Abstract

In the 21 century, manufacturing companies face increasingly frequent and unpredictable market changes driven by global competition, including the rapid introduction of new products and constantly varying product demand. To remain competitive, companies must design manufacturing systems that not only produce high-quality products at low costs, but also which allow for rapid response to market changes and consumer needs. Complex Discrete Event Simulation Systems like Flexible Manufacturing systems necessitate the complete utilization of available resources to optimize their productivity. One important objective of scheduling in FMS systems is to increase resource utilization and reduce idle time. In this paper, scheduling is modeled as a Multi Objective Optimization Problem, with primary objective for picking a schedule which has very less Combined Objective Function (COF) value. Most of the optimization functions proposed in the literature have penalties incorporated in them when the scheduled job is not completed in the specified time. The authors have incorporated a reward for each job if the job is completed ahead of time. Such an approach has led to the increase in efficiency of the system.

Complex machining operations configured in the existing setup of FMS having 6 Machines producing 3 different parts through 3 alternative routes is considered for this work. An automated tool in the form of Graphical User Interface (GUI) is designed to automate the optimization of scheduling process by searching for solution in the search spaces using Bacterial Foraging Optimization Algorithm (BFOA), Genetic algorithm (GA) and Differential Evolution (DE) approaches and choose the best for that scenario. The inclusion of reward along with the penalty value as one of the parameters in the Combined Objective Function has yielded expected results in increasing the efficiency of the scheduling process in way of reduced machine idle time and reduced penalties.

Abstract

This project shows the use of optimization techniques for DC-DC buck and boost converter. Nowadays, dc-dc converters are used in many applications. The sliding mode control based on variable structure system theory has been examined by buck and boost switching mode converter type. In this project, the dynamics response of both buck and boost converter can be increased by using some optimization techniques. The sliding mode control strategy has been proposed to ensure system stability even when the large input voltage and load variation, and the dynamic response can be increased. The sliding surface has been selected by assigning the poles combined with genetic algorithm which it will give sliding regime. The simulation result of the proposed genetic algorithm based SMC strategy is compared with the existing SMC. The proposed GA based SMC gives considerable improvement in faster output voltage response during load variation.

Abstract

This thesis deals with the creation of a device that will climb towering palms to harvest (primarily) coconuts. It will foster not only a love for engineering, designing, and inventing, but also a feeling of pride and accomplishment in helping people who live in coconut-harvesting countries. There are no 100% safe coconut-harvesting devices currently in the market. Although there have been efforts made by many inventors, the most similar contraption is a coconut-climbing assistance device that assures efficiency, but not necessarily safety. The proposed coconut-climbing device will attempt to address both efficiency and safety. The design of the device has to be simple and enough for villagers to operate, yet work efficiently to appeal to the majority. Other design obstacles include creating a multi-axis arm, allowing the villagers to observe what is happening at the top of the tree, and maintaining the friction between the device and the tree when the device ascends and descends. A coconut plucking robot is created in hopes of saving lives and improving the living standards of many coconut-climbers.

Abstract

Brushless DC motors are widely used for many applications like industrial automation, home appliances and medical equipment because of their low EMI ,high efficiency, commutation done on windings and high reliability. This paper presents the simulation results of fuzzy logic and conventional PI controller for the position sensorless speed control of permanent magnet brushless DC motor. It is difficult to tune the parameter and get satisfied control characteristics by using conventional controller. Furthermore PI controller requires accurate mathematical model, as the Fuzzy logic controller has the ability to obtain satisfied control characteristics and it is easy for computing. The experiment results show the comparison of a fuzzy logic controller that has better performance than PI controller. The modeling, control and simulation of the BLDC motor have been done using the software package MATLAB/SIMULINK.

Abstract

Under partial shading conditions, multiple peaks are observed in the power-voltage (P-V) characteristics curve of a photovoltaic (PV) array, and conventional maximum power point tracking (MPPT) algorithm may fail to track the global maximum power point (GMPP). In this paper a fuzzy-logic controller for global maximum power point tracking (GMPPT) is proposed to increase the performance during partial shading condition. A mathematical model of the PV system under partial shading conditions is derived. The proposed fuzzy logic based controller is implemented in MATLAB- SIMULINK.