Fuzzy Logic for pH Neutralization Process

pH neutralization process is a process that is widely studied due to its highly nonlinear process reaction. Its nonlinearity behavior is caused by static nonlinearity between pH and concentration. This nonlinearity depends on the substances in the solution and on their concentrations. In this project, the nonlinearity of the process was investigated. Later, the mathematical model of the process was developed based on McAvoy et al [I]. In addition to the mathematical model, an empirical model was also obtained from Analytical & Chemical Pilot Plant located in the Process Control & Instrumentation Laboratory (23-00-06). Both models were then used to develop the Fuzzy Logic Controller (FLC) by using Advanced-Neuro Fuzzy Inference System (ANFIS) and also gain-scheduling method. In ANFIS implementation for empirical model, the FLC output was identical to the output from PID. Therefore it is concluded that FLC could be used to replace PID for empirical model. In ANFIS implementation for mathematical model, the FLC also could be implemented for mathematical model since the controlled variable successfully follows all the set point changes. For gainscheduling method, the FLC was tested on servo and regulator problems. The servo test was performed by using a random number generator to generate random pH set points between 3 and 11 and the simulation is performed for 100 seconds. The result for the servo test was similar with the result from the ANFIS implementation for mathematical model. For regulator test, the disturbance was the ±20% variation in acid flow. The result for the regulator shows, the controller manages to eliminate the disturbance effect in the process variable. In overall, the project successfully shows that FLC could be a good alternative to PID controller

Fuzzy Logic for pH Neutralization Process

pH neutralization process is a process that is widely studied due to its highly nonlinear process reaction. Its nonlinearity behavior is caused by static nonlinearity between pH and concentration. This nonlinearity depends on the substances in the solution and on their concentrations. In this project, the nonlinearity of the process was investigated. Later, the mathematical model of the process was developed based on McAvoy et al [I]. In addition to the mathematical model, an empirical model was also obtained from Analytical & Chemical Pilot Plant located in the Process Control & Instrumentation Laboratory (23-00-06). Both models were then used to develop the Fuzzy Logic Controller (FLC) by using Advanced-Neuro Fuzzy Inference System (ANFIS) and also gain-scheduling method. In ANFIS implementation for empirical model, the FLC output was identical to the output from PID. Therefore it is concluded that FLC could be used to replace PID for empirical model. In ANFIS implementation for mathematical model, the FLC also could be implemented for mathematical model since the controlled variable successfully follows all the set point changes. For gainscheduling method, the FLC was tested on servo and regulator problems. The servo test was performed by using a random number generator to generate random pH set points between 3 and 11 and the simulation is performed for 100 seconds. The result for the servo test was similar with the result from the ANFIS implementation for mathematical model. For regulator test, the disturbance was the ±20% variation in acid flow. The result for the regulator shows, the controller manages to eliminate the disturbance effect in the process variable. In overall, the project successfully shows that FLC could be a good alternative to PID controller

A review on the self energize structural health monitoring (SHM) in vertical axis wind turbine (VAWT) system

Wind energy is one of the renewable energy sources which the trend is positive and increasing year by year. This technology applied widely in several regions in the world and already has maturity in technology, good infrastructure and relative cost competitiveness. The application of structural health monitoring (SHM) is crucial especially to evaluate the performance of wind turbine in real time assessment. Furthermore, the smart material in SHM can be utilized as micro energy harvester as well. However, the application of SHM and micro energy harvester for wind turbine is still premature especially in SHM embedded or bonded strategy. Several issues are highlighted such as SHM material selection, wind turbine selection and the issue in micro energy harvester. The issues are discussed and compared with the recent finding in this review. Several recommendations are suggested for future study especially on the application of micro energy harverster

Students’ Inclination towards English Language as Medium of Instruction in the Teaching of Science and Mathematics

AbstractMalay language, the national language of Malaysia has been the medium of instruction for Science and Mathematics for the past four and a half decades in Malaysia. The government however changed the medium of instruction of these subjects to English in January 2003. The “Teaching and Learning of Science and Mathematics in English” (PPSMI) policy was implemented in all primary and secondary schools. It aims to improve the English language proficiency among students as well as the learning and achievement level in science and mathematics. This paper presents findings of the study on students’ inclination towards English language as medium of instruction in teaching and learning of Science and Mathematics in Higher Learning Institutions in Malaysia. The respondents were 291 undergraduate students from the Faculty of Science and Technology (FST) and Faculty of Education (FPEND) of Universiti Kebangsaan Malaysia (UKM). A questionnaire pertaining to students’ inclination was used as research instrument. Using descriptive statistics, ANOVA and t-test, the study found that undergraduate students of FST and FPEND had an inclination towards English as medium of instruction in the teaching and learning of Science and Mathematics. Using the Post-Hoc test, it is found that Indian students and students from other races than Malay and Chinese have greater inclination towards English as medium of instruction in teaching and learning of Science and Mathematics in UKM for both faculties. However, FST students who studied in Mandarin and Tamil at pre-university level (STPM) had higher inclination compared to those who used Malay language or even English

The influence of tree induce suction on soil suction profiles

This study provided an investigation of active root tree zone located at the toe of the slope. This section of slope generated suction due to tree water uptake during dry season. A field monitoring set up program was carried out to collect matric suction data at slope with absent of a tree and with a tree located at toe of the slope. The installations of Jet-fill tensiometer and Gypsum blocks to measured matric suction were placed at vicinity of tree with certain depths and distances. The distribution in matric suction values and matric suction profiles responses to tree water uptake and rainfall were investigated. The decreased of soil matric suction after intense rainfall in this monitoring period as a function of an initial condition before the water uptake driven by active root tree substantially increased matric suction (low moisture content). Matric suction significantly increased at vicinity of tree trunk located at toe of slope compared to the slope without tree. This exploration provides the viewed of mature tree can significantly alter the suction distribution driven by transpiration in an unsaturated soil slope. It takes consideration by preserved mature tree can improved soil properties in geotechnical slope design

DEVELOPMENT OF SOFT SENSOR TO ESTIMATE MULTIPHASE FLOW RATES USING NEURAL NETWORKS AND EARLY STOPPING

This paper proposes a soft sensor to estimate phase flow rates utilizing common measurements in oil and gas production wells. The developed system addresses the limited production monitoring due to using common metering facilities. It offers a cost-effective solution to meet real-time monitoring demands, reduces operational and maintenance costs, and acts as a back-up to multiphase flow meters. The soft sensor is developed using feed-forward neural network, and generalization and network complexity are regulated using K-fold cross-validation and early stopping technique. The soft sensor is validated using actual well test data from producing wells, and model performance is analyzed using cumulative deviation and cumulative flow plots. The developed soft sensor shows promising performance with a mean absolute percent error of around 4% and less than 10% deviation for 90% of the samples

Design requirements for new food delivery and waste collection system onboard commercial transport aircraft

The objective of this paper is to identify the driving needs for an improved food delivery and waste collection system to be implemented onboard of the commercial passenger transport aircraft. Quality Function Deployment (QFD) method has been applied to establish the design requirements from the point of view of the passengers and airlines. The collected data from conducted public survey and also interview sessions with the experts from the airlines are utilized to construct the House of Quality (HOQ). In short, it has been found that safety and cleanliness are the two top prioritized design requirements for a new food delivery and waste collection system. On the other hand, the type of carriage, overall profile of the system and also the operating mechanism used for the system are top technical design parameters that can influence the successful achievement of the design requirements. Findings from this study will be further utilized to generate design options for the improved food delivery and waste collection system