Trajectory planning of single and dual-arm robots for time-optimal handling of liquids and objects

This Thesis studies the optimal control problem of single-arm and dual-arm serial robots to achieve the time-optimal handling of liquids and objects. The first topic deals with the planning of time-optimal anti-sloshing trajectories of an industrial robot carrying a cylindrical container filled with a liquid, considering 1-dimensional and 2-dimensional planar motions. A technique for the estimation of the sloshing height is presented, together with its extension to 3-dimensional motions. An experimental validation campaign is provided and discussed to assess the thoroughness of such a technique. As far as anti-sloshing trajectories are concerned, 2-dimensional paths are considered and, for each one of them, three constrained optimizations with different values of the sloshing-height thresholds are solved. Experimental results are presented to compare optimized and non-optimized motions. The second part focuses on the time-optimal trajectory planning for dual-arm object handling, employing two collaborative robots (cobots) and adopting an admittance-control strategy. The chosen manipulation approach, known as cooperative grasping, is based on unilateral contact between the cobots and the object, and it may lead to slipping during motion if an internal prestress along the contact-normal direction is not prescribed. Thus, a virtual penetration is considered, aimed at generating the necessary internal prestress. The stability of cooperative grasping is ensured as long as the exerted forces on the object remain inside the static-friction cone. Constrained-optimization problems are solved for 3-dimensional paths: the virtual penetration is chosen among the control inputs of the problem and friction-cone conditions are treated as inequality constraints. Also in this case experiments are presented in order to prove evidence of the firm handling of the object, even for fast motions.

Development of the optimal estimation method for inversion of stratospheric emission spectra and validation of HNO3 profiles

This doctoral thesis focuses on ground-based measurements of stratospheric nitric acid (HNO3)concentrations obtained by means of the Ground-Based Millimeter-wave Spectrometer (GBMS). Pressure broadened HNO3 emission spectra are analyzed using a new inversion algorithm developed as part of this thesis work and the retrieved vertical profiles are extensively compared to satellite-based data. This comparison effort I carried out has a key role in establishing a long-term (1991-2010), global data record of stratospheric HNO3, with an expected impact on studies concerning ozone decline and recovery. The first part of this work is focused on the development of an ad hoc version of the Optimal Estimation Method (Rodgers, 2000) in order to retrieve HNO3 spectra observed by means of GBMS. I also performed a comparison between HNO3 vertical profiles retrieved with the OEM and those obtained with the old iterative Matrix Inversion method. Results show no significant differences in retrieved profiles and error estimates, with the OEM providing however additional information needed to better characterize the retrievals. A final section of this first part of the work is dedicated to a brief review on the application of the OEM to other trace gases observed by GBMS, namely O3 and N2O. The second part of this study deals with the validation of HNO3 profiles obtained with the new inversion method. The first step has been the validation of GBMS measurements of tropospheric opacity, which is a necessary tool in the calibration of any GBMS spectra. This was achieved by means of comparisons among correlative measurements of water vapor column content (or Precipitable Water Vapor, PWV) since, in the spectral region observed by GBMS, the tropospheric opacity is almost entirely due to water vapor absorption. In particular, I compared GBMS PWV measurements collected during the primary field campaign of the ECOWAR project (Bhawar et al., 2008) with simultaneous PWV observations obtained with Vaisala RS92k radiosondes, a Raman lidar, and an IR Fourier transform spectrometer. I found that GBMS PWV measurements are in good agreement with the other three data sets exhibiting a mean difference between observations of ~9%. After this initial validation, GBMS HNO3 retrievals have been compared to two sets of satellite data produced by the two NASA/JPL Microwave Limb Sounder (MLS) experiments (aboard the Upper Atmosphere Research Satellite (UARS) from 1991 to 1999, and on the Earth Observing System (EOS) Aura mission from 2004 to date). This part of my thesis is inserted in GOZCARDS (Global Ozone Chemistry and Related Trace gas Data Records for the Stratosphere), a multi-year project, aimed at developing a long-term data record of stratospheric constituents relevant to the issues of ozone decline and expected recovery. This data record will be based mainly on satellite-derived measurements but ground-based observations will be pivotal for assessing offsets between satellite data sets. Since the GBMS has been operated for more than 15 years, its nitric acid data record offers a unique opportunity for cross-calibrating HNO3 measurements from the two MLS experiments. I compare GBMS HNO3 measurements obtained from the Italian Alpine station of Testa Grigia (45.9° N, 7.7° E, elev. 3500 m), during the period February 2004 - March 2007, and from Thule Air Base, Greenland (76.5°N 68.8°W), during polar winter 2008/09, and Aura MLS observations. A similar intercomparison is made between UARS MLS HNO3 measurements with those carried out from the GBMS at South Pole, Antarctica (90°S), during the most part of 1993 and 1995. I assess systematic differences between GBMS and both UARS and Aura HNO3 data sets at seven potential temperature levels. Results show that, except for measurements carried out at Thule, ground based and satellite data sets are consistent within the errors, at all potential temperature levels.

An optimal estimator for the correlation of CMB anisotropies with Large Scale Structures and its application to WMAP-7year and NVSS

In the thesis we present the implementation of the quadratic maximum likelihood (QML) method, ideal to estimate the angular power spectrum of the cross-correlation between cosmic microwave background (CMB) and large scale structure (LSS) maps as well as their individual auto-spectra. Such a tool is an optimal method (unbiased and with minimum variance) in pixel space and goes beyond all the previous harmonic analysis present in the literature. We describe the implementation of the QML method in the {\it BolISW} code and demonstrate its accuracy on simulated maps throughout a Monte Carlo. We apply this optimal estimator to WMAP 7-year and NRAO VLA Sky Survey (NVSS) data and explore the robustness of the angular power spectrum estimates obtained by the QML method. Taking into account the shot noise and one of the systematics (declination correction) in NVSS, we can safely use most of the information contained in this survey. On the contrary we neglect the noise in temperature since WMAP is already cosmic variance dominated on the large scales. Because of a discrepancy in the galaxy auto spectrum between the estimates and the theoretical model, we use two different galaxy distributions: the first one with a constant bias $b$ and the second one with a redshift dependent bias $b(z)$. Finally, we make use of the angular power spectrum estimates obtained by the QML method to derive constraints on the dark energy critical density in a flat $\Lambda$CDM model by different likelihood prescriptions. When using just the cross-correlation between WMAP7 and NVSS maps with 1.8° resolution, we show that $\Omega_\Lambda$ is about the 70\% of the total energy density, disfavouring an Einstein-de Sitter Universe at more than 2 $\sigma$ CL (confidence level).

Analysis of optimal control problems for the incompressible MHD equations and implementation in a finite element multiphysics code

This thesis deals with the study of optimal control problems for the incompressible Magnetohydrodynamics (MHD) equations. Particular attention to these problems arises from several applications in science and engineering, such as fission nuclear reactors with liquid metal coolant and aluminum casting in metallurgy. In such applications it is of great interest to achieve the control on the fluid state variables through the action of the magnetic Lorentz force. In this thesis we investigate a class of boundary optimal control problems, in which the flow is controlled through the boundary conditions of the magnetic field. Due to their complexity, these problems present various challenges in the definition of an adequate solution approach, both from a theoretical and from a computational point of view. In this thesis we propose a new boundary control approach, based on lifting functions of the boundary conditions, which yields both theoretical and numerical advantages. With the introduction of lifting functions, boundary control problems can be formulated as extended distributed problems. We consider a systematic mathematical formulation of these problems in terms of the minimization of a cost functional constrained by the MHD equations. The existence of a solution to the flow equations and to the optimal control problem are shown. The Lagrange multiplier technique is used to derive an optimality system from which candidate solutions for the control problem can be obtained. In order to achieve the numerical solution of this system, a finite element approximation is considered for the discretization together with an appropriate gradient-type algorithm. A finite element object-oriented library has been developed to obtain a parallel and multigrid computational implementation of the optimality system based on a multiphysics approach. Numerical results of two- and three-dimensional computations show that a possible minimum for the control problem can be computed in a robust and accurate manner.

Essays On CEO Compensation: New Evidence On The Managerial-Power Vs. Optimal Contracting Debate

This dissertation analyzes the effect of market analysts’ expectations of share prices (price targets) on executive compensation. It examines how well the estimated effects of price targets on compensation fit with two competing views on determining executive compensation: the arm’s length bargaining model, which assumes that a board seeks to maximize shareholders’ interests, and the managerial power model, which assumes that a board seeks to maximize managers’ compensation (Bebchuk et al. 2005). The first chapter documents the pattern of CEO pay from fiscal year 1996 to 2010. The second chapter analyzes the Institutional Broker Estimate System Detail History Price Target data file, which that reports analysts’ price targets for firms. I show that the number of price target announcements is positively associated with company share price’s volatility, that price targets are predictive of changes in the value of stocks, and that when analysts announce positive (negative) expectations of future stock price, share prices change in the same direction in the short run. The third chapter analyzes the effect of price targets on executive compensation. I find that analysts' price targets alter the composition of executive pay between cash-based compensation and stock-based compensation. When analysts forecast a rise (fall) in the share price for a firm, the compensation package tilts toward stock-based (cash-based) compensation. The substitution effect is stronger in companies that have weaker corporate governance. The fourth chapter explores the effect of the introduction of the Sarbanes-Oxley Act (SOX) in 2002 and its reinforcement in 2006 on the options granting process. I show that the introduction of SOX and its reinforcement eliminated the practice of backdating options but increased “spring-loading” of option grants around price targets announcements. Overall, the dissertation shows that price targets provide insights into the determinants of executive pay in favor of the managerial power model.

Optimal Supervisory Control of Hybrid Vehicles

Hybrid vehicles (HV), comprising a conventional ICE-based powertrain and a secondary energy source, to be converted into mechanical power as well, represent a well-established alternative to substantially reduce both fuel consumption and tailpipe emissions of passenger cars. Several HV architectures are either being studied or already available on market, e.g. Mechanical, Electric, Hydraulic and Pneumatic Hybrid Vehicles. Among the others, Electric (HEV) and Mechanical (HSF-HV) parallel Hybrid configurations are examined throughout this Thesis. To fully exploit the HVs potential, an optimal choice of the hybrid components to be installed must be properly designed, while an effective Supervisory Control must be adopted to coordinate the way the different power sources are managed and how they interact. Real-time controllers can be derived starting from the obtained optimal benchmark results. However, the application of these powerful instruments require a simplified and yet reliable and accurate model of the hybrid vehicle system. This can be a complex task, especially when the complexity of the system grows, i.e. a HSF-HV system assessed in this Thesis. The first task of the following dissertation is to establish the optimal modeling approach for an innovative and promising mechanical hybrid vehicle architecture. It will be shown how the chosen modeling paradigm can affect the goodness and the amount of computational effort of the solution, using an optimization technique based on Dynamic Programming. The second goal concerns the control of pollutant emissions in a parallel Diesel-HEV. The emissions level obtained under real world driving conditions is substantially higher than the usual result obtained in a homologation cycle. For this reason, an on-line control strategy capable of guaranteeing the respect of the desired emissions level, while minimizing fuel consumption and avoiding excessive battery depletion is the target of the corresponding section of the Thesis.

A Law and Economics Analysis of Lobbying Regulation Towards an optimal structure through the Cost Indicator Index

This research primarily represents a contribution to the lobbying regulation research arena. It introduces an index which for the first time attempts to measure the direct compliance costs of lobbying regulation. The Cost Indicator Index (CII) offers a brand new platform for qualitative and quantitative assessment of adopted lobbying laws and proposals of those laws, both in the comparative and the sui generis dimension. The CII is not just the only new tool introduced in the last decade, but it is the only tool available for comparative assessments of the costs of lobbying regulations. Beside the qualitative contribution, the research introduces an additional theoretical framework for complementary qualitative analysis of the lobbying laws. The Ninefold theory allows a more structured assessment and classification of lobbying regulations, both by indication of benefits and costs. Lastly, this research introduces the Cost-Benefit Labels (CBL). These labels might improve an ex-ante lobbying regulation impact assessment procedure, primarily in the sui generis perspective. In its final part, the research focuses on four South East European countries (Slovenia, Serbia, Montenegro and Macedonia), and for the first time brings them into the discussion and calculates their CPI and CII scores. The special focus of the application was on Serbia, whose proposal on the Law on Lobbying has been extensively analysed in qualitative and quantitative terms, taking into consideration specific political and economic circumstances of the country. Although the obtained results are of an indicative nature, the CII will probably find its place within the academic and policymaking arena, and will hopefully contribute to a better understanding of lobbying regulations worldwide.

A Law and Economics Analysis of Trade Secrets: Optimal Scope of Law, Misappropriation and Alternative Damages Regimes

This thesis is primarily based on three core chapters, focused on the fundamental issues of trade secrets law. The goal of this thesis is to come up with policy recommendations to improve legal structure governing trade secrets. The focal points of this research are the following. What is the optimal scope of trade secrets law? How does it depend on the market characteristics such as degree of product differentiation between competing products? What factors need to be considered to balance the contradicting objectives of promoting innovation and knowledge diffusion? The second strand of this research focuses on the desirability of lost profits or unjust enrichment damage regimes in case of misappropriation of a trade secret. A comparison between these regimes is made and simple policy implications are extracted from the analysis. The last part of this research is an empirical analysis of a possible relationship between trade secrets sharing and misappropriation instances faced by firms.

Technological trajectories and environmental policy: the transformation of the automobile

This thesis aims to fill the gap in the literature by examining the relationship between technological trajectories and environmental policy in the automotive industry, focusing on the role of environmental policies in unlocking the industry from fossil fuel path-dependence. It first explores the inducement mechanism that underpins the interaction between environmental policy and green technological advances, investigating under what conditions the European environmental transport policy portfolio and the intrinsic characteristics of assignees' knowledge boost worldwide green patent production. Subsequently, the thesis empirically analyses the dynamics of technological knowledge involved in technological trajectories assessing evolution patterns such as variation, selection and retention, in order to study the impact of policy implementation on technological knowledge related to electric and hybrid vehicle technologies. Finally, the thesis sheds light on the drivers that encourage a shift from incumbent internal combustion engine technologies towards low-emission vehicle technologies. This analysis tests whether tax-inclusive fuel prices and technological proximity between technological fields induce a shift from non-environmental inventions to environmentally friendly inventive activities and if they impact the competition between alternative vehicle technologies. The findings provide insights into the effectiveness of environmental policy in triggering inventive activities related to the development of alternative vehicle technologies. In addition, there is evidence that environmental policy redirects technological efforts towards a sustainable path and impacts the competition between low-emission vehicles.