Double-tank Liquid Level Control Based on Genetic Algorithm

2012 ◽  
Author(s):  
Keliang Zhou ◽  
Bin Yan ◽  
Yulan Jiang ◽  
Jinlin Huang
Keyword(s):  
Genetic Algorithm ◽  
Liquid Level ◽  
Level Control ◽  
Liquid Level Control

scholarly journals Parameter Tuning of PID Controller for Beer Filling Machine Liquid Level Control Based on Improved Genetic Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Liqing Xiao
Keyword(s):  
Genetic Algorithm ◽  
Pid Controller ◽  
Parameter Tuning ◽  
Liquid Level ◽  
Improved Genetic Algorithm ◽  
Level Control ◽  
Experimental Conditions ◽  
Modified Particle Swarm Optimization ◽  
Beer Production ◽  
Liquid Level Control

Parameter tuning of PID controller for liquid level control of beer filling machine was studied in this paper, which can meet the demand of accurate controlling in beer production and improve the rapidity under the same conditions. Firstly, an improved genetic algorithm was proposed which has been verified by eight kinds of test functions. Simulation results revealed that, in comparation with other modified particle swarm optimization algorithm and modified genetic algorithm, the algorithm proposed in this work is not only capable to improve the convergence speed and precision under the same experimental conditions but also to improve the probability to converge to the optimal value. Finally, the proposed algorithm was applied to the parameter tuning of the PID controller of beer filling machine for liquid level control. Superior property had been obtained, which implied an effective improvement in the rapidity with the premise of steady-state error exclusion.

Integral Time Absolute Error Minimization For Pi Controller On Coupled–Tank Liquid Level Control System Based On Stochastic Search Echniques

2012 ◽  
Author(s):  
Ammar Hussam Yousif Yacoub ◽  
Salinda Buyamin ◽  
Norhaliza Abdul Wahab
Keyword(s):  
Genetic Algorithm ◽  
Simulated Annealing ◽  
Absolute Error ◽  
Pi Controller ◽  
Stochastic Search ◽  
Time Response ◽  
Liquid Level ◽  
Level Control ◽  
Proportional Integral ◽  
Liquid Level Control

Kertas ini membincangkan tentang aplikasi teknik pencarian stochastic yang dikenali sebagai Simulated Annealing bagi mengatasi masalah menala (tuning) alat pengawal Proportional plus Integral (PI) bagi pengawalan takat cecair di dalam sistem tangki berkembar. Setelah penerangan tentang prinsipal asas kepada Simulated Annealing diberikan, kertas ini mencadangkan tentang pencarian penyelesaian yang optimal bagi alat kawalan PI dengan mengoptimumkan prestasi indek, ITAE. Keberkesanan menggunakan kaedah Simulated Annealing telah dibandingkan dengan satu lagi kaedah iaitu Genetic Algorithm. Perbandingan adalah berdasarkan prestasi time response. Hasil keputusan menunjukkan perbandingan antara kaedah Simulated Annealing dan Genetic Algorithm. Kaedah yang di cadangkan tidak bergantung kepada tahap sesuatu sistem dan berupaya untuk menala walaupun tanpa diketahui parameter sesuatu proses . Di samping itu, kaedah yang di cadangkan tidak memerlukan sistem tersebut dimodelkan dalam bentuk matematik dan keseluruhan keputusan menunjukkan Simulated Annealing menghasilkan keputusan yang lebih baik dari Genetik Algorithm. Oleh itu, Simulated Annealing bolehlah dicadangkan sebagai salah satu cara bagi mengoptimumkan alat kawalan PI. Kata kunci: Penalaan proportional integral tuning; imulated annealing; genetic algorithm This paper introduces the application of a stochastic search technique, known as Simulated Annealing to the problem of tuning the proportional–integral controller for a linearized coupled tank liquid level control. After describing the basic principles of the Simulated Annealing, the proposed method concentrates on finding the optimal solution of PI controller by optimizing the performance index, the Integral Time Absolute Error, ITAE. The efficiency of Simulated Annealing algorithm for tuning the controller is compared with an evolutionary method, Genetic Algorithm. The comparison is based on the time response performance. The results shows the effectiveness and the capability of the SA to tune the proportional–integral (PI) controller for the coupled tank liquid level control. The proposed method does not depend on the system order and has the ability to tune the controller even there is unknown process parameters. In addition, the technique avoids the requirement for mathematical modeling of the system and the overall results have shown that SA yields better performance as compared to GA, hence, it is recommended for an alternative for optimizing the PI controller. Key words: Proportional integral tuning; simulated annealing; genetic algorithm

Liquid Level Control of Four-Tank System Based on Active Disturbance Rejection Technology

Measurement ◽  
2021 ◽  
Vol 175 ◽  
pp. 109146
Author(s):  
Xiangxiang Meng ◽  
Haisheng Yu ◽  
Jie Zhang ◽  
Tao Xu ◽  
Herong Wu
Keyword(s):  
Disturbance Rejection ◽  
Liquid Level ◽  
Level Control ◽  
Active Disturbance Rejection ◽  
Tank System ◽  
Liquid Level Control
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