Optimisation of the extended Kalman filter for speed estimation of induction motor drives

A speed sensorless drive requires the elimination of the sensor; therefore a speed estimator is required. Speed estimation using the Extended Kalman Filter (EKF) is investigated. The use of an EKF as an observer for a sensorless induction motor has been a longstanding subject of research. However, little attempt has been made to optimise the filter performance. First some speed estimation results are presented where the commonly used Trial and Error method is used for tuning the EKF. The performance of the EKF is strictly dependant on the choice of the covariance matrices. Therefore to improve the performance of the EKF, a guided random search technique, Simulated Annealing is proposed. The work concentrates on finding the EKF parameters by the Simulated Annealing algorithm in both low and high performance drives, for constant V/f and vector control. A Genetic Algorithm is also a guided random search technique and in this work the algorithm has been used for comparison purposes on optimising the EKF. The robustness of the EKF parameters tuned by Genetic Algorithm, Simulated Annealing and Trial and Error is compared. The results presented show that Simulated Annealing is more robust against machine parameter variations. Despite the large computation time Simulated Annealing does have the potential of being an alternative method for optimising the EKF. These novel results presented here show that Simulated Annealing is capable of tuning the EKF in the induction motor drives application.EThOS - Electronic Theses Online ServiceUniversiti Teknologi Malaysia (UTM)GBUnited Kingdo

Fire fighting robot

Fire-fighting is an important but dangerous occupation. A fire-fighter must be able to put out fire quickly and safely. This is a common way to prevent fatalities and further damages. So, technology has done its part by bridging up the gap between fire fighters and machineries. So, a robot is invented in order to combine both man kind and technology [1]. Fire Fighting Robot is designed to put out a fire, before it reaches out of control. Robot with these fire-handling abilities is a great advantage to replace fire extinguishers [2]. Water-based robot will be an advantage for users to refill the tank as it goes empty. Users can fill up water and keep the robot in a safe position. Water is a basic non-chemical liquid which will not experience any expiry or damage or corrosion. This invention would be a great contribution to mankind in order to ease their work and minimize the risk during fire put out

Development of Automatic Mixing Process for Fertigation System in Rock Melon Cultivation

This work proposed an automatic mixing system of nutrient solution for rock melon fertigation according to the required electrical conductivity (EC) level. Compared to the manual practice, this automatic system will ensure continuous supply of mixed nutrient solution without the need to daily check and mix new nutrient. Thus, this easy to use and low cost automatic system will reduce the burden of the farmers. This system uses an EC sensor to automatically check the concentration level of the mixed nutrient solution. Other than that, the system only consists of electronic pumps for mixing process and an Arduino board as the controller. The controller will monitor the EC level and run the mixing process when the EC level is below the required level. By calibrating the EC sensors, the test shows that the automatic mixing system is able to accurately keep the mixed nutrient solution concentration in a 400 L mixing reservoir at several required levels

Fault monitoring system for traffic light

Traffic light breakdown is very common. These create hassle as well as unsafe condition for road users. This project provides a new paradigm in traffic light monitoring system. The system has the capability to send multiple Short Message Service (SMS) to the contractor, traffic police and local council in the event of a malfunction traffic light. Normally, road users have to call the contractor based on the information displayed at the traffic light pole. With the current system, time taken to respond to the traffic light breakdown depends on how soon road users call the contractor. Monitoring system for fault traffic light will address this matter. In this project, the system can detect two types of failure, power failure and bulb/ Light Emitting Diode (LED) failure (a particular light not working i.e. red light only). Upon receiving the power failure signal, SMS will be sent to the above-mentioned parties for further action. For LED types of traffic light, the system has the capability to detect deterioration in function. If >50% of the LED for any light is not working the system will notify the contractor and other related parties to perform restorative action. The malfunction of LED can be detected by measuring real current vs the nominal current for that particular light. The seriousness of traffic light failure is divided into three parts, which are the total power failure, total LED failure and partial failure. The microcontroller analyzes the seriousness of the failure and sends the signal to a Global System for Mobile communications (GSM) module. Then the GSM module will send the details of failure including location and types of failure. For this project, LED was used as prototype of the traffic ligh

Agricultural rout planning with variable rate pesticide application in a greenhouse environment

The use of robotics in executing agricultural tasks has significantly improved productivity over the years as a result of automation in performing such activities as spray, harvesting, planting etc. In order to optimize both crop yield and quality while minimizing costs, there will be need for the application of navigation strategies. These will provide optimal as well as autonomous navigation capability which is built entirely upon field coverage plan thereby making robot navigation approach a paramount scheme. In this paper, the autonomy of an agricultural mobile robot is enhanced in a structured environment (greenhouse farm) to locate an optimum route such that the robot performs a selective and variable spray of pesticides to the plants. To realize this, a robust vehicle routing problem (VRP) scheme is designed to navigate the robot autonomously while making intelligent decisions to fulfil the pesticide demands at each node (infected plants). The improved non-dominated sorting genetic algorithm (INSGA-III) is adopted to solve this fully integer problem based on three (3) test cases carried out with 8, 32 and 56 infected plants respectively for validation. The results obtained show a trade-off solution as the Optimal INSGA-III is significantly lower than NSGA-III in terms of solution quality. On the other hand, a significant reduction in run times of between 66% and 76% and 76–93% was obtained for all test case scenarios for population sizes of 100 and 1500 respectively

Advancement of a smart fibrous capillary irrigation management system with an Internet of Things integration

This paper presents the development work for integrating an Internet of Things (IoT) with a fibrous capillary irrigation system based on the climatic demand estimated by the weather condition. The monitoring and control using an IoT system is critical for such application that is targeted for precision irrigation. The fibrous capillary irrigation system is managed by manipulating a water supply depth using the potential evapotranspiration (ETo). A soil mositure sensor was used to monitor the progress of the root water uptake and input the fuzzy logic system, to determine the water requirements for the crop medium. Experiment was conducted by using a Choy sum plant as the test crop grown in a greenhouse. The monitoring of the demand and management of the watering system was successful. The ETo data was able to approximate the crop water requirement in near real time

Improving Vector Evaluated Particle Swarm Optimisation by Incorporating Nondominated Solutions

The Vector Evaluated Particle Swarm Optimisation algorithm is widely used to solve multiobjective optimisation problems. This algorithm optimises one objective using a swarm of particles where their movements are guided by the best solution found by another swarm. However, the best solution of a swarm is only updated when a newly generated solution has better fitness than the best solution at the objective function optimised by that swarm, yielding poor solutions for the multiobjective optimisation problems. Thus, an improved Vector Evaluated Particle Swarm Optimisation algorithm is introduced by incorporating the nondominated solutions as the guidance for a swarm rather than using the best solution from another swarm. In this paper, the performance of improved Vector Evaluated Particle Swarm Optimisation algorithm is investigated using performance measures such as the number of nondominated solutions found, the generational distance, the spread, and the hypervolume. The results suggest that the improved Vector Evaluated Particle Swarm Optimisation algorithm has impressive performance compared with the conventional Vector Evaluated Particle Swarm Optimisation algorithm

DNA SEQUENCE DESIGN FOR DNA COMPUTATION BASED ON BINARY PARTICLE SWARM OPTIMIZATION

Abstract. Deoxyribonucleic Acid (DNA) has certain unique properties such as selfassembly and self-complementary in hybridization, whic

IoT-based monitoring and data-driven modelling of drip irrigation system for mustard leaf cultivation experiment

The changing dynamics, non-linearity of soil moisture content, as well as other weather and plant variables requires real-time monitoring and accurate predictive model for effective irrigation and crop management. In this paper, an improved monitoring and data-driven modelling of the dynamics of parameters affecting the irrigation of mustard leaf plant is presented. An IoT-based monitoring framework is implemented using ESPresso Lite V2.0 module interfaced with different soil moisture sensors (VH-400), flowmeter (YF-S201) as well as Davis vantage pro 2 weather station to measure soil moisture content, irrigation volume, and computation of the reference evapotranspiration (ETo). The data collected including plant images were transmitted to the Raspberry Pi 3 controller for onward online storage and the data are displayed on the IoT dashboard. The combination of both soil moisture and ETo values was used for scheduling a drip irrigated plant grown in a greenhouse for 35 days. A total number of 20, 703 experimental data samples are collected from the IoT-based platform was further used for data driven modelling through system identification in MATLAB. The result shows the development of different predictive models for soil moisture content prediction. The ARX prediction model is found to perform better than the ARMX, BJ and State space model in terms of estimated fit of 91.31%, 91.09%, 91.08%, and 90.75% respectively. Therefore, a robust monitoring framework for irrigation system has been developed, while the performance of the identified ARX model is promising to predict the volumetric soil water content