This thesis deals with the design of multivariable controllers for stable linear time-invariant multi-input multi-output systems, with an unknown mathematical model, subject to constant reference/disturbance signals and actuator saturation constraints. A new controller parameter optimization approach, which can be carried out experimentally with no knowledge of the plant model nor of the order of the system, is proposed. The approach has the advantage that controllers can be optimized by perturbing only the initial conditions of the servocompensator, and that the order of the resulting controller obtained can be specified by the designer. Implementation of the proposed controller design approach is described, and an experimental application study of the proposed method applied to a multivariable system with industrial sensor/actuator components is presented to illustrate the feasibility of the design method in an industrial environment.

This thesis deals with the design of multivariable controllers for stable linear time-invariant multi-input multi-output systems, with an unknown mathematical model, subject to constant reference/disturbance signals and actuator saturation constraints. A new controller parameter optimization approach, which can be carried out experimentally with no knowledge of the plant model nor of the order of the system, is proposed. The approach has the advantage that controllers can be optimized by perturbing only the initial conditions of the servocompensator, and that the order of the resulting controller obtained can be specified by the designer. Implementation of the proposed controller design approach is described, and an experimental application study of the proposed method applied to a multivariable system with industrial sensor/actuator components is presented to illustrate the feasibility of the design method in an industrial environment.

Positive systems, which carry the well known property of confining the state, output, and/or input variables to the nonnegative orphant, are of great practical importance, as the nonnegative property occurs quite frequently in numerous applications and in nature. These type of systems frequently occur in hydrology where they are used to model natural and artificial networks of reservoirs; in biology where they are used to describe the transportation, accumulation, and drainage processes of elements and compounds like hormones, glucose, insulin, and metals; and in stocking, industrial, and engineering systems where chemical reactions, heat exchanges, and distillation processes take place. The interest of this dissertation is in two key problems: positive stabilization and the positive servomechanism problem. In particular, this thesis outlines the necessary and sufficient conditions for the stabilization of positive linear time-invariant (LTI) systems using state feedback control, along with providing an algorithm for constructing such a stabilizing regulator. Moreover, the results on stabilization also encompass the two problems of the positive separation principle and stabilization via observer design. The second, and most emphasized, problem of this dissertation considers the positive servomechanism problem for both single-input single-output (SISO) and multi-input multi-output (MIMO) stable positive LTI systems. The study of the positive servomechanism problem focuses on the tracking problem of nonnegative constant reference signals for unknown/known stable SISO/MIMO positive LTI systems with nonnegative unmeasurable/measurable constant disturbances via switching tuning clamping regulators (TcR), linear quadratic clamping regulators (LTQcR), and ending with MPC control. Finally, all theoretical results on the positive servomechanism problem are justified via numerous experimental results on a waterworks system.

With increased and varied performance demands, it is essential that complex multi-standard radio/systems coexist on a same chip. To have cost and performance benefits, these analog/RF systems are implemented in scaled nanometer nodes. At these nodes, the high level of variability in process variations is making the task of manufacturing high fidelity systems a challenge leading to yield and reliability issues. Hence, in the post-manufacturing phase, test and diagnosis steps are critical to identify the cause and effect of the process variations. Further, intelligent post-manufacturing tuning techniques are required to correct the effect of process variations on analog/RF systems. In this work, a die-level concurrent test and diagnosis approach using optimized measurements obtained in high volume manufacturing environment is proposed for analog/RF circuits. Such a simultaneous test and diagnosis methodology enables monitoring parametric process shifts and providing rapid feedback to the fab to minimize or prevent yield loss. In the case of devices that are continuously operating in the field, an efficient on-line diagnosis approach has been developed to perform reliability related prognosis. For advanced RF technologies such as MIMO-OFDM systems, a rapid system-level testing scheme is presented that performs concurrent testing of the multiple RF chains. Depending on the availability of the computational resources and system tuning knobs, different low-cost methodologies for post-manufacture tuning or self-healing of RF SISO/MIMO systems are developed. These include faster digital monitoring and tuning techniques, on-chip tuning techniques using digital logic that enables die-level self-tuning, and DSP-based power conscious iterative techniques for SISO/MIMO RF systems. An adaptive power-performance tuning technique is developed for those devices that have a post-manufacture power consumption value that is more than the acceptable limit. These intelligent post-manufacturing techniques result in reduced manufacturing cost, improved yield, and reliability of analog/RF systems.

Automatic physical database design tools rely on ``what-if'' interfaces to the query optimizer to estimate the execution time of the training query workload under different candidate physical designs. The tools use these what-if interfaces to recommend physical designs that minimize the estimated execution time of the input training workload. Minimizing estimated execution time alone can lead to designs that are not robust to query optimizer errors and workload changes. In particular, if the optimizer makes errors in estimating the execution time of the workload queries, then the recommended physical design may actually degrade the performance of these queries. In this sense, the physical design is risky. Furthermore, if the production queries are slightly different from the training queries, the recommended physical design may not benefit them at all. In this sense, the physical design is not general. We define Risk and Generality as two new measures aimed at evaluating the robustness of a proposed physical database design, and we show how to extend the objective function being optimized by a generic physical design tool to take these measures into account. We have implemented a physical design advisor in PostqreSQL, and we use it to experimentally demonstrate the usefulness of our approach. We show that our two new metrics result in physical designs that are more robust, which means that the user can implement them with a higher degree of confidence. This is particularly important as we move towards truly zero-administration database systems in which there is not the possibility for a DBA to vet the recommendations of the physical design tool before applying them.

Automatic physical database design tools rely on ``what-if'' interfaces to the query optimizer to estimate the execution time of the training query workload under different candidate physical designs. The tools use these what-if interfaces to recommend physical designs that minimize the estimated execution time of the input training workload. Minimizing estimated execution time alone can lead to designs that are not robust to query optimizer errors and workload changes. In particular, if the optimizer makes errors in estimating the execution time of the workload queries, then the recommended physical design may actually degrade the performance of these queries. In this sense, the physical design is risky. Furthermore, if the production queries are slightly different from the training queries, the recommended physical design may not benefit them at all. In this sense, the physical design is not general. We define Risk and Generality as two new measures aimed at evaluating the robustness of a proposed physical database design, and we show how to extend the objective function being optimized by a generic physical design tool to take these measures into account. We have implemented a physical design advisor in PostqreSQL, and we use it to experimentally demonstrate the usefulness of our approach. We show that our two new metrics result in physical designs that are more robust, which means that the user can implement them with a higher degree of confidence. This is particularly important as we move towards truly zero-administration database systems in which there is not the possibility for a DBA to vet the recommendations of the physical design tool before applying them.

This thesis presents an adaptive tuning system that can be described as a dynamic Just Intonation tuning system, being compatible with equally tempered instruments. The tuning system is called Hermode Tuning (HMT) and the tuning used as comparison for evaluation is the standardized western tuning, the equal tempered tuning. This study investigates preferences for these two musical tuning systems, depending on whether the tunings are presented on a piano or with woodwind instruments. A listening test was done with students at the Falun Conservatory of Music, including both a vertical listening (intervalls) and a horizontal listening (cadenses and musical compositions) of Hermode tuned musical material. Overall the results showed no significant preferences for either tuning system irrespectively of what instrument it was presented with. The clearest results was that of a misjudged just intonated perfect third on the piano and a preference for an adaptively tuned piano presented in a simple harmonic structure, with a parameter setting of HMT 70%. Materials for comparison was partly taken from Hermode´s own website, but overall the attitude towards these sequenses (using a likert scale of one to five) showed a low expected value. This shows the complexity of the topic and no general conclusions regarding the choice of intonation or tuning system could be done for the presented material.

Rhythmic movementssuch as swimming, flying, and walkingare ubiquitous in nature. Intrinsically active neural networks called central pattern generators (CPGs) provide the feedforward signals to actuate these movements, but the preferred movement frequency is often equivalent to the resonant frequency of the musculoskeletal system. Sensory feedback is essential to synchronize the neural and musculoskeletal systems to the mechanical resonant frequency, a phenomenon called resonance tuning. In this dissertation, we use a simple computational model of rhythmic movement to understand how the configuration of sensory feedback affects both the sensitivity of resonance tuning to parameter variation and the resiliency of resonance tuning to perturbation. Although previous studies have shown that resonance tuning is limited to frequencies that are above the intrinsic CPG frequency, we demonstrate that this limitation is only valid with negative feedback and with endogenously bursting CPG neurons. Specifically, we show that with positive feedback, resonance tuning occurs at frequencies that are below the intrinsic CPG frequency. Moreover, when the synaptic connections within the CPG are required for bursting activity, resonance tuning occurs both above and below the intrinsic CPG frequency with negative feedback and does not occur with positive feedback. Using Floquet analysis, we then demonstrate that perturbations decay more quickly when resonance tuning is realized with positive than with negative proportional feedback. Finally, we evaluate how the intrinsic CPG frequency, feedback gain, and mechanical damping affect the stability and range of resonance tuning with negative and positive feedback. Overall, these results indicate that the configuration of sensory feedback dramatically affects both the parameter space in which resonance tuning occurs and the stability of the resultant periodic motion.

This thesis reports development of three different high performance, low g-sensitive micromachined gyroscopes having single, double, and quadruple masses. The single mass gyroscope (SMG) is developed for comparison of its performance with the double mass gyroscope (DMG) and quadruple mass gyroscope (QMG). DMG is a tuning fork gyroscope, diminishing the effects of unpredictable g-loadings during regular operation, while QMG is a twin tuning fork gyroscope, developed for a uniform and minimized g-sensitivity. DMG and QMG use novel ring spring connections for merging the masses in drive modes, providing uniform and anti-phase drive mode vibrations that minimize the cross-coupling and the effects of intrinsic and extrinsic accelerations on the scale factor and bias levels of the gyroscopes. The sense mode of each mass of the multi-mass gyroscopes is designed to have higher resonance frequencies than that of the drive mode for possible matching requirements, and these sense modes have dedicated frequency tuning electrodes for frequency matching or tuning. Detailed performance simulations are performed with a very sophisticated computer model using the ARCHITECT software. These gyroscopes are fabricated using a standard SOIMUMPs process of MEMSCAP Inc., which provides capacitive gaps of 2 &micro / m and structural layer thickness of 25 &micro / m. Die sizes of the fabricated gyroscope chips are 4.1 mm x 4.1 mm for the single mass, 4.1 mm x 8.9 mm for the double mass, and 8.9 mm x 8.9 mm for the quadruple mass gyroscope. Fabricated gyroscopes are tested with dedicated differential readout electronics constructed with discrete components. Drive mode resonance frequencies of these gyroscopes are in a range of 3.4 kHz to 5.1 kHz. Depending on the drive mode mechanics, the drive mode quality (Q) factors of the fabricated gyroscopes are about 300 at atmospheric pressure and reaches to a value of 2500 at a vacuum ambient of 50 mTorr. Resolvable rates of the fabricated gyroscopes at atmospheric pressure are measured to be 0.109 deg/sec, 0.055 deg/sec, and 1.80 deg/sec for SMG, DMG, and QMG, respectively. At vacuum, the respective resolutions of these gyroscopes improve significantly, reaching to 106 deg/hr with the SMG and 780 deg/hr with the QMG, even though discrete readout electronics are used. Acceleration sensitivity measurements at atmosphere reveal that QMG has the lowest bias g-sensitivity and the scale factor g sensitivity of 1.02deg/sec/g and 1.59(mV/(deg/sec))/g, respectively. The performance levels of these multi-mass gyroscopes can be even further improved with high performance integrated capacitive readout electronics and precise sense mode phase matching.

In this study, the structural design and analysis of a wing having mission-adaptive control surfaces were conducted. The wing structure was designed in order to withstand a maximum aerodynamic loading of 5 g due to maneuver. The structural model of the wing was developed by using MSC/PATRAN package program and that structural model was analyzed by using MSC/NASTRAN package program. The designed wing was then manufactured by Turkish Aerospace Industries Inc. (TUSAS-TAI). The finite element analysis results were verified by conducting ground vibration tests on the manufactured wing. The comparative results were used to tune the finite element model and the results obtained showed that the modeling was very successful.