Intelligent Approaches to Real Time Level Control

Abstract

Liquid level control is important for ensuring energy and material balance in many installations but it also difficult as the plant is nonlinear, inertial and with model uncertainties. Fuzzy logic controllers (FLCs) are successfully applied to ensure system stability and robustness by simple means and a model-free design. This paper suggests a procedure for off-line tuning of the many FLC parameters based on optimization of a suggested multi-objective function defined on several system performance indices using genetic algorithms (GAs). First, a model-free FLC is empirically tuned, then applied for real time control of the plant and the necessary data recorded and used to GA parameter optimize a TSK plant model of an accepted structure. The validated on different set of experimental data model is employed in FLC closed loop system simulation experiments to evaluate the fitness function in the GA optimization of the FLC pre-processing and postprocessing parameters. The procedure is applied for the real time PI/PID FLC level control in a laboratory-scale tank system. The improvement of the system performance indices due to the GA optimization is estimated in level real time control.

Bulanık Anahtarlama Algoritması ile DTC Kontrollü Asenkron Makine için İyileştirilmiş Tork ve Hız Performansları

“…Scaling factors, rule-base, and membership functions are the three basic components of the fuzzy logic speed controller (MFs). Preprocessing, processing, and post-processing are the three operational activities that make up FLC's system (Yordanova, 2015). The input variables are turned (fuzzified) into fuzzy variables through input membership functions during the pre-processing stage, which is known as fuzzification.…”

Kendali PI-D dan Kontrol Fuzzy pada Plant Level Air Terdistribusi

“…Dalam kasus semacam ini diterapkan kendali terdistribusi sebagai solusinya. Penelitian lain mencoba menyelesaikan dengan mereduksi waktu komputasi (Wang & Wang, 2018) (Yordanova, 2015), meminimalkan hilangnya data (Pambakian, 2011) (Wang & Wang, 2018), mengoptimasi transmisi data dan layanan paket (packet of service) (Chen & Tat Pham, 2008) (Narayan, 2014).…”

An Approach to Observability and Controllability Analysis of Nonlinear Plants on the Basis of TSK Models

“…[12,[20][21][22][23][24][25]. They are appealing because can be developed and applied to any nonlinear plant in a unified manner, using the well mastered linear control techniques both for the design and the nonlinear system stability analysis.…”