Design of a Data-Driven Multi-loop Self-Tuning PID Controller

2019 ◽  
Vol 139 (4) ◽  
pp. 356-363
Author(s):  
Yoichiro Ashida ◽  
Shin Wakitani ◽  
Toru Yamamoto
Keyword(s):  
Pid Controller ◽  
Data Driven ◽  
Self Tuning

scholarly journals Data-Driven Tuning of PID Controlled Piezoelectric Ultrasonic Motor

Actuators ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 148
Author(s):  
Sarah Makarem ◽  
Bülent Delibas ◽  
Burhanettin Koc
Keyword(s):  
Genetic Algorithm ◽  
Pid Controller ◽  
Good Alternative ◽  
Data Driven ◽  
Grid Search ◽  
Single Source ◽  
Dual Frequency ◽  
Dual Source ◽  
Stage System ◽  
Piezoelectric Ultrasonic Motor

Ultrasonic motors employ resonance to amplify the vibrations of piezoelectric actuator, offering precise positioning and relatively long travel distances and making them ideal for robotic, optical, metrology and medical applications. As operating in resonance and force transfer through friction lead to nonlinear characteristics like creep and hysteresis, it is difficult to apply model-based control, so data-driven control offers a good alternative. Data-driven techniques are used here for iterative feedback tuning of a proportional integral derivative (PID) controller parameters and comparing between different motor driving techniques, single source and dual source dual frequency (DSDF). The controller and stage system used are both produced by the company Physik Instrumente GmbH, where a PID controller is tuned with the help of four search methods: grid search, Luus–Jaakola method, genetic algorithm, and a new hybrid method developed that combines elements of grid search and Luus–Jaakola method. The latter method was found to be quick to converge and produced consistent result, similar to the Luus–Jaakola method. Genetic Algorithm was much slower and produced sub optimal results. The grid search has also proven the DSDF driving method to be robust, less parameter dependent, and produces far less integral position error than the single source driving method.

scholarly journals Simulation Study of Hydraulic Turbine by Using Self-Tuning Fuzzy PID Controller

2015 ◽  
Vol 3 (1) ◽  
pp. 7-15
Author(s):  
Hakan Açıkgöz ◽  
Ö. Fatih Keçecioğlu ◽  
Mahit Güneş ◽  
Mustafa Şekkeli
Keyword(s):  
Simulation Study ◽  
Pid Controller ◽  
Hydraulic Turbine ◽  
Fuzzy Pid ◽  
Fuzzy Pid Controller ◽  
Self Tuning
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