasma site control. Even under extreme conditions, the modeled-based controller exhibited no behavioral problems.


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