Performance comparison between PID and fuzzy logic controller in position control system of dc servomotor

The objective of this paper is to compare the time specification performance between conventional controller and artificial intelligence controller in position control system of a DC motor. This will include design and development of a GUI software using Microsoft Visual Basic 6.0 for position control system experiment. The scope of this research is to apply direct digital control technique in position control system. Two types of controller namely PID and fuzzy logic controller will be used to control the output response. An interactive software will be developed to visualize and analyze the system. This project consists of hardware equipment and software design. The hardware parts involve in interfacing MS150 Modular servo System and Data Acquisition System with a personal computer. The software part includes programming real-time software using Microsoft Visual Basic 6.0. Finally, the software will be integrated with hardware to produce a GUI position control system

MODELING AND CONTROLLER DESIGN FOR A COUPLEDTANK LIQUID LEVEL SYSTEM: ANALYSIS & COMPARISON

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 analyze

Identification And Non-Linear Control Strategy For Industrial Pneumatic Actuator

In this paper, a combination of nonlinear gain and proportional integral derivative (NPID) controller was proposed to the trajectory tracking of a pneumatic positioning system. The nonlinear gain was employed to this technique in order to avoid overshoot when a relatively large gain is used to produce a fast response. This nonlinear gain can vary automatically either by increasing or decreasing depending on the error generated at each instant. Mathematical model of a pneumatic actuator plant was obtained by using system identification based on input and output of open-loop experimental data. An auto-regressive moving average with exogenous (ARMAX) model was used as a model structure of the system. The results of simulation and experimental tests conducted for pneumatic system with different kind of input namely step, sinusoidal, trapezoidal and random waveforms were applied to evaluate the performance of the proposed technique. The results reveal that the proposed controller is better than conventional PID controller in terms of robust performance as well as show an improvement in its accuracy

Optimization of Modified Sliding Mode Control for an Electro-Hydraulic Actuator System with Mismatched Disturbance

This paper presents a modified sliding mode controller (MSMC) for tracking purpose of electro-hydraulic actuator system with mismatched disturbance. The main contribution of this study is in attempting to find the optimal tuning of sliding surface parameters in the MSMC using a hybrid algorithm of particle swarm optimization (PSO) and gravitational search algorithms (GSA), in order to produce the best system performance and reduce the chattering effects. In this regard, Sum square error (SSE) has been used as the objective function of the hybrid algorithm. The performance was evaluated based on the tracking error identified between reference input and the system output. In addition, the efficiency of the designed controller was verified within a simulation environment under various values of external disturbances. Upon drawing a comparison of PSOGSA with PSO and GSA alone, it was learnt that the proposed controller MSMC, which had been integrated with PSOGSA was capable of performing more efficiently in trajectory control and was able to reduce the chattering effects of MSMC significantly compared to MSMC-PSO and MSMC-GSA, respectively when the highest external disturbance, 10500N being injected into the system's actuator

DESIGN OF ADAPTIVE BACKSTEPPING WITH GRAVITATIONAL SEARCH ALGORITHM FOR NONLINEAR SYSTEM

Adaptive backstepping controller is designed for tracking purpose of nonlinear system with unknown parameter is injected to it. Gravitational search algorithm (GSA) is integrated with the designed controller in order to automatically tune its control parameters and adaptation gain since the tracking performance of the controller relies on these parameters. Performance evaluation is observed based on the tracking output and the tracking error between reference input and the system’s output. The effectiveness of the adaptive backstepping controller is verified by looking at the lowest amount value of Sum of Squared Error (SSE) attained from the simulation process. The results show that the system’s output follow the reference input given with remarkably small tracking error

Model Identification And Controller Design For An Electro-Pneumatic Actuator System With Dead Zone Compensation

Pneumatic actuator system is inexpensive, high power to weight ratio, cleanliness and ease of maintenance make it’s a choice compared to hydraulic actuator and electromagnetic actuator. Nonetheless, the steady state error of the system is high due to the dead zone of the valve. In this paper, an Auto-Regressive with External Input (ARX) model structure is chosen to represent the pneumatic actuator system. The recursive least square method is used to estimate the model parameters. The pole-assignment controller is then developed for position tracking. To cater the problem of high in steady state error, the dead zone compensation is added to the system. The dead zone controller was designed based on the inverse dead zone model and the dead zone compensation designed based on the desired error. The proposed method is then experimentally with varies load and compares with Nonlinear PID controller. The result shows that the proposed controller reduced the overshoot and steady state error of the pneumatic actuator system to no overshoot and 0.025mm respectively. Index terms: System identification, recursive least square, ARX, dead zone compensator, pneumatic actuato

Image Reconstruction Algorithm for Electrical Charge Tomography System

Abstract: Problem statement: Many problems in scientific computing can be formulated as inverse problem. A vast majority of these problems are ill-posed problems. In Electrical Charge Tomography (EChT), normally the sensitivity matrix generated from forward modeling is very ill-condition. This condition posts difficulties to the inverse problem solution especially in the accuracy and stability of the image being reconstructed. The objective of this study is to reconstruct the image cross-section of the material in pipeline gravity dropped mode conveyor as well to solve the ill-condition of matrix sensitivity. Approach: Least Square with Regularization (LSR) method had been introduced to reconstruct the image and the electrodynamics sensor was used to capture the data that installed around the pipe. Results: The images were validated using digital imaging technique and Singular Value Decomposition (SVD) method. The results showed that image reconstructed by this method produces a good promise in terms of accuracy and stability. Conclusion: This implied that LSR method provides good and promising result in terms of accuracy and stability of the image being reconstructed. As a result, an efficient method for electrical charge tomography image reconstruction has been introduced

Neural Network-Based Battery Management System for Through-the-Road Hybrid Electric Vehicle

Battery management system (BMS) plays a big role in the safety, performance, and longevity of batteries especially in sophisticated systems such as electrified vehicles. Among all the techniques involved in BMS, the state of charge (SOC) estimation is one of the most important elements as battery utilization depends heavily on it. Unlike other physical parameters, real-time monitoring of SOC is almost unattainable due to its non-linear characteristics which cannot be measured directly. Typically, indirect methods such as open circuit voltage (OCV) estimation and Coulomb counting are used to estimate the SOC level to a certain degree of accuracy, but these methods are not applicable to all types of batteries which raises the issue of reliability. This reliability concern is related to the efficiency of the main system as the recharging process is directly affected and might jeopardize the operational safety and usage of battery in electrified vehicles. An efficient and reliable BMS can prevent batteries from damages and improves the energy conversion efficiency which can lead to the lower fuel consumption in systems such as hybrid electric vehicles (HEV). In this paper, a neural network-based BMS (NN-BMS) is developed for a through-the-road hybrid electric vehicle (TtR HEV) focusing on the recharging capability of the TtR HEV. A real-time neural network SoC estimator is proposed and the BMS performance is evaluated in Simulink to observe the performance that improves the SOC management of the TtR HEV model by accumulating up to 46% of charging time under extreme condition on NEDC

controller. The result shows that the proposed controller reduced the overshoot and steady state error of the pneumatic actuator system to no overshoot and 0.025mm respectively. Index terms: System identification, recursive least square, ARX, dead zone compensator, pneumatic actuator

In this paper, a nonlinear mathematical modeling based on fundamental physical derivation is presented. The mass flow rate, pressure dynamic and equation of motion are derived referring to the previous research. Simulation work is done to confirm the model based on this derivation. Cascade control based on PID and P controller is designed through simulation in SIMULINK where the parameters of the controller are obtained through PID with optimization toolbox. The results reveal that both step and sinusoidal response test, the cascade controller consistently indicates outperform performance compared to classical PID method. In future, it is recommended to apply this technique to the real-time implementation

Sensing and filtering characteristics of electrostatic sensors for pneumatically conveyed particles

Electrostatic sensor, which can also be called as triboelectric sensor or electrodynamic sensor, senses the electrostatic charge carried by the dry particle in pneumatic conveyor. Source of the signal induced on the electrostatic sensor is brought by the object to be measured and no excitation circuit is necessary. Electrostatic sensors are used in the process industry due their low cost and robust. This paper describes an investigation into characteristics of circular and rectangular plate shapes of electrostatic sensors. Two parameters were investigated, the effect of sensor area on sensitivity and the spatial filtering effect of the sensor due to its finite size. Models were proposed and results obtained and used to compare with experimental values. It was observed that relationships existed between sensor sensitivity, sensor area and sensor spatial filtering effect