Passive wireless sensor networks (WSNs) are quickly becoming popular for many applications such as article tracking, position location, temperature sensing, and passive data storage. Passive tags and sensors are unique in that they collect their electrical energy by harvesting it from the ambient environment. Tags with charge pumps collect their energy from the signal they receive from the transmitting source. The efficiency of converting the received signal to DC power is greatly enhanced using a power-optimized waveform (POW). Measurements in the first part of this dissertation show that a POW can provide efficiency gains of up to 12 dB compared to a sine-wave input. Tracking the real-time location of these passive tags is a specialized feature used in some applications such as animal tracking. A passive WSN that uses POWs for the improvement of energy-harvesting may also estimate the range to a tag by measuring the time delay of propagation from the transmitter to the tag and back to the transmitter. The maximum-likelihood (ML) estimator is used for estimating this time delay, which simplifies to taking the cross-correlation of the received signal with the transmitted signal. This research characterizes key aspects of performing range estimations in passive WSNs using POWs. The shape of the POW has a directly-measurable effect on ranging performance. Measurements and simulations show that the RMS bandwidth of the waveform has an inversely proportional relationship to the uncertainty of a range measurement. The clutter of an environment greatly affects the uncertainty and bias exhibited by a range estimator. Random frequency-selective environments with heavy clutter are shown to produce estimation uncertainties more than 20 dB higher than the theoretical lower bound. Estimation in random frequency-flat environments is well-behaved and fits the theory quite nicely. Nonlinear circuits such as the charge pump distort the POW during reflection, which biases the range estimations. This research derives an empirical model for predicting the estimation bias for Dickson charge pumps and verifies it with simulations and measurements.

A full Strouhal number thermo-acoustic model is purposed for the feedback control of self excited noise driven combustors. The inclusion of time delays in the volumetric heat release perturbation models create unique behavioral characteristics which are not properly reproduced within current low Strouhal number thermo acoustic models. New analysis tools using probability density functions are introduced which enable exact expressions for the statistics of a time delayed system. Additionally, preexisting tools from applied mathematics and control theory for spectral analysis of time delay systems are introduced to the combustion community. These new analysis tools can be used to extend sensitivity function analysis used in control theory to explain limits to control effectiveness in self-excited combustors. The control effectiveness of self-excited combustors with actuator constraints are found to be most sensitive to the location of non-minimum phase zeros. Modeling the non-minimum phase zeros correctly require accurate volumetric heat release perturbation models. Designs that removes non-minimum phase zeros are more likely to have poles in the right hand complex plane. As a result, unstable combustors are inherently more responsive to feedback control.

The angular location of an acoustic source can be estimated by measuring an acoustic direction of incidence based solely on the noise produced by the source. Methods for determining the direction of incidence based on sound intensity, the phase of cross-spectral functions, and cross-correlation functions are available. In this current work, we implement Dominant Frequency SElection (DFSE) algorithm. Direction of arrival (DOA) estimation usingmicrophone arrays is to use the phase information present in signals from microphones that are spatially separated. DFSE uses the phase difference between the Fourier transformedsignals to estimate the direction ofarrival (DOA)and is implemented using a three-element ’L’ shaped microphone array, linear microphone array, and planar 16-microphone array. This method is based on simply locating the maximum amplitude from each of the Fourier transformed signals and thereby deriving the source location by solving the set of non-linear least squares equations. For any pair of microphones, the surface on whichthe time difference ofarrival (TDOA) is constant is a hyperboloidoftwo sheets. Acoustic source localization algorithms typically exploit this fact by grouping all microphones into pairs, estimating the TDOA of each pair, then finding the point where all associated hyperboloids most nearly intersect. We make use of both closed-form solutions and iterative techniques to solve for the source location.Acoustic source positioned in 2-dimensional plane and 3-dimensional space have been successfully located.

Recent research focuses on expanding the use of RF/Microwave circuits and systems to include multi-disciplinary applications. One example is the detection of the dielectric properties of chemicals and bio-chemicals at microwave frequencies, which is useful for pharmaceutical applications, food and drug safety, medical diagnosis and material characterization. Dielectric spectroscopy is also quite relevant to detect the frequency dispersive characteristics of materials over a wide frequency range for more accurate detection. In this dissertation, on-chip and on-board solutions for microwave chemical sensing are proposed. An example of an on-chip dielectric detection technique for chemical sensing is presented. An on-chip sensing capacitor, whose capacitance changes when exposed to material under test (MUT), is a part of an LC voltage-controlled oscillator (VCO). The VCO is embedded inside a frequency synthesizer to convert the change in the free runing frequency frequency of the VCO into a change of its input voltage. The system is implemented using 90 nm CMOS technology and the permittivities of MUTs are evaluated using a unique detection procedure in the 7-9 GHz frequency range with an accuracy of 3.7% in an area of 2.5 × 2.5 mm^2 with a power consumption of 16.5 mW. The system is also used for binary mixture detection with a fractional volume accuracy of 1-2%. An on-board miniaturized dielectric spectroscopy system for permittivity detec- tion is also presented. The sensor is based on the detection of the phase difference be- tween the input and output signals of cascaded broadband True-Time-Delay (TTD) cells. The sensing capacitor exposed to MUTs is a part of the TTD cell. The change of the permittivity results in a change of the phase of the microwave signal passing through the TTD cell. The system is fabricated on Rogers Duroid substrates with a total area of 8 × 7.2 cm2. The permittivities of MUTs are detected in the 1-8 GHz frequency range with a detection accuracy of 2%. Also, the sensor is used to extract the fractional volumes of mixtures with accuracy down to 1%. Additionally, multi-band and multi-standard communication systems motivate the trend to develop broadband front-ends covering all the standards for low cost and reduced chip area. Broadband amplifiers are key building blocks in wideband front-ends. A broadband resistive feedback low-noise amplifier (LNA) is presented using a composite cross-coupled CMOS pair for a higher gain and reduced noise figure. The LNA is implemented using 90 nm CMOS technology consuming 18 mW in an area of 0.06 mm2. The LNA shows a gain of 21 dB in the 2-2300 MHz frequency range, a minimum noise figure of 1.4 dB with an IIP3 of -1.5 dBm. Also, a four-stage distributed amplifier is presented providing bandwidth extension with 1-dB flat gain response up to 16 GHz. The flat extended bandwidth is provided using coupled inductors in the gate line with series peaking inductors in the cascode gain stages. The amplifier is fabricated using 180 nm CMOS technology in an area of 1.19 mm2 achieving a power gain of 10 dB, return losses better than 16 dB, noise figure of 3.6-4.9 dB and IIP3 of 0 dBm with 21 mW power consumption. All the implemented circuits and systems in this dissertation are validated, demonstrated and published in several IEEE Journals and Conferences.

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The research work presented in this thesis concern to the stability analysis of linear time-delay systems with low-order controllers. This thesis is divided into three parts.The first part of the thesis focus on the study of linear SISO (single-input/single-output) systems with input/output delays, where the feedback loop is closed with a controller of PID-type. Inspired by the geometrical approach developed by Gu et al. we propose an analytical method to find the stability regions of all stabilizing controllers of PID-type for the time-delay system. Based on this same approach, we propose an algorithm to calculate the degree of fragility of a given controller of PID- type (PI, PD and PID).The second part of the thesis focuses on the stability analysis of linear systems under an NCS (Networked System Control) based approach. More precisely, we first focus in the stabilization problem by taking into account the induced network delays and the effects induced by the sampling period. To carry out such an analysis we have adopted an eigenvalue perturbation-based approach.Finally, in the third part of the thesis we tackle certain problems concerning to the behavior of the zeros of a certain class of sampled-data SISO systems. More precisely, given a continuous-time system, we obtain the sampling intervals guaranteeing the invariance of the number of unstable zeros in each interval. To perform such an analysis, we adopt an eigenvalue perturbation-based approach.

System identification finds nowadays application in various areas of biological research as a tool of empiric mathematical modeling and model individualization. A fundamental challenge of system identification in biology awaits in the form of response variability. Furthermore, biological systems tend to exhibit high degree of nonlinearity as well as significant time delays. This thesis covers system identification approaches developed for the applications within two particular biomedical fields: neuroscience and endocrinology. The first topic of the thesis is parameter estimation of the classical Elementary Motion Detector (EMD) model in insect vision. There are two important aspects to be taken care of in the identification approach, namely the nonlinear dynamics of the individual EMD and the spatially distributed structure of multiple detectors producing a measurable neural response. Hence, the suggested identification method is comprised of two consecutive stages addressing each of the above aspects. Furthermore, visual stimulus design for high spatial excitation order has been investigated. The second topic is parameter estimation of mathematical model for testosterone regulation in the human male. The main challenges of this application are in the unavailability of input signal measurements and the presence of an unknown pulsatile feedback in the system resulting in a highly nonlinear closed-loop dynamics. Semi-blind identification method has been developed based on a recently proposed pulse-modulated model of pulsatile endocrine regulation. The two system identification problems treated in the thesis bear some resemblance in the sense that both involve measured signals that can be seen as square-integrable functions of time. This property is handled by transforming the signals into the Laguerre domain, i.e. by equivalently representing the functions with their infinite Laguerre series.

Since their discovery in 1978 by Hill et al. and the development of the transverse holographic technique for their fabrication by Meltz et al. in 1989, fiber Bragg gratings (FBG) have become an important device for applications in optical communications, optical signal processing and fiber-optical sensors. A superstructured fiber Bragg grating (SFBG), also called a sampled fiber Bragg grating, is a special FBG that consists of a several small FBGs placed in close proximity to one another. SFBGs have attracted much attention in recent years with the discovery of techniques allowing the creation of equivalent chirp or equivalent phase shifts. The biggest advantage of an SFBG with equivalent chirp or equivalent phase shifts is the possibility to design and fabricate gratings with greatly varying phase and amplitude responses by adjusting the spatial profile of the superstructure. The realization of SFBGs with equivalent chirp or equivalent phase shifts requires only sub-millimeter precision. This is a relief from the sub-micron precision required by traditional approaches. In this thesis, the mathematical modeling of FBGs and SFBGs is reviewed. The use of SFBGs for various applications in photonic microwave signal processing is considered. Four main topics are presented in this thesis. The first topic is the use of SFBG as a photonic true-time delay (TTD) beamformer for phased array antennas (PAAs). The second topic addresses non-linearities in the group delay response of an SFBG with equivalent chirp in its sampling period. An SFBG with an equivalent chirp using only a linear chirp coefficient may yield a group delay response that deviates from the linear response required by a TTD beamformer. In the thesis, a technique to improve the linearity of the group delay response is proposed and an adaptive algorithm to find the optimal linear and non-linear chirp coefficients to produce the best linear group delay response is described. Since no closed-form solution exists to represent the amplitude and phase responses of an SFBG, we rely on a Fourier transform analogy under a weak grating approximation as a starting point in the design of an SFBG. Simulations are then used to refine the response of the SFBG. The algorithm proposed provides an optimal set of chirp coefficients that minimizes the error in the group delay response. Four gratings are fabricated using the optimized chirp coefficients and their application in a TTD PAA system is discussed. The third topic discusses the use of an SFBG with equivalent phase shifts in its sampling period as a means to realize optical single sideband (SSB) modulation. SSB modulation eliminates the power penalty caused by chromatic dispersion experienced by an optical signal traveling through a long length of optical fiber. By introducing two π phase shifts through equivalent sampling to the SFBG, two ultra-narrow transmission bands are created in the grating stop band of the +/- 1st spectral orders. In the proposed system, a double-sideband plus carrier (DSB+C) modulated optical signal is sent to the input of an optical SSB filter based on the equivalent phase-shift SFBG in order to select the optical carrier and a single sideband, effectively blocking one sideband from propagating. Finally, the fourth topic focuses on the implementation of a photonic microwave bandpass filter based on an SFBG with equivalent chirp. Photonic microwave filters are used to process microwave signals in the optical domain. By using a technique called phase-modulation to intensity-modulation (PM-IM) conversion, a two-tap delay line filter is created with one negative tap. A single SFBG with a chirp in its sampling period is used as a means to achieve the PM-IM conversion for the two taps. Two phase modulated optical carriers are used to generate the two taps, each entering a different port of the SFBG and thus experiencing an opposite dispersion value. The two optical signals are then recombined before being sent to a photodetector (PD) where the filtered microwave signal is recovered.

The optimal steady-state control, and suboptimal adaptive control, of disturbed single-input-output systems are introduced, and the class of systems considered is defined. It is noted that the stochastic tracking problem divides into a deterministic tracking problem and a stochastic regulator problem; the solutions to these two problems are shown to be independent but formally similar. The continuous regulator problem is approached via both frequency and time domain methods: the former method is extended to cover unstable systems; the latter method is extended to include systems with input delay. The two regulators are shown to be externally equivalent. The frequency domain method is briefly described for discrete systems, and shown to include the minimum variance regulator of Åström and Peterka as a special case. Some systems which allow measurement noise to be treated as a system disturbance for the purposes of optimal controller design are investigated. A novel class of control laws is described in both continuous and discrete time; in the same way as the minimum variance regulator forms the basis of the self-tuning regulator of Åström and Wittenmark, these minimum variance controllers from the basis of a self-tuning controller. These minimum variance controllers have a number of advantages over the minimum-variance regulator, and are open to a number of interpretations including: a model following control law, and an extension of classical control laws to systems with delay. The optimality of this class of control laws is investigated, and analogies drawn with the previously considered k-step-ahead control laws; some examples are given to illustrate the method. An adaptive control law combining the above minimum variance controllers with a linear least-squares algorithm is proposed and shown to be self-tuning. These self-tuning controllers are only slightly more complex than the self-tuning regulator of Åström and Wittenmark, but have a number of advantages. Intuitive justification is given for the conjecture that some methods of Ljung, developed for the analysis of the self-tuning regulator, are applicable to the self-tuning controller. Simulated examples are given which compare and contrast the performance of the self-tuning controller with that of the self-tuning regulator. The first steps towards a quasi-continuous self-tuning controller are outlined.

In this thesis study, it is aimed to improve the performance of an Internet-based teleoperation system enabling the remote operation of a 6 DOF industrial robot. In order to improve the safety and efficiency of the teleoperation, stability and synchronization (hand-eye coordination) are considered. The selected communication medium between the human operator and remote robot is the Internet. The variable time delays and nondeterministic characteristics of the Internet may lead to instability of the teleoperation system. Considering the disturbing effects of the Internet onto the transmission, an event-based control approach is used in order to improve the stability of the teleoperation system. Besides, a visual feedback system is developed and a force-feedback mouse is designed in order to improve synchronization between the human operator and robot during the command generation according to the feedback obtained from the control system. A client-server software application is developed to interface the human operator with remote environment. It is observed that, using the event-based control approach in the operation makes the teleoperation stable and improves the synchronization ability. Implementation of visual feedback and force-feedback mouse to the teleoperation system improves the human operator&rsquo / s ability to perform remote operation.