Decision-making is an important operation for any autonomous system. Robots in particular must observe their environment and compute appropriate responses. For solitary robots and centralized multiple-robot systems, decision-making is a relatively straightforward operation, since only a single agent (either the solitary robot or the single central controller) is solely responsible for the operation. The problem is much more complex in a decentralized system, to the point where optimal decision-making is intractable in the general case. Decentralized multiple-robot systems (dec-MRS) are robotic teams in which no robot is in authority over any others. The globally observed behaviour of dec-MRS emerges out of the individual robots’ local interactions with each other. This makes system-level decision-making, an operation in which an entire dec-MRS cooperatively makes a decision, a difficult problem. Social insects have long been a source of inspiration for dec-MRS research, and their example is followed in this work. Honeybees and Temnothorax ants must make group decisions in order to choose a new nest site whenever they relocate their colonies. Like the simple robots that compose typical dec-MRS, the insects utilize local, peer-to-peer behaviours to make good, cooperative decisions. This thesis examines their decision-making strategies in detail and proposes a three-phase framework for system-level decision-making by dec-MRS. Two different styles of decision are described, and experiments in both simulation and with real robots were carried out and presented here to demonstrate the framework’s decision-making ability. Using only local, anonymous communication and emergent behaviour, the proposed collective decision-making framework is able to make good decisions reliably, even in the presence of noisy individual sensing. Social cues such as consensus and quorum testing enables the robots to predicate their behaviour during the decision-making process on the global state of their system. Furthermore, because the operations carried out by the individual robots are so simple, and because their complexity to the individual robots is independent of the population size of a dec-MRS, the proposed decision-making framework will scale well to very large population sizes.

Environmental targets set by governments around the world are leading to high penetrations of small to medium-scale renewable distributed generation (DG). High penetration of DG in distribution networks, however, can result in voltage and thermal issues among other technical problems. The traditional 'Fit & Forget' approach that refers to the passive use of assets with limited or no control, in the context of distribution network planning, is used to meet maximum demand or generation requirements. However, to ensure that more renewable generation is cost-effectively connected to distribution networks, it is imperative to adopt a more active control of network elements and participants. The active control of future distribution networks requires understanding the corresponding dependencies between voltage magnitudes and DG active/reactive power outputs to mitigate voltage issues. One classical method to calculate these dependencies is to use sensitivity approaches such as those based on the Jacobian matrix. However, during operation, updating the Jacobian matrix requires the network to be fully observable making it unfeasible for decentralized control approaches. Therefore, it is critical to develop a sensitivity approach only requiring local real-time information. This thesis proposes a novel approach to produce voltage sensitivity coefficients using the surface fitting technique based solely on knowledge of network characteristics and, therefore, no remote monitoring is required. To assess the performance of the proposed voltage sensitivity approach, a decentralized (local) voltage control algorithm that simultaneously caters for both the active and reactive power outputs of a single DG plant is adopted. Comparisons with classical sensitivity approaches are carried out using the 16-bus UK GDS test network, 1-min resolution demand and wind generation data. Persistence forecasting (i.e., assuming no changes in demand and wind in a short time period) is considered in this case. The lower Mean Squared Error (MSE) shows that the coefficients of the proposed sensitivity approach are close to those of the Jacobian matrix and better than the perturb-and-observe approach. In the context of voltage management, results highlight that the proposed sensitivity approach is more effective than the Jacobian matrix inverse and perturb-and-observe, resulting in better voltage compliance and energy harvesting (better capacity factor). It should be highlighted that this performance is achieved without the need of full network observability. Furthermore, to cater for the more realistic and complex case of multiple DG plants, this thesis proposes a time-delay based decentralized control algorithm. A comparison with an ideal AC Optimal Power Flow (OPF) is carried out using the same 16-bus UK GDS network but with seven DG plants. The results demonstrate that the proposed sensitivity approach and time delays are very effective when compared to the AC OPF. This, in turn, proves that the combined use of the proposed voltage sensitivity approach and the decentralized controller is an implementable, cost-effective solution to manage DG plants in distribution networks without the need of further communication infrastructure. Finally, a decentralized DG control logic with the capability of using wind forecasting techniques is proposed to tackle the unpredictable nature of wind power. In this work, a time-series based forecasting technique is incorporated to the proposed decentralized controller. The results confirm that the use of more advanced forecasting technique can further improve the management of renewable DG plants.

The aim of this thesis was to quantify and asset the degree of fiscal decentralization and its development in the Czech Republic. We managed to quantify the measure of fiscal decentralization and its development in the Czech Republic from 2000 to 2006 through indicators of tax decentralization, expenditure decentralization, revenue decentralization, financial and tax autonomy. The figures for ČR were compared with other countries.

This dissertation presents the results of a series of studies on dynamic stabilisation of CoMan, which is actuated by series elastic actuators. The main goal of this dissertation is to dynamically stabilise the humanoid robot on the floor by the simplest multivariate feedback control for the purpose of walking. The multivariable scheme is chosen to take into account the joints' interactions, as well as providing a systematic way of designing the feedback system to improve the bandwidth and tracking performance of CoMan's existing PID control. A detailed model is derived which includes all the motors and joints state variables and their multibody interactions which are often ignored in the previous studies on bipedal robots in the literature. The derived dynamic model is then used to design multivariable optimal control feedback and observers with a mathematical proof for the relative stability and robustness of the closed loop system in face of model uncertainties and disturbances. In addition, two decentralized optimal feedback design algorithms are presented that explicitly take the compliant dynamics and the multibody interactions into account while providing the mathematical proof for the stability of the overall system. The purpose of the proposed decentralized control methods is to provide a systematic model based PDPID design to replace the existing PID controllers which are derived by a trial and error process. Moreover, the challenging constrained and compliant motion of the robot in double support is studied where a novel constrained feedback design is proposed which directly takes the compliance dynamics, interactions and the constraints into account to provide a closed loop feedback tracking system that drives the robot inside the constrained subspace. This method of control is particularly interesting since most control methods applied to closed kinematic chains (such as the double support phase) are over complicated for implementation purposes or have an ad-hoc approach to controller design. In terms of walking trajectory generation, an extension to the ZMP walking trajectory generation is proposed to utilise the CoMan's upper body to tackle the non-minimum phase behaviour that is faced in trajectory generation. Simple inverted pendulum models of walking are then used to study the maximum feasible walking speed and step size where parameters of CoMan are used to provide numerical upperbounds on the step size and walking speed. Use of straight knee and toe push-off during walking is shown to be beneficial for taking larger step lengths and hence achieving faster walking speeds. Subsequently, the designed tracking systems are then applied to a dynamic walking simulator which is developed during this PhD project to accurately model the compliant walking behaviour of the CoMan. A walking gait is simulated and visualized to show the effectiveness of the developed walking simulator. Moreover, the experimental results and challenges faced during the implementation of the designed tracking control systems are discussed where it is shown that the LQR feedback results in 50% less control effort and tracking errors in comparison with CoMan's existing independent PID control. This advantage directly affects the feasible walking speed. In addition, a set of standard and repeatable tests for CoMan are designed to quantify and compare the performance of various control system designs. Finally, the conclusions and future directions are pointed out.

Layered structures are commonly used in communication systems, but their roles in decentralized control are not understood well. In the first part of this thesis, a theoretical study of consensus (a typical decentralized control task) in layered structures is conducted. The unique graph topology approach permits explicit characterization of consensus performance based on simple graphical characteristics of MLMG structures. In the second part of this thesis, a generic LEGO test-bed to mimic multi-domain communication with layered structures is described. A search-and-rescue scenario is implemented to demonstrate the use of the test-bed.

The purpose of the non-experimental quantitative research study was to identify if there is a significant difference between the types of budget model an institution utilizes, institutional size, and student enrollment, retention, and graduation rates. This study was to identify if there is significant difference between institutional size and the type budget model utilized. Member institutions of the American Association of State Colleges and Universities (AASCU) were selected to participate in this study due to their similarities of mission and admissions policy. AASCU institutions share a common mission that focuses on access, innovation, regional support, and inclusion. AASCU institutions are all public regional institutions. Larger institutions within the study presented significantly higher retention and graduation rates compared to medium size institutions. I used the Carnegie classification of size as institutions that have enrollments less than 3,000 as small, institutions that have enrollments less than 10,000 as medium, and institutions with enrollments greater than 10,000 as large. I study found no significant difference in the types of budget model utilized and the student outcomes related to enrollment, retention, or graduation rates. I did indicate that institutions that utilized a more decentralized budgeting approach had higher enrollment percentages and higher retention and graduation rates than institutions that utilized a centralized budget model. I also did not identify any significant difference in the size of an institution and the type of budget model utilized.

Water scarcity has caused severe impact on the entire ecosphere while the climate change is resulting in high frequency of extreme weather conditions, especially extended period of drought. Due to the even increasing world’s population and the continued societal modernization, water scarcity is now one of the leading global challenges towards the development of human society. On the other hand, atmospheric water, accounting for 6 times the water in all rivers on Earth, is emerging as an alternative water resource. This dissertation thoroughly investigated the fully solar energy driven atmospheric water harvesting (AWH) process in a broad scientific and application context. The light-to-heat conversion process of solar photothermal materials was investigated first with a rationally designed droplet-laser system, which in combination with the calculation of heat of absorption of water vapor for various application scenarios, formed a theoretical basis of this dissertation research. As a result, a series of commonly used hydrated salts and their anhydrous counterparts were judiciously selected and successfully proven to be low-cost AWH materials to generate clean fresh water for arid regions. A hydrogel-deliquescent salt composite was further developed as AWH material with a significantly enhanced fresh water production capacity. A new design of nano-capsule encapsulated deliquescent salt was further put forward to enhance water vapor sorption/desorption kinetics, which enabled, for the first time, multiple sorption/desorption cycles within one day and thus multiplied water production capacity. The first-ever continuous AWH device, as opposed to batch-type one, was rationally designed, fabricated, and successfully tested in field conditions outdoors. At last, the dissertation pioneered a novel concept of atmospheric water sorption and desorption cycle for photovoltaic (PV) panel cooling. This dissertation shines significant light on sorption based atmospheric water harvesting and inspires more research efforts on this important research topic.

In this dissertation we consider the problem of cooperative sensing for secondary user access to primary user spectrum in cognitive radio systems. Using a fusion center or an access point, the cooperative users decide on the availability of spectrum for their use. Both Neyman-Pearson and Bayes criterion are considered for performance assessment. Our work on the asymptotic performance of counting rules with a very large number of sensors in decentralized detection problem shows that majority logic fusion rule has the same order of performance when compared to the best fusion rule based on the binary decisions received from the observing sensors in a network. In cognitive radio context, very large number of sensors may not be realistic and hence we would like to examine the performance of majority logic and counting rules involving a finite and small number of sensors. Uniformly most powerful test for decentralized detection for testing parameter θ when the observation is a sample from uniform (0,θ) distribution is investigated and it is shown that OR rule has the best performance among all counting rules in error free channel. The numerical study for reporting channel as a binary symmetric channel (BSC) with probability of bit error is also investigated and the results show that 2-out-of-5 or 2-out-of-10 has better performance among other k-out-of-n rules, whenever OR rule is not able to provide a probability of false alarm at the sensor, that lies over (0,1) at a given probability of bit error.

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A large number of power sources, operational in a microgrid, optimum power sharing and accordingly controlling the power sources along with scheduling loads are the biggest challenges in modern power system. In the era of smart grid, the solution is certainly not simple paralleling. Hence it is required to develop a control scheme that delivers the overall power requirements while also adhering to the power limitations of each source. As the penetration of distributed generators increase and are diversifi ed, the choice of decentralized control becomes preferable. In this work, a decentralized control framework is conceived. The primary approach is taken where a small hybrid system is investigated and decentralized control schemes were developed and subsequently tested in a hardware in the loop in conjunction with the hybrid power system setup developed at the laboratory. The control design approach is based on the energy conservation principle. However, considering the vastness of the real power network and its complexity of operation along with the growing demand of smarter grid operations, called for a revamp in the control framework design. Hence, in the later phase of this work, a novel framework is developed based on the coupled dynamical system theory, where each control node corresponds to one distributed generator connected to the microgrid. The coupling topology and coupling strengths of individual nodes are designed to be adjustable. The layer is modeled as a set of coupled differential equations of pre-assigned order. The control scheme adjusts the coupling weights so that steady state constraints are met at the system level, while allowing flexibility to explore the solution space. Additionally, the approach guarantees stable equilibria during power redistribution. The theoretical development is verified using simulations in matlab simulink environment.