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  • In Jour Smart Sensing And Intelligent Systems

 

Article | 16-December-2013

SYSTEM IDENTIFICATION MODELLING AND IMC BASED PID CONTROL OF IMPRESSED CURRENT CATHODIC PROTECTION SYSTEMS

parametric model of this system was obtained using System Identification (SI) approach.Furthermore,an Internal Model Control based Proportional Integral Derivative (IMC-PID) controller has been designed for enhancingthe performance of ICCP systems.Additionally, simulation and onlineimplementation works have been carried out to control ICCP systems at different operating conditions. Nevertheless, the IMC-PID controller leads todecrease both the Integral of the Absolute Error (IAE) and the Steady State

EzzEldin Balla, MohdFua’ad Rahmat

International Journal on Smart Sensing and Intelligent Systems, Volume 6 , ISSUE 5, 2055–2074

Article | 03-November-2017

APPLICATION OF SELF-TUNING FUZZY PID CONTROLLER ON INDUSTRIAL HYDRAULIC ACTUATOR USING SYSTEM IDENTIFICATION APPROACH

In this paper, Self Tuning Fuzzy PID controller is developed to improve the performance of the electro-hydraulic actuator. The controller is designed based on the mathematical model of the system which is estimated by using System Identification technique. The model is performed in linear discrete model to obtain a discrete transfer function for the system. Model estimation procedures are done by using System Identification Toolbox in Matlab. Data for model estimation is taken from an

Zulfatman, M. F. Rahmat

International Journal on Smart Sensing and Intelligent Systems, Volume 2 , ISSUE 2, 246–261

Research paper | 13-December-2017

SYSTEM IDENTIFICATION OF NONLINEAR AUTOREGRESSIVE MODELS IN MONITORING DENGUE INFECTION

This paper proposes system identification on application of nonlinear AR (NAR) based on Artificial Neural Network (ANN) for monitor of dengue infections. In building the model, three selection criteria, i.e. the final prediction error (FPE), Akaike’s Information Criteria (AIC), and Lipschitz number were used. Each of the models is divided into two approaches, which are unregularized approach and regularized approach. The findings indicate that NARMAX model with regularized approach yields

H. Abdul Rahim, F. Ibrahim, M. N. Taib

International Journal on Smart Sensing and Intelligent Systems, Volume 3 , ISSUE 4, 783–806

Article | 01-June-2012

NON-MINIMUM PHASE MODEL OF VERTICAL POSITION ELECTRO-HYDRAULIC CYLINDER FOR TRAJECTORY ZPETC

polynomial algorithm. With the proposed strategy, the controller parameters are determined using comparing coefficients methods. The electro-hydraulic system mathematical model is approximated using system identification technique with non-minimum phase system being considered. The real-time experimental result will be compared with simulation result using a model from a real plant.

Norlela Ishak, Mazidah Tajjudin, Hashimah Ismail, Michael Patrick, Yahaya Md Sam, Ramli Adnan

International Journal on Smart Sensing and Intelligent Systems, Volume 5 , ISSUE 2, 504–520

Article | 27-December-2017

IDENTIFICATION OF ELECTRO-HYDRAULIC ACTUATOR USING FRACTIONAL MODEL

Electro-hydraulic actuator (EHA system) identification is to describe the characteristic of the system that useful for prediction or control system design. There are numerous methods of EHA modeling but there has not been much model using fractional-order (FO) model. In this work, integer-order (IO) model and FO model are developed to model EHA system. Output-error method is used as the estimator for both model. The coefficient of IO model was first estimated and using the estimated coefficient

Nuzaihan Mhd Yusof, Norlela Ishak, Ramli Adnan, Yahaya Md. Sam, Mazidah Tajjudin, Mohd Hezri Fazalul Rahiman

International Journal on Smart Sensing and Intelligent Systems, Volume 9 , ISSUE 1, 32–48

Research Article | 01-June-2011

SELF-TUNING CONTROL OF AN ELECTRO-HYDRAULIC ACTUATOR SYSTEM

Due to time-varying effects in electro-hydraulic actuator (EHA) system parameters, a self-tuning control algorithm using pole placement and recursive identification is presented. A discrete-time model is developed using system identification method to represent the EHA system and residual analysis is used for model validation. A recursive least square (RLS) method with covariance resetting technique is proposed to estimate parameters of the discrete-time model. The results show the proposed

R. Ghazali, Y. M. Sam, M. F. Rahmat, K. Jusoff, Zulfatman, A. W. I. M. Hashim

International Journal on Smart Sensing and Intelligent Systems, Volume 4 , ISSUE 2, 189–204

Article | 01-September-2012

MODELING AND CONTROLLER DESIGN OF PNEUMATIC ACTUATOR SYSTEM WITH CONTROL VALVE

Pneumatic actuators offer several advantages over electromechanical and hydraulic actuators for positioning applications. Nonetheless, pneumatic actuators are subject to high friction forces, dead band and dead time, which make fast and accurate position control difficult to achieve. This research paper presents the process of controller identification, design, modeling and control for pneumatic actuator system. System Identification approach is used with the purpose to estimate the

W.K. Lai, M.F. Rahmat, N. Abdul Wahab

International Journal on Smart Sensing and Intelligent Systems, Volume 5 , ISSUE 3, 624–644

Research Article | 20-February-2013

FEED FORWARD LINEAR QUADRATIC CONTROLLER DESIGN FOR AN INDUSTRIAL ELECTRO HYDRAULIC ACTUATOR SYSTEM WITH SERVO VALVE

Electro-hydraulic servo actuator (EHA) system consists of several dynamic parts which are widely used in motion control application. These dynamic parts need to be controlled to determine direction of the motion. In this research paper, system identification technique is used for system modeling and the model of the system is estimated by using parameter estimation technique. This process started with collection of input and output data from experimental procedure. The data collected is used

J. Micheal, M.F. Rahmat, N. Abdul Wahab, W.K. Lai

International Journal on Smart Sensing and Intelligent Systems, Volume 6 , ISSUE 1, 155–170

Research Article | 13-December-2017

APPLICATION OF DRAW WIRE SENSOR IN POSITION TRACKING OF ELECTRO HYDRAULIC ACTUATOR SYSTEM

motion when an input signal is injected to the system. The sensor output is the displacement in millimeter and converted to the voltage based on the input signal given. These input and output readings are collected and applied to a system identification procedure in order to obtain the best mathematical model of the system. The modeling process is followed by designed a proportional integral and derivative controller (PID) for the system to assure the output is tracking the input given. The designed

MF Rahmat, S Md Rozali, N Abdul Wahab, Zulfatman

International Journal on Smart Sensing and Intelligent Systems, Volume 3 , ISSUE 4, 736–755

Article | 03-November-2017

MODELING AND CONTROLLER DESIGN FOR THE VVS-400 PILOT SCALE HEATING AND VENTILATION SYSTEM

In this paper, a heating and ventilation model VVS-400 from Instrutek, Larvik, Norway is modeled using ARX model structure and linear black-box technique. The conventional PID controller and artificial Fuzzy controller are designed based on the approximated plant model and real plant model. The approximated plant model is estimated using System Identification approach while the real plant model is developed by interfacing the Real-time Windows Target toolbox in Matlab with real VVS-plant by

M.F. Rahmat, N.A. Mohd Subha, Kashif M.Ishaq, N. Abdul Wahab

International Journal on Smart Sensing and Intelligent Systems, Volume 2 , ISSUE 4, 579–601

Research Article | 27-December-2017

MODEL IDENTIFICATION AND CONTROLLER DESIGN FOR AN ELECTRO-PNEUMATIC ACTUATOR SYSTEM WITH DEAD ZONE COMPENSATION

N. H. Sunar, M. F. Rahmat, Zool Hilmi Ismail, Ahmad Athif Mohd Faudzi, Sy Najib Sy Salim

International Journal on Smart Sensing and Intelligent Systems, Volume 7 , ISSUE 2, 798–819

Article | 05-June-2013

AUTO-ADAPTIVE CONTROL OF A ONE-JOINT ARM DIRECT DRIVEN BY ANTAGONISTIC SHAPE MEMORY ALLOY

experimentally. The controller is designed based on the model estimated by using system identification technique. Experimental and simulation results show that antagonistic SMA actuator in combination with the controller can track any input trajectory signal with high accuracy motion control and is suitable for various control applications.

D Josephine Selvarani Ruth, S Sunjai Nakshatharan, K Dhanalakshmi

International Journal on Smart Sensing and Intelligent Systems, Volume 6 , ISSUE 3, 833–849

Research paper | 01-September-2011

PERFECT TRACKING CONTROL WITH DISCRETE-TIME LQR FOR A NON-MINIMUM PHASE ELECTRO-HYDRAULIC ACTUATOR SYSTEM

) technique which the main difficulty arises from the non-minimum phase system is have no stable inverse. Subsequently, the controller is applied to EHS system which is represented in discrete-time model where the model is obtained experimentally using system identification method. The proposed controller design using ZPETC is particularly suited to the various positioning control applications that encounter non-minimum phase problem. It is also shows that the controller offers good performance in

R. Ghazali, Y. M. Sam, M.F. Rahmat, Zulfatman, A. W. I. M. Hashim

International Journal on Smart Sensing and Intelligent Systems, Volume 4 , ISSUE 3, 424–439

Research Article | 01-December-2017

I-PD CONTROL DESIGN AND ANALYSIS IN AN ISLANDED MICROGRID SYSTEM

voltage in a microgrid. In the simulation using MATLAB, a distributed energy resource unit applying voltage-source converter in order to have three-phase voltage from a DC-source is taken into account. Using system identification to simplify the controller design generates a linear model of the system. The compensated system shows a very good reference tracking capability during set point and load changes. It also reduces the coupling effect due to active and reactive power.

S. D. Panjaitan, R. Kurnianto, B.W. Sanjaya, M. C. Turner

International Journal on Smart Sensing and Intelligent Systems, Volume 10 , ISSUE 4, 935–954

research-article | 30-November-2020

Development of Low Cost Autonomous Underwater Vehicle Platform

batteries are located along with the circuitry, sensors, and control unit. The dry portion is segregated by the bulkheads for providing waterproof environment. An on-board data logger and control unit have been equipped with the AUV platform to allow sensor and actuator data to be recorded and processed to implement advanced system identification and control techniques. Necessary computers and sensors are chosen, considering the need for low cost, compact, simplicity of program and processor

Osama Hassanein, G. Sreenatha, S. Aboobacker, Shaaban Ali

International Journal on Smart Sensing and Intelligent Systems, Volume 14 , ISSUE 1, 1–22

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