M. F. Rahmat

Electrodynamics Sensor for the Image Reconstruction Process in an Electrical Charge Tomography System

Electrical charge tomography (EChT) is a non-invasive imaging technique that is aimed to reconstruct the image of materials being conveyed based on data measured by an electrodynamics sensor installed around the pipe. Image reconstruction in electrical charge tomography is vital and has not been widely studied before. Three methods have been introduced before, namely the linear back projection method, the filtered back projection method and the least square method. These methods normally face ill-posed problems and their solutions are unstable and inaccurate. In order to ensure the stability and accuracy, a special solution should be applied to obtain a meaningful image reconstruction result. In this paper, a new image reconstruction method – Least squares with regularization (LSR) will be introduced to reconstruct the image of material in a gravity mode conveyor pipeline for electrical charge tomography. Numerical analysis results based on simulation data indicated that this algorithm efficiently overcomes the numerical instability. The results show that the accuracy of the reconstruction images obtained using the proposed algorithm was enhanced and similar to the image captured by a CCD Camera. As a result, an efficient method for electrical charge tomography image reconstruction has been introduced.

PERFORMANCE COMPARISON BETWEEN LQR AND PID CONTROLLERS FOR AN INVERTED PENDULUM SYSTEM

The objective of this paper is to compare the time specification performance between two conventional controllers for an inverted pendulum system. The goal is to determine which control strategy delivers better performance with respect to pendulum’s angle and cart’s position. The inverted pendulum represents a challenging control problem, which continually moves toward an uncontrolled state. Two controllers are presented such as Linear‐Quadratic‐Regulator (LQR) and Proportional‐Integral‐Derivatives (PID) controllers for controlling the linearized system of inverted pendulum model. Simulation study has been done in Matlab simulink environment shows that both controllers are capable to control multi output inverted pendulum system successfully. The result shows that LQR produced better response compared to PID control strategies and is presented in time domain.

Velocity and mass flow rate profiles of dry powders in a gravity drop conveyor using an electrodynamic tomography system

This paper describes measurements made on a gravity drop conveyor using two arrays of axially spaced electrodynamic sensors to measure axial velocities close to the wall of the conveyor and velocity profiles both of flowing sand and of plastic beads. The level of correlation obtained using pixels is investigated. The velocity profile is combined with a tomographic concentration profile to estimate the mass flow profile, which is summed over the measurement cross section to estimate the mass flow rate. A calibration of the tomographically determined mass flow rate versus the actual mass flow rate is presented.

System identification of electro-hydraulic actuator servo system

This paper presents the system identification process done on an industrial Electro-Hydraulic Actuator (EHA) system. The model obtained through system identification by aid of System Identification Toolbox of MATLAB and System Identification Toolkit of LabVIEW. Attraction of system identification is ability to obtain systems model with sets of input and output data; without need of prior knowledge on system. The model is later validated with the actual performance of real EHA system.

Modelling and controller design for a cruise control system

This paper presents the performance of different control approaches that consist of conventional, modern and intelligent controller that employed in a cruise control system. The cruise control system is one of the most enduringly popular and important laboratory models for teaching control system engineering. The system is widely used because it is very simple to understand and yet the control techniques cover many important classical and modern design methods. In this paper, the mathematical modelling for linear and nonlinear dynamic model of the cruise control system is obtained. PID, state space and artificial intelligence controller (fuzzy logic) are designed for linear model. Meanwhile, PID with feedforward controller is proposed for nonlinear model with disturbance effect. Feedforward-type PD controller is proposed in this study in order to eliminate the gravitational and wind disturbance effect. Simulation will be carried out using. Finally, a comparative assessment of the impact of each controller on the basis of results acquired.

Pitch control system using LQR and Fuzzy Logic Controller

This paper presents a comparative assessment based on time response specification performance between modern and intelligent controller for a pitch control system of an aircraft system. The dynamic modeling of pitch control system is considered on the design an autopilot that controls the pitch angle of an aircraft. It begins with a derivation of suitable mathematical model to describe the dynamics of an aircraft. To study the effectiveness of the controllers, the Linear Quadratic Controller (LQR) and Fuzzy Logic Controller (FLC) is developed for controlling the pitch angle of an aircraft system. Simulation results for the response of pitch controller are presented in time domain. Finally, the performances of pitch control systems are investigated and analyzed based on common criteria of steps response in order to identify which control strategy delivers better performance with respect to the desired pitch angle and pitch rate. It is found from simulation, LQR controller give the best performance compared to fuzzy logic controller.

On-line identification of an electro-hydraulic system using recursive least square

This paper presents experimental on-line identification of an electro-hydraulic system represented by a discrete time model. A recursive least square (RLS) method is used to estimate the unknown parameters of the system based on auto regression with exogenous input (ARX) model. Residual analysis is used for model validation. Results are presented which show variations in parameters of the electro-hydraulic system.

System Identification model for an Intelligent Pneumatic Actuator (IPA) system

Intelligent Pneumatic Actuators (IPA) is a new generation of actuator for Research and Development (R&D). The purpose of this paper is to present the System Identification (SI) technique and procedure for the IPA system. System identification is used to obtain the mathematical model (transfer function) of the IPA system from the measured experimental data. Flow for the SI procedure starts with experimental setup, model structure selection, model estimation, model validation and finally testing with basic controller to prove the operation of IPA system. Auto Regressive with Exogenous Input (ARX) model is chosen as model structure of the system. Based on the input and output data of the system (model validation), best fit criterion and correlation analysis of the residual is analyzed to determine the adequate model to represent the IPA system. The result from SI model shows linear discrete model in order to obtain a discrete transfer function for the IPA system.

Application of fuzzy logic and electrodynamic sensors as flow pattern identifier

Purpose – The use of pneumatic conveying of solid bulk over long distance has become a popular technique due to low operational cost, low maintenance requirement, layout flexibility and ease of automation. The purpose of this paper is to identifity the flow regime in a pneumatic conveyor system by electrodynamic sensor placed around the pipe using fuzzy logic tools.Design/methodology/approach – Electrical charge tomography is used to detect the existence of inherent charge on the moving particles through the pipe. Linear back projection algorithm and filtered back projection algorithm are employed to produce tomography image. Baffles of different shapes are inserted to create various flow regimes, such as full flow, three quarter flow, half flow and quarter flow. Fuzzy logic tools are used to identify different flow regimes and produce filtered back concentration profiles for each flow regime.Findings – The results show significant improvement in the pipe flow image resolution and measurement.Originality/...

PID controller design for an industrial hydraulic actuator with servo system

Electro-hydraulic system (EHS) 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. Mathematical model of EHS is required in order to design a controller for the system. In this paper, system identification technique is used for system modeling. Model of the system is estimated by using System Identification Toolbox in Matlab. This process began with collection of input and output data from experimental works. The data collected is used for model estimation. Auto Regressive with eXogeneous input (ARX) model is chosen as model structure of the system. Based on the input and output data of the system, best fit criterion and correlation analysis of the residual is analyze to determine the adequate model for representing the EHS system. By using Ziegler-Nichols tuning method, PID controller is designed for the model chosen through simulation in Simulink. In order to verify this controller, it is applied to the real time system and the performance of the system is monitored. The result obtained shows that the output of the system with controller in simulation mode and experimental works is almost similar. The output of the system also tracked the input given successfully.