The output power variability of intermittent renewable sources can cause significant fluctuations in distribution system voltages. A local linear controller that exploits the capability of a photovoltaic inverter to provide both real and reactive power is described. This controller substitutes reactive power for real power when fluctuations in the output of the photovoltaic source are experienced. In this way, the inverter can help mitigate distribution system voltage fluctuations. In order to provide real and reactive to the grid, a three-phase grid-connected single-stage photovoltaic system with maximum power point tracking and power control is described. A method of reducing the current harmonic caused by resonance of the LC filter and transformer is presented. The local linear controller is examined using an example distribution system, and it is found that the controller is effective at mitigating voltage violations. The photovoltaic control system is examined using three-phase single-stage PV inverter system. The power control and damping system show good performance and stability under rapid change of irradiance.

Humidity measurement has been increasingly important in many industries and process control applications. This thesis research focus mainly on humidity sensor calibration and characterization. The humidity sensor instrumentation is briefly described. The testing infrastructure was designed for sensor data acquisition, in order to compensate the humidity sensor’s temperature coefficient, temperature chambers using Peltier elements are used to achieve easy-controllable stable temperatures. The sensor characterization falls into a multivariate interpolation problem. Neuron networks is tried for non-linear data fitting, but in the circumstance of limited training data, an innovative algorithm was developed to utilize shape preserving polynomials in multiple planes in this kind of multivariate interpolation problems.

This dissertation aims at developing techniques to achieve high power density in motor drives under the performance requirements for transportation system. Four main factors influencing the power density are the main objects of the dissertation: devices, passive components, pulse width modulation (PWM) methods and motor control methods. Firstly, the application of SiC devices could improve the power density of the motor drive. This dissertation developed a method of characterizing the SiC device performance in phase-leg with loss estimation, and claimed that with SiC Schottky Barrier Diode the advantage of SiC JFET could benefit the motor drive especially at high temperature. Then the design and improvement of the EMI filter in the active front-end rectifier of the motor drive was introduced in this dissertation. Besides the classical filter design method, the parasitic parameters in the passive filter could also influence the filtering performance. Random PWM could be applied to reduce the EMI noise peak value. The common-mode (CM) noise reduction by PWM methods is also studied in this dissertation. This dissertation compared the different PWM methods’ CM filtering performance. Considering the CM loop, the design of PWM methods and switching frequency should be together with the CM impedance. Variable switching frequency PWM (VSFPWM) methods are introduced in the dissertation for the motor drive’s EMI and loss improvement. The current ripple of the three-phase converter could be predicted. Then the switching frequency could be designed to adapt the current ripple requirements. Two VSFPWM methods are introduced to satisfy the ripple current peak and RMS value requirements. For motor control issue, this dissertation analyzed the principle of the start-up transient and proposed an improved start-up method. The transient was significantly reduced and the motor could push to high speed and high power with speed sensorless control. Next, the hardware development of modular motor drive was introduced. The development and modification of 10kW phase-legs and full power test of a typical 30kW modular converter is realized with modular design method. Finally, the techniques developed in this dissertation for high power density motor drive design and control are summarized and future works are proposed.

Solar energy is an abundant renewable source, which is expected to play an increasing role in the grid's future infrastructure for distributed generation. The research described in the thesis focuses on the analysis of integrating multi-megawatt photovoltaics (PV) systems with battery energy storage into the existing grid and on the theory supporting the electrical operation of components and systems. The PV system is divided into several sections, each having its own DC-DC converter for maximum power point tracking and a two-level grid connected inverter with different control strategies. The functions of the battery are explored by connecting it to the system in order to prevent possible voltage fluctuations and as a buffer storage in order to eliminate the power mismatch between PV array generation and load demand. Computer models of the system are developed and implemented using the PSCADTM/EMTDCTM software.

The modern smart grid would involve deep integration between measurement nodes, communication systems, artificial intelligence, power electronics and distributed resources. On one hand, this type of integration can dramatically improve the grid performance and efficiency, but on the other, it can also introduce new types of vulnerabilities to the grid. To obtain the best performance, while minimizing the risk of vulnerabilities, the physical power system must be designed as a security aware system. In this dissertation, an interoperability and communication framework for microgrid control and Cyber Physical system enhancements is designed and implemented taking into account cyber and physical security aspects. The proposed data-centric interoperability layer provides a common data bus and a resilient control network for seamless integration of distributed energy resources. In addition, a synchronized measurement network and advanced metering infrastructure were developed to provide real-time monitoring for active distribution networks. A hybrid hardware/software testbed environment was developed to represent the smart grid as a cyber-physical system through hardware and software in the loop simulation methods. In addition it provides a flexible interface for remote integration and experimentation of attack scenarios. The work in this dissertation utilizes communication technologies to enhance the performance of the DC microgrids and distribution networks by extending the application of the GPS synchronization to the DC Networks. GPS synchronization allows the operation of distributed DC-DC converters as an interleaved converters system. Along with the GPS synchronization, carrier extraction synchronization technique was developed to improve the system’s security and reliability in the case of GPS signal spoofing or jamming. To improve the integration of the microgrid with the utility system, new synchronization and islanding detection algorithms were developed. The developed algorithms overcome the problem of SCADA and PMU based islanding detection methods such as communication failure and frequency stability. In addition, a real-time energy management system with online optimization was developed to manage the energy resources within the microgrid. The security and privacy were also addressed in both the cyber and physical levels. For the physical design, two techniques were developed to address the physical privacy issues by changing the current and electromagnetic signature. For the cyber level, a security mechanism for IEC 61850 GOOSE messages was developed to address the security shortcomings in the standard.

This thesis presents the design of uBot-7, the latest version of a dexterous mobile manipulator. This platform has been iteratively developed to realize a high performance-to-cost dexterous whole body manipulator with respect to mobile manipulation. The semi-anthropomorphic design of the uBot is a demonstrated and functional research platform for developing advanced autonomous perception, manipulation, and mobility tasks. The goal of this work is to improve the uBot’s ability to sense and interact with its environment in order to increase the platforms capability to operate dexterously, through the incorporation of joint torque feedback, and safely, through the implementation of passive and active compliance. This is accomplished through incorporating series elastic actuators in its arms and torso joints, improving the mechanical design to reduce backlash, and incorporating impedance controllers in the robot. The focus of this thesis is the development of the mechanical, sensor, and controller design for the uBot-7 platform. An impedance controller is developed and evaluated on a bench top prototype series elastic actuator.

Autonomous vehicle navigation is a complex and challenging task. Land and aerial vehicles often use highly accurate GPS sensors to localize themselves in their environments. These sensors are ineffective in underwater environments due to signal attenuation. Autonomous underwater vehicles utilize one or more of the following approaches for successful localization and navigation: inertial/dead-reckoning, acoustic signals, and geophysical data. This thesis examines autonomous localization in a simulated environment for an OpenROV Underwater Drone using a Kalman Filter. This filter performs state estimation for a dead reckoning system exhibiting an additive error in location measurements. We evaluate the accuracy of this Kalman Filter by analyzing the effect each parameter has on accuracy, then choosing the best combination of parameter values to assess the overall accuracy of the Kalman Filter. We find that the two parameters with the greatest effects on the system are the constant acceleration and the measurement uncertainty of the system. We find the filter employing the best combination of parameters can greatly reduce measurement error and improve accuracy under typical operating conditions.

It is well known that real op-amps do not share most of the desirable characteristics of an ideal one, particularly those of gain and output impedance. When presented with a capacitive load, such as a MOSFET or ADC, feedback in an op-amp circuit can quickly become unstable. This thesis studies and characterizes an op-amp’s output impedance and how its interaction with this type of load creates a parasitic pole which leads to instability. Applying ideas from feedback control theory, a model for studying the problem is developed from which a generalized method for compensating the undesirable circumstance is formulated. Even in a zero-input state, many real op-amps driving capacitive loads can experience unforced oscillations. A case study is performed with three commonly used devices. First, the output impedance is determined by its dependence on the unity-gain bandwidth, load capacitance, and oscillation frequency. It is fitted into a second-order feedback control model that allows for an analytical study of the problem. It is then shown that a carefully designed passive network can be introduced between the load and op-amp to obtain a properly damped system free of oscillation and well-behaved. Using a shunt resistor is a known and commonly used method for lowering an op-amp’s output impedance to gain stability. This work considers the converse addition of a series capacitor to instead lower the load capacitance seen by the op-amp, a seemingly complementary method that achieves the same goal. A generalized, composite compensation method is developed that uses both the shunt resistor and series capacitor– a strategy not yet found in literature. Relevant formulas for damping ratio and natural frequency are derived that allow the design of a passive compensation network. Furthermore, tradeoffs between compensation, voltage swing, current consumption, and power usage are considered. An emphasis is placed on comparing simulated versus real circuits to highlight the fact that any problem is much worse in real-life than in a simulation. SPICE models and programs aim to de-idealize certain device characteristics, but often cannot account for environmental conditions and manufacturing variance. Thus, an importance is placed on experimental verification guided by simulations.

Contactless Electric Vehicle (EV) charging based on magnetic resonant induction is an emerging technology that can revolutionize the future of the EV industry and transportation systems by enabling an automated and convenient charging process. However, in order to make this technology an acceptable alternative for conventional plug-in charging systems it needs to be optimized for different design measures. Specifically, the efficiency of an inductive EV charging system is of a great importance and should be comparable to the efficiency of conventional plug-in EV chargers. The aim of this study is to develop solutions that contribute to the design enhancement of inductive EV charging systems. Specifically, generalized physics-based design optimization methods that address the trade-off problem between several key objectives including efficiency, power density, misalignment tolerance, and cost efficiency considering critical constraints are developed. Using the developed design methodology, a 3.7kW inductive charging system with square magnetic structures is investigated as a case study and a prototype is built to validate the optimization results. The developed prototype achieves 93.65% efficiency (DC-to-DC) and a power density of 1.65kW/dm3. Also, self-tuning power transfer control methods with resonance frequency tracking capability and bidirectional power transfer control are presented. The proposed control methods enhance the efficiency of power converters and reduce the Electromagnetic Interference (EMI) by enabling soft-switching operations. Several simplified digital controllers are developed and experimentally implemented. The controllers are implemented without the use of DSP/FPGA solutions. Experimental tests show that of the developed simplified controllers can effectively regulate the power transfer around the desired value. Moreover, the experiments show that compared to conventional converters, the developed converters can achieve 4% higher efficiency at low power levels. Moreover, enhanced matrix converter topologies that can achieve bidirectional power transfer and high efficiency with a reduced number of switching elements are introduced. The self-tuning controllers are utilized to design and develop control schemes for bidirectional power transfer regulation. The simulation analyses and experimental results show that the developed matrix converters can effectively establish bidirectional power transfer at the desired power levels with soft-switching operations and resonance frequency tracking capability. Specifically, a direct three-phase AC-AC matrix converter with a reduced number of switches (only seven) is developed and built. It is shown that the developed converters can achieve efficiencies as high as 98.54% at high power levels and outperform conventional two-stage converters.

The Cal Poly Sustainable Power for Electrical Resources (SuPER) project is a solar power DC distribution system designed to autonomously manage and supply the energy needs of a single family off-the-grid home. The following thesis describes the improvement and re-design of a MATLAB Simulink model for the Cal Poly SuPER system. This model includes a photovoltaic (PV) array, a lead-acid gel battery with temperature effects, a wind turbine model, a re-designed DC-DC converter, a DC microgrid, and multiple loads. This thesis will also include several control algorithms such as a temperature controlled thermoelectric (T.E.) cooler, intelligent load switching, and an intelligent power source selector. Furthermore, a seven day simulation and evaluation of the results are presented. This simulation is an important tool for further system development, re-design, and long term system performance prediction.