Modeling and Controller Design for a Coupled–Tank Liquid Level System: Analysis & Comparison

2012 ◽  
Author(s):  
Mohd Fua’ad Rahmat ◽  
Sahazati Md Rozali
Keyword(s):  
Fuzzy Logic ◽  
System Identification ◽  
System Analysis ◽  
Binary Sequence ◽  
Least Square Method ◽  
Least Square ◽  
Step Response ◽  
Response Analysis ◽  
Pseudorandom Binary Sequence ◽  
Tank System

Sistem yang diuji ialah tangki berkembar yang biasa digunakan dalam proses kawalan industri. Prinsip asas sistem tangki berkembar adalah untuk mengekalkan paras cecair di dalam tangki pada suatu nilai tetap apabila wujud aliran keluar masuk cecair dalam tangki. Analisis tindak balas langkah, analisis pseudorandom binary sequence (PRBS) dan kaedah least square digunakan untuk mengklasifikasikan sistem ini. Objektif utama projek ini adalah untuk menentukan model matematik sistem tangki berkembar menggunakan tiga teknik tesebut. Ia diikuti dengan mereka bentuk pengawal yang terdiri daripada pengawal PID dan pengawal Fuzzy Logic untuk sistem ini. Pada peringkat akhir projek ini, penggunaan kedua-dua pengawal dalam aplikasi industri dibandingkan dan dianalisa. Kata kunci: Pengenalpastian sistem, tindak balas langkah, pseudorandom binary sequence, kaedah least square, pengawal Fuzzy Logic & PID The system under investigation is a coupled-tank apparatus which is a laboratory bench top emulation of a common process in industrial control. The basic control principle of the coupled-tank system is to maintain a constant level of the liquid in the tank when there is an inflow and outflow of water in the tank and outflow of water out of the tank respectively. Classification of this system using system identification technique involved the transient response analysis, the pseudorandom binary sequence (PRBS) analysis and the least square method. The main objective of this project is to determine the mathematical model of a coupled-tank system using these techniques. It follows by designing a controller consists of a PID and a Fuzzy Logic controllers for the system. At the final stage of this project, the usage of both controllers in industrial applications is compared and analyzed. Key words: System identification, step response, pseudorandom binary sequence, least square method, PID & Fuzzy Logic controller

Research on Efficiency Model of the Variable Hydraulic Pump Based on System Identification

2012 ◽  
Vol 184-185 ◽  
pp. 421-428 ◽  
Author(s):  
Xiang Sheng Li
Keyword(s):  
System Identification ◽  
Functional Relationship ◽  
Least Square Method ◽  
Calculation Model ◽  
Least Square ◽  
Hydraulic Pump ◽  
Polynomial Expression ◽  
Identification Theory ◽  
Set Up ◽  
Axial Piston

For the complication and imprecision of the calculation of efficiency about variable hydraulic pump, based on system identification theory and thought of identification with the modeling，the general polynomial expression is proposed to describe the efficiency of variable hydraulic pumps and the functional relationship between parametric and to set up the model using the least square method of parameters identification, and calculation model of the efficiency is established as an example for a type of axial piston variable hydraulic pump, the model is verified by the experimental data, and it’s fitting accuracy is over 87%.

Adaptive Modeling of Laser Powder Deposition Process for Control and Monitoring Application

2005 ◽  
Author(s):  
Mohammad Durali ◽  
Alireza Fathi ◽  
Amir Khajepour ◽  
Ehsan Toyserkani
Keyword(s):  
Kalman Filter ◽  
System Identification ◽  
Least Square Method ◽  
Deposition Process ◽  
Least Square ◽  
Filter Method ◽  
Recursive Least Square ◽  
Noise Elimination ◽  
Laser Powder Deposition ◽  
Powder Deposition

Laser Powder Deposition technique is an advanced production method with many applications. Despite this fact, reliable and accurate control schemes have not yet fully developed for this method. This article presents method for in time identification of the process for modeling and adaptation of proper control strategy. ARMAX structure is chosen for system model. Recursive least square method and Kalman Filter methods are adopted for system identification, and their performance are compared. Experimental data was used for system identification, and proper filtering schemes are devised here for noise elimination and increased estimation results. It was concluded that although both methods yield efficient performance and accurate results, Kalman Filter method gives better results in parameter estimations. The comparison of the results shows that this method can be used very efficiently in control and monitoring of Laser Powder Deposition process.

MICROCONTROLLER-BASED FOR SYSTEM IDENTIFICATION TOOLS USING LEAST SQUARE METHOD FOR RC CIRCUITS

2015 ◽  
Vol 77 (28) ◽  
Author(s):  
Ang Jia Yi ◽  
M. S. Abdul Majid ◽  
Azuwir M. N. ◽  
S. Yaacob
Keyword(s):  
Mathematical Model ◽  
System Identification ◽  
Least Square Method ◽  
Least Square ◽  
Real Time System ◽  
System Identification Method ◽  
Identification Method ◽  
Verification Methods ◽  
Identification Technique ◽  
Rc Circuit

System identification is one of the method to construct a plant mathematical model from experimental data. This method has been widely applied in the automatic control, aviation, spaceflight medicine, society economics and other fields more. With the rapid growth of the science and technology, the system identification technique has increasingly grown in various applications. Since most of the system identification devices are off-line base, this means that the system identification can only be done after collecting the data and process through a computer devices. This paper will show how to process system identification method with real-time system. This method required a microcontroller as the medium to perform. That’s why the system identification method will be programmed into a microcontroller, based on Least Square Method. Later, the system will be tested on a RC circuit to see the effect of the signal and the mathematical model obtained. The data will undergo the system identification toolbox for process using ARX and ARMAX model. On the other hand, the data will also be collected using the microcontroller created for analysis purpose. To ensure the validity of the model some verification methods are performed. Results show that the Least Square Method using Microcontroller base has the capability to work as a system identification tools.

System Identification of a Class of Second-Order Continuous System

2014 ◽  
Vol 651-653 ◽  
pp. 528-533 ◽  
Author(s):  
Zhi Gang Jia ◽  
Xing Xuan Wang
Keyword(s):  
Linear Equations ◽  
Continuous System ◽  
Least Square Method ◽  
Second Order ◽  
Least Square ◽  
Step Response ◽  
Order System ◽  
Simulation Results ◽  
Order Continuous ◽  
Identification Model

An identification method of a class of second-order continuous system is proposed. This method constructs a discrete-time identification model, forms a set of linear equations. The parameters can be obtained by least square method. Simulation results show that the method is effective for a class of second-order system, and is not only for step response but also for square wave signal.

scholarly journals Fuzzy Logic-Based Aerodynamic Modeling with Continuous Differentiability

2013 ◽  
Vol 2013 ◽  
pp. 1-14 ◽  
Author(s):  
Ray C. Chang
Keyword(s):  
Fuzzy Logic ◽  
Atmospheric Turbulence ◽  
Model Development ◽  
Unsteady Aerodynamics ◽  
Least Square Method ◽  
Least Square ◽  
Transport Aircraft ◽  
Fuzzy Logic Algorithm ◽  
Modeling Process ◽  
Data Points

This paper presents a modeling method based on a fuzzy-logic algorithm to establish aerodynamic models by using the datasets from flight data recorder (FDR). The fuzzy-logic aerodynamic models are utilized to estimate more accurately the nonlinear unsteady aerodynamics for a transport aircraft, including the effects of atmospheric turbulence. The main objective in this paper is to present the model development and the resulting models with continuous differentiability. The uncertainty and correlation of the data points are estimated and improved by monitoring a multivariable correlation coefficient in the modeling process. The latter is increased by applying a least square method to a set of data points to train a set of modeling coefficients. A commercial transport aircraft encountered severe atmospheric turbulence twice at transonic flight in descending phase is the study case in the present paper. The robustness and nonlinear interpolation capability of the fuzzy-logic algorithm are demonstrated in predicting the degradation in performance and stability characteristics of this transport in severe atmospheric turbulence with sudden plunging motion.

Thrust Control of Small Turbojet Engines Using Fuzzy Logic: Design and Experimental Validation

2012 ◽  
Author(s):  
Riccardo Amirante ◽  
Luciano Andrea Catalano ◽  
Paolo Tamburrano
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Response Speed ◽  
Electricity Production ◽  
Control Technique ◽  
Step Response ◽  
Small Scale ◽  
Response Analysis ◽  
General Validity ◽  
Thrust Control

The aim of this paper is to propose an effective technique which employs a proportional-integral Fuzzy logic controller for the thrust regulation of small scale turbojet engines, capable of ensuring high performance in terms of response speed, precision and stability. Fuzzy rules have been chosen by logical deduction and some specific parameters of the closed loop control have been optimized using a numerical simulator, so as to achieve rapidity and stability of response, as well as absence of overshoots. The proposed Fuzzy logic controller has been tested on the Pegasus MK3 microturbine: the high response speed and precision of the proposed thrust control, revealed by the simulations, have been confirmed by several experimental tests with step response. Its stability has been demonstrated by means of the frequency response analysis of the system. The proposed thrust control technique has general validity and can be applied to any small-scale turbojet engine, as well as to microturbines for electricity production, provided that thrust being substituted with the net mechanical power.

Thrust Control of Small Turbojet Engines Using Fuzzy Logic: Design and Experimental Validation

2012 ◽  
Vol 134 (12) ◽  
Author(s):  
Riccardo Amirante ◽  
Luciano Andrea Catalano ◽  
Paolo Tamburrano
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Response Speed ◽  
Electricity Production ◽  
Control Technique ◽  
Step Response ◽  
Small Scale ◽  
Response Analysis ◽  
General Validity ◽  
Thrust Control

The aim of this paper is to propose an effective technique which employs a proportional-integral Fuzzy logic controller for the thrust regulation of small scale turbojet engines, capable of ensuring high performance in terms of response speed, precision and stability. Fuzzy rules have been chosen by logical deduction and some specific parameters of the closed loop control have been optimized using a numerical simulator, so as to achieve rapidity and stability of response, as well as absence of overshoots. The proposed Fuzzy logic controller has been tested on the Pegasus MK3 microturbine: the high response speed and precision of the proposed thrust control, revealed by the simulations, have been confirmed by several experimental tests with step response. Its stability has been demonstrated by means of the frequency response analysis of the system. The proposed thrust control technique has general validity and can be applied to any small-scale turbojet engine, as well as to microturbines for electricity production, provided that thrust being substituted with the net mechanical power.

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