DESIGN AND IMPLEMENT DYNAMIC PROGRAMMING BASED DISCRETE POWER LEVEL SMART HOME SCHEDULING USING FPGA

With the development and capabilities of the Smart Home system, people today are entering an era in which household appliances are no longer just controlled by people, but also operated by a Smart System. This results in a more efficient, convenient, comfortable, and environmentally friendly living environment. A critical part of the Smart Home system is Home Automation, which means that there is a Micro-Controller Unit (MCU) to control all the household appliances and schedule their operating times. This reduces electricity bills by shifting amounts of power consumption from the on-peak hour consumption to the off-peak hour consumption, in terms of different “hour price”. In this paper, we propose an algorithm for scheduling multi-user power consumption and implement it on an FPGA board, using it as the MCU. This algorithm for discrete power level tasks scheduling is based on dynamic programming, which could find a scheduling solution close to the optimal one. We chose FPGA as our system’s controller because FPGA has low complexity, parallel processing capability, a large amount of I/O interface for further development and is programmable on both software and hardware. In conclusion, it costs little time running on FPGA board and the solution obtained is good enough for the consumers.

DESIGN AND IMPLEMENTATION OF HOME USE PORTABLE SMART ELECTRONICS

The widespread of low cost embedded electronics makes it easier to implement the smart devices that can understand either the environment or the user behaviors. The main object of this project is to design and implement home use portable smart electronics, including the portable monitoring device for home and office security and the portable 3D mouse for convenient use. Both devices in this project use the MPU6050 which contains a 3 axis accelerometer and a 3 axis gyroscope to sense the inertial motion of the door or the human hands movement. For the portable monitoring device for home and office security, MPU6050 is used to sense the door (either home front door or cabinet door) movement through the gyroscope, and Raspberry Pi is then used to process the data it receives from MPU6050, if the data value exceeds the preset threshold, Raspberry Pi would control the USB Webcam to take a picture and then send out an alert email with the picture to the user. The advantage of this device is that it is a small size portable stand-alone device with its own power source, it is easy to implement, really cheap for residential use, and energy efficient with instantaneous alert. For the 3D mouse, the MPU6050 would use both the accelerometer and gyroscope to sense user hands movement, the data are processed by MSP430G2553 through a digital smooth filter and a complementary filter, and then the filtered data will pass to the personal computer through the serial COM port. By applying the cursor movement equation in the PC driver, this device can work great as a mouse with acceptable accuracy. Compared to the normal optical mouse we are using, this mouse does not need any working surface, with the use of the smooth and complementary filter, it has certain accuracy for normal use, and it is easy to be extended to a portable mouse as small as a finger ring.

AGENT BASED, DISTRIBUTED CONTROL STRATEGIES AND OPTIMIZATION OF PLUG-IN ELECTRIC VEHICLES ON SMART/MICROGRID ARCHITECTURES

This thesis will present strategies for the use of plug-in electric vehicles on smart and microgrids. MATLAB is used as the design tool for all models and simulations. First, a scenario will be explored using the dispatchable loads of electric vehicles to stabilize a microgrid with a high penetration of renewable power generation. Grid components for a microgrid with 50% photovoltaic solar production will be sized through an optimization routine to maintain storage system, load, and vehicle states over a 24-hour period. The findings of this portion are that the dispatchable loads can be used to guard against unpredictable losses in renewable generation output. Second, the use of distributed control strategies for the charging of electric vehicles utilizing an agent-based approach on a smart grid will be studied. The vehicles are regarded as additional loads to a primary forecasted load and use information transfer with the grid to make their charging decisions. Three lightweight control strategies and their effects on the power grid will be presented. The findings are that the charging behavior and peak loads on the grid can be reduced through the use of distributed control strategies.

Computer Aided Design Algorithmic Technique for Very Large Scale Integrated Circuit Design and Smart Home Embedded System Design

To tackle the challenges at circuit level and system level VLSI and embedded system design, this dissertation proposes various novel algorithms to explore the efficient solutions. At the circuit level, a new reliability-driven minimum cost Steiner routing and layer assignment scheme is proposed, and the first transceiver insertion algorithmic framework for the optical interconnect is proposed. At the system level, a reliability-driven task scheduling scheme for multiprocessor real-time embedded systems, which optimizes system energy consumption under stochastic fault occurrences, is proposed. The embedded system design is also widely used in the smart home area for improving health, wellbeing and quality of life. The proposed scheduling scheme for multiprocessor embedded systems is hence extended to handle the energy consumption scheduling issues for smart homes. The extended scheme can arrange the household appliances for operation to minimize monetary expense of a customer based on the time-varying pricing model.

ADVANCED COMPUTATIONAL MODELING OF THE INTERNAL STRUCTURE OF SMART WIND-TURBINE BLADES

Implementation of stable aeroelastic models with the ability to capture the complex features of Multi concept smartblades is a prime step in reducing the uncertainties that come along with blade dynamics. The numerical simulations of fluid structure interaction can thus be used to test a realistic scenarios comprising of full-scale blades at a reasonably low computational cost. A code which was a combination of two advanced numerical models was designed and was run with the help of paralell HPC supercomputer platform. The first model was based on a variation of dimensional reduction technique proposed by Hodges and Yu. This model was the one to record the structural response of heterogenous composite blades. This technique reduces the geometrical complexities of the heterogenous blade section into a stiffness matrix for an equivalent beam. This derived equivalent 1-D strain energy matrix is similar to the actual 3-D strain energy matrix in an asymptotic sense. As this 1-D matrix helps in accurately modeling the blade structure as a 1-D finite element problem, this substantially redues the computational effort and subsequently the computational cost that are required to model the structural dynamics at each step. Second model comprises of implementation of the Blade Element Momentum Theory. In this approach we map all the velocities and the forces with the help of orthogonal matrices that help in capturing the large deformations and the effects of rotations in calculating the aerodynamic forces. This ultimately helps us to take into account the complex flexo torsional deformations. In this thesis we have succesfully tested these computayinal tools developed by MTU’s research team lead by for the aero elastic analysis of wind-turbine blades. The validation in this thesis is majorly based on several experiments done on NREL-5MW blade, as this is widely accepted as a benchmark blade in the wind industry. Along with the use of this innovative model the internal blade structure was also changed to add up to the existing benefits of the already advanced numerical models.

STUDIES OF FUNCTIONALIZED NANOPARTICLES FOR SMART SELF-ASSEMBLY AND AS CONTROLLED DRUG DELIVERY

This dissertation is related to the studies of functionalized nanoparticles for self-assembly and as controlled drug delivery system. The whole topic is composed of two parts. In the first part, the research was conducted to design and synthesize a new type of ionic peptide-functionalized copolymer conjugates for self-assembly into nanoparticle fibers and 3D scaffolds with the ability of multi-drug loading and governing the release rate of each drug for tissue engineering. The self-assembly study confirmed that such peptide-functionalized amphiphilic copolymers underwent different self-assembly behavior. The bigger nanoparticles were more easily assembled into nanoparticle fibers and 3D scaffolds with larger pore size, while the smaller nanoparticle underwent faster self-assembly to form more compact 3D scaffolds with smaller porosity but more stable structure. Controlled release studies confirmed the ability of governing simultaneous release of different model drugs with independent release rate from a same scaffold. Cytotoxicity tests showed that all synthesized peptides, copolymers and peptide-copolymer conjugates were biocompatible with SW-620 cell lines and NIH3T3 cell lines. This new type of self-assembled scaffolds combined the advantages of peptide nanofibers and versatile controlled release of polymeric nanoparticles to achieve simultaneous multi-drug loading and controlled release of each drug, uniform distribution and flexibility of hydrogel scaffolds. The investigations in second part were first to design and synthesize organic biocide-loaded nanoparticles for low-leaching wood preservation using a cost-effective one-pot method to synthesize amphiphilic chitosan-g-PMMA nanoparticles loading with ~25-28 wt.% of the fungicide tebuconazole with particle size of ~100 nm diameter by FESEM. FESEM analysis confirmed efficient penetration of nanoparticles throughout the treated wooden stake with dimension of 19 × 19 × 455 mm^3. Leaching studies showed that biocide introduced into sapwood via nanoparticles leached only ~9% compared with the amount leached from tebuconazole solution-treated control, while soil jar tests showed that the nanoparticle-treated wood blocks were effectively protected from biological decay tested against G. trabeum, a brown rot fungus. Copper oxide nanoparticles with and without polymer stabilizers were also investigated to use as inorganic wood preservatives to clarify the factor affecting copper leaching from treated wood. Copper oxide nanoparticles with uniform diameters of ~10 nm and ~50 nm were prepared, and the leachates from southern pine sapwood treated with these nanoparticles were analyzed. It was found by TEM and EDS analysis that significant numbers of nanoparticles leached from the treated wood. The 50 nm nanoparticles leached slightly less than a soluble copper salt control, but 10 nm nanoparticles leached substantially more than the control. The effect of polymer stabilizers on nanoparticle leaching was also investigated. Results showed that polymer stabilizers increased leaching. The trends showed that nanoparticle size was a major factor in copper leaching.