<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>An averaging tank with variable filling is a nonlinear multidimensional system and can thus be considered a complex control system. General control objectives of such object include ensuring stability, zero steady-state error, and achieving simultaneously shortest possible settling time and minimal overshoot. The main purpose of this research work was the modeling and synthesis of three control systems for an averaging tank. In order to achieve the intended purpose, in the first step, a mathematical model of the control system was derived. The model was adapted to the form required to design two out of three planned control systems by linearization and reduction of its dimensions, resulting in two system variants. A multivariable proportional-integral-derivative (PID) control system for the averaging tank was developed using optimization for tuning PID controllers. State feedback and output feedback with an integral action control system for the considered control system was designed using a linear-quadratic regulator (LQR) and optimization of weights. A fuzzy control system was designed using the Mamdani inference system. The developed control systems were tested using theMATLAB environment. Finally, the simulation results for each control algorithm (and their variants) were compared and their performance was assessed, as well as the effects of optimization in the case of PID and integral control (IC) systems.</p>
</abstract>

An averaging tank with variable filling is a nonlinear multidimensional system and can thus be considered a complex control system. General control objectives of such object include ensuring stability, zero steady-state error, and achieving simultaneously shortest possible settling time and minimal overshoot. The main purpose of this research work was the modeling and synthesis of three control systems for an averaging tank. In order to achieve the intended purpose, in the first step, a mathematical model of the control system was derived. The model was adapted to the form required to design two out of three planned control systems by linearization and reduction of its dimensions, resulting in two system variants. A multivariable proportional-integral-derivative (PID) control system for the averaging tank was developed using optimization for tuning PID controllers. State feedback and output feedback with an integral action control system for the considered control system was designed using a linear-quadratic regulator (LQR) and optimization of weights. A fuzzy control system was designed using the Mamdani inference system. The developed control systems were tested using theMATLAB environment. Finally, the simulation results for each control algorithm (and their variants) were compared and their performance was assessed, as well as the effects of optimization in the case of PID and integral control (IC) systems.

Design of Three Control Algorithms for an Averaging Tank with Variable Filling

Faculty of Electrical and Control Engineering

Acta Mechanica et Automatica

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Design of Three Control Algorithms for an Averaging Tank with Variable Filling"}

An averaging tank with variable filling is a nonlinear multidimensional system and can thus be considered a complex control system. General control objectives...

Design of Three Control Algorithms for an Averaging Tank with Variable Filling

Publié en ligne: 18 avr. 2022

Pages: 136 - 150

Reçu: 03 janv. 2022

Accepté: 06 mars 2022

DOI: https://doi.org/10.2478/ama-2022-0018

Mots clés
control system, fuzzy control system, integral control system, LQR, mathematical model, PID control system, state feedback controller, tank with variable filling

© 2020 Michał Kolankowski et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Design of Three Control Algorithms for an Averaging Tank with Variable Filling

Publié en ligne: 18 avr. 2022

Pages: 136 - 150

Reçu: 03 janv. 2022

Accepté: 06 mars 2022

DOI: https://doi.org/10.2478/ama-2022-0018

Mots cléscontrol system, fuzzy control system, integral control system, LQR, mathematical model, PID control system, state feedback controller, tank with variable filling

© 2020 Michał Kolankowski et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Mots clés
control system, fuzzy control system, integral control system, LQR, mathematical model, PID control system, state feedback controller, tank with variable filling