Adaptive control of sinusoidal brushless DC motor actuators

Electrical Power Assisted Steering system (EPAS) will likely be used on future automotive power steering systems. The sinusoidal brushless DC (BLDC) motor has been identified as one of the most suitable actuators for the EPAS application. Motor characteristic variations, which can be indicated by variations of the motor parameters such as the coil resistance and the torque constant, directly impart inaccuracies in the control scheme based on the nominal values of parameters and thus the whole system performance suffers. The motor controller must address the time-varying motor characteristics problem and maintain the performance in its long service life. In this dissertation, four adaptive control algorithms for brushless DC (BLDC) motors are explored. The first algorithm engages a simplified inverse dq-coordinate dynamics controller and solves for the parameter errors with the q-axis current (iq) feedback from several past sampling steps. The controller parameter values are updated by slow integration of the parameter errors. Improvement such as dynamic approximation, speed approximation and Gram-Schmidt orthonormalization are discussed for better estimation performance. The second algorithm is proposed to use both the d-axis current (id) and the q-axis current (iq) feedback for parameter estimation since id always accompanies iq. Stochastic conditions for unbiased estimation are shown through Monte Carlo simulations. Study of the first two adaptive algorithms indicates that the parameter estimation performance can be achieved by using more history data. The Extended Kalman Filter (EKF), a representative recursive estimation algorithm, is then investigated for the BLDC motor application. Simulation results validated the superior estimation performance with the EKF. However, the computation complexity and stability may be barriers for practical implementation of the EKF. The fourth algorithm is a model reference adaptive control (MRAC) that utilizes the desired motor characteristics as a reference model. Its stability is guaranteed by Lyapunov’s direct method. Simulation shows superior performance in terms of the convergence speed and current tracking. These algorithms are compared in closed loop simulation with an EPAS model and a motor speed control application. The MRAC is identified as the most promising candidate controller because of its combination of superior performance and low computational complexity. A BLDC motor controller developed with the dq-coordinate model cannot be implemented without several supplemental functions such as the coordinate transformation and a DC-to-AC current encoding scheme. A quasi-physical BLDC motor model is developed to study the practical implementation issues of the dq-coordinate control strategy, such as the initialization and rotor angle transducer resolution. This model can also be beneficial during first stage development in automotive BLDC motor applications.

SPACECRAFT ATTITUDE CONTROL USING MAGNETIC ACTUATORS

This report presents a study on the problem of spacecraft attitude control using magnetic actuators. Several existing approaches are reviewed and one control strategy is implemented and simulated. A time-varying feedback control law achieving inertial pointing for magnetically actuated spacecraft is implemented. The report explains the modeling of the spacecraft rigid body dynamics, kinematics and attitude control in detail. Besides the fact that control laws have been established for stabilization around local equilibrium, this report presents the results of a control law that yields a generic, global solution for attitude stabilization of a magnetically actuated spacecraft. The report also involves the use MATLAB as a tool for both modeling and simulation of the spacecraft and controller. In conclusion, the simulation outlines the performance of the controller in independently stabilizing the spacecraft in three mutually perpendicular directions.

Active surgical positioning device for a cochlear implant electrode array

Cochlear implants have been of great benefit in restoring auditory function to individuals with profound bilateral sensorineural deafness. The implants are used to directly stimulate auditory nerves and send a signal to the brain that is then interpreted as sound. This project focuses on the development of a surgical positioning tool to accurately and effectively place an array of stimulating electrodes deep within the cochlea. This will lead to improved efficiency and performance of the stimulating electrodes, reduced surgical trauma to the cochlea, and as a result, improved overall performance to the implant recipient. The positioning tool reported here consists of multiple fluidic chambers providing localized curvature control along the length of the attached silicon electrode array. The chambers consist of 200μm inner diameter PET (polyethylene therephthalate) tubes with 4μm wall thickness. The chambers are molded in a tapered helical configuration to correspond to the cochlear shape upon relaxation of the actuators. This ensures that the optimal electrode placement within the cochlea is retained after the positioning tool becomes dormant (for chronic implants). Actuation is achieved by injecting fluid into the PET chambers and regulating the fluidic pressure. The chambers are arranged in a stacked, overlapping design to provide fluid connectivity with the non-implantable pressure controller and allow for local curvature control of the device. The stacked tube configuration allows for localized curvature control of various areas along the length of the electrode and additional stiffening and actuating power towards the base. Curvature is affected along the entire length of a chamber and the result is cumulative in sections of multiple chambers. The actuating chambers are bonded to the back of a silicon electrode array.

Localized annealing of polysilicon microstructures by inductively heated ferromagnetic films

The monolithic integration of dissimilar microsystems is often limited by conflicts in thermal budget. One of the most prevalent examples is the fabrication of active micro-electromechanical systems (MEMS), as structural films utilized for surface micromachining such as polysilicon typically require processing at temperatures unsuitable for microelectronic circuitry. A localized annealing process could provide for the post-deposition heat treatment of integrated structures without compromising active devices. This dissertation presents a new microfabrication technology based on the inductive heating of ferromagnetic films patterned to define regions for heat treatment. Support is provided through theory, finite-element modeling, and experimentation, concluding with the demonstration of inductive annealing on polysilicon inertial sensing structures. Though still in its infancy, the results confirm the technology to be a viable option for integrated MEMS as well as any microsystem fabrication process requiring a thermal gradient.

Porous silicon technology for integrated microsystems

With the development of micro systems, there is an increasing demand for integrable porous materials. In addition to those conventional applications, such as filtration, wicking, and insulating, many new micro devices, including micro reactors, sensors, actuators, and optical components, can benefit from porous materials. Conventional porous materials, such as ceramics and polymers, however, cannot meet the challenges posed by micro systems, due to their incompatibility with standard micro-fabrication processes. In an effort to produce porous materials that can be used in micro systems, porous silicon (PS) generated by anodization of single crystalline silicon has been investigated. In this work, the PS formation process has been extensively studied and characterized as a function of substrate type, crystal orientation, doping concentration, current density and surfactant concentration and type. Anodization conditions have been optimized for producing very thick porous silicon layers with uniform pore size, and for obtaining ideal pore morphologies. Three different types of porous silicon materials: meso porous silicon, macro porous silicon with straight pores, and macro porous silicon with tortuous pores, have been successfully produced. Regular pore arrays with controllable pore size in the range of 2µm to 6µm have been demonstrated as well. Localized PS formation has been achieved by using oxide/nitride/polysilicon stack as masking materials, which can withstand anodization in hydrofluoric acid up to twenty hours. A special etching cell with electrolytic liquid backside contact along with two process flows has been developed to enable the fabrication of thick macro porous silicon membranes with though wafer pores. For device assembly, Si-Au and In-Au bonding technologies have been developed. Very low bonding temperature (~200 degrees C) and thick/soft bonding layers (~6µm) have been achieved by In-Au bondi ng technology, which is able to compensate the potentially rough surface on the porous silicon sample without introducing significant thermal stress. The application of the porous silicon material in micro systems has been demonstrated in a micro gas chromatograph system by two indispensable components: an integrated vapor source and an inlet filter, wherein porous silicon performs the basic functions of porous media: wicking and filtration. By utilizing a macro porous silicon wick, the calibration vapor source was able to produce a uniform and repeatable vapor generation for n-decane with less than a 0.1% variation in 9 hours, and less than a 0.5% variation in rate over 7 days. With engineered porous silicon membranes the inlet filter was able to show a depth filtration with nearly 100% collection efficiency for particles larger than 0.3µm in diameter, a low pressure-drop of 523Pa at 20sccm flow rate, and a filter capacity of 500µg/cm2.

EXTRACTION OF PICTORIAL ENERGY INFORMATION FROM CAMPUS UNMETERED BUILDINGS USING IMAGE PROCESSING TECHNIQUES

In recent years, advanced metering infrastructure (AMI) has been the main research focus due to the traditional power grid has been restricted to meet development requirements. There has been an ongoing effort to increase the number of AMI devices that provide real-time data readings to improve system observability. Deployed AMI across distribution secondary networks provides load and consumption information for individual households which can improve grid management. Significant upgrade costs associated with retrofitting existing meters with network-capable sensing can be made more economical by using image processing methods to extract usage information from images of the existing meters. This thesis presents a new solution that uses online data exchange of power consumption information to a cloud server without modifying the existing electromechanical analog meters. In this framework, application of a systematic approach to extract energy data from images replaces the manual reading process. One case study illustrates the digital imaging approach is compared to the averages determined by visual readings over a one-month period.