An Optimal Controller Architecture for Poset-Causal Systems

We propose a novel and natural architecture for decentralized control that is applicable whenever the underlying system has the structure of a partially ordered set (poset). This controller architecture is based on the concept of Moebius inversion for posets, and enjoys simple and appealing separation properties, since the closed-loop dynamics can be analyzed in terms of decoupled subsystems. The controller structure provides rich and interesting connections between concepts from order theory such as Moebius inversion and control-theoretic concepts such as state prediction, correction, and separability. In addition, using our earlier results on H_2-optimal decentralized control for arbitrary posets, we prove that the H_2-optimal controller in fact possesses the proposed structure, thereby establishing the optimality of the new controller architecture.Comment: 32 pages, 9 figures, submitted to IEEE Transactions on Automatic Contro

The role of smart sensor networks for voltage monitoring in smart grids

The large-scale deployment of the Smart Grid paradigm will support the evolution of conventional electrical power systems toward active, flexible and self-healing web energy networks composed of distributed and cooperative energy resources. In a Smart Grid platform, distributed voltage monitoring is one of the main issues to address. In this field, the application of traditional hierarchical monitoring paradigms has some disadvantages that could hinder their application in Smart Grids where the constant growth of grid complexity and the need for massive pervasion of Distribution Generation Systems (DGS) require more scalable, more flexible control and regulation paradigms. To try to overcome these challenges, this paper proposes the concept of a decentralized non-hierarchal voltage monitoring architecture based on intelligent and cooperative smart entities. These devices employ traditional sensors to acquire local bus variables and mutually coupled oscillators to assess the main variables describing the global grid state

The Pertinence of the Regionalization Project in Romania

The concept of "unified" or "homogeneous" state authority (in which the local authorities act as representatives of the central government, equivocally subordinated to its directive and control) was rejected and replaced with a dual system, in which the state and the local management act each in its own sphere of influence. However, we should not be surprised by the fact that the reality of local management partly lags behind the normative ideal. Europe is a space of decentralized local communities, the emphasis being placed on decentralization to enable the development of contacts which the hyper-centralized state would not have promoted and could not have tolerated. The decentralization is one of the ways which leads to a sort of European "normality" and that it participates in achieving this goal. Thus, the actual context is quite favourable to diminishing the role of the state, which should focus on its major functions: diplomacy, defence, monetary policy, preserving the economic macro-balance etc. those which stem directly from the national sovereignty, which only the state holds, no matter if it is a unitary or federal one

An Emergent Architecture for Scaling Decentralized Communication Systems (DCS)

With recent technological advancements now accelerating the mobile and wireless Internet solution space, a ubiquitous computing Internet is well within the research and industrial community's design reach - a decentralized system design, which is not solely driven by static physical models and sound engineering principals, but more dynamically, perhaps sub-optimally at initial deployment and socially-influenced in its evolution. To complement today's Internet system, this thesis proposes a Decentralized Communication System (DCS) architecture with the following characteristics: flat physical topologies with numerous compute oriented and communication intensive nodes in the network with many of these nodes operating in multiple functional roles; self-organizing virtual structures formed through alternative mobility scenarios and capable of serving ad hoc networking formations; emergent operations and control with limited dependency on centralized control and management administration. Today, decentralized systems are not commercially scalable or viable for broad adoption in the same way we have to come to rely on the Internet or telephony systems. The premise in this thesis is that DCS can reach high levels of resilience, usefulness, scale that the industry has come to experience with traditional centralized systems by exploiting the following properties: (i.) network density and topological diversity; (ii.) self-organization and emergent attributes; (iii.) cooperative and dynamic infrastructure; and (iv.) node role diversity. This thesis delivers key contributions towards advancing the current state of the art in decentralized systems. First, we present the vision and a conceptual framework for DCS. Second, the thesis demonstrates that such a framework and concept architecture is feasible by prototyping a DCS platform that exhibits the above properties or minimally, demonstrates that these properties are feasible through prototyped network services. Third, this work expands on an alternative approach to network clustering using hierarchical virtual clusters (HVC) to facilitate self-organizing network structures. With increasing network complexity, decentralized systems can generally lead to unreliable and irregular service quality, especially given unpredictable node mobility and traffic dynamics. The HVC framework is an architectural strategy to address organizational disorder associated with traditional decentralized systems. The proposed HVC architecture along with the associated promotional methodology organizes distributed control and management services by leveraging alternative organizational models (e.g., peer-to-peer (P2P), centralized or tiered) in hierarchical and virtual fashion. Through simulation and analytical modeling, we demonstrate HVC efficiencies in DCS structural scalability and resilience by comparing static and dynamic HVC node configurations against traditional physical configurations based on P2P, centralized or tiered structures. Next, an emergent management architecture for DCS exploiting HVC for self-organization, introduces emergence as an operational approach to scaling DCS services for state management and policy control. In this thesis, emergence scales in hierarchical fashion using virtual clustering to create multiple tiers of local and global separation for aggregation, distribution and network control. Emergence is an architectural objective, which HVC introduces into the proposed self-management design for scaling and stability purposes. Since HVC expands the clustering model hierarchically and virtually, a clusterhead (CH) node, positioned as a proxy for a specific cluster or grouped DCS nodes, can also operate in a micro-capacity as a peer member of an organized cluster in a higher tier. As the HVC promotional process continues through the hierarchy, each tier of the hierarchy exhibits emergent behavior. With HVC as the self-organizing structural framework, a multi-tiered, emergent architecture enables the decentralized management strategy to improve scaling objectives that traditionally challenge decentralized systems. The HVC organizational concept and the emergence properties align with and the view of the human brain's neocortex layering structure of sensory storage, prediction and intelligence. It is the position in this thesis, that for DCS to scale and maintain broad stability, network control and management must strive towards an emergent or natural approach. While today's models for network control and management have proven to lack scalability and responsiveness based on pure centralized models, it is unlikely that singular organizational models can withstand the operational complexities associated with DCS. In this work, we integrate emergence and learning-based methods in a cooperative computing manner towards realizing DCS self-management. However, unlike many existing work in these areas which break down with increased network complexity and dynamics, the proposed HVC framework is utilized to offset these issues through effective separation, aggregation and asynchronous processing of both distributed state and policy. Using modeling techniques, we demonstrate that such architecture is feasible and can improve the operational robustness of DCS. The modeling emphasis focuses on demonstrating the operational advantages of an HVC-based organizational strategy for emergent management services (i.e., reachability, availability or performance). By integrating the two approaches, the DCS architecture forms a scalable system to address the challenges associated with traditional decentralized systems. The hypothesis is that the emergent management system architecture will improve the operational scaling properties of DCS-based applications and services. Additionally, we demonstrate structural flexibility of HVC as an underlying service infrastructure to build and deploy DCS applications and layered services. The modeling results demonstrate that an HVC-based emergent management and control system operationally outperforms traditional structural organizational models. In summary, this thesis brings together the above contributions towards delivering a scalable, decentralized system for Internet mobile computing and communications

Virtual Coordination in Collective Object Manipulation

Inspired by nature, swarm robotics aims to increase system robustness while utilizing simple agents. In this work, we present a novel approach to achieve decentralized coordination of forces during collective manipulation tasks resulting in a highly scalable, versatile, and robust solution. In this approach, each robot involved in the collective object manipulation task relies on the behavior of a cooperative ``virtual teammate\u27 in a fully decentralized architecture, regardless of the size and configuration of the real team. By regulating their actions with their corresponding virtual counterparts, robots achieve continuous pose control of the manipulated object, while eliminating the need for inter-agent communication or a leader-follower architecture. To experimentally study the scalability, versatility, and robustness of the proposed collective object manipulation algorithm, a new swarm agent, Δρ is introduced which is able to apply linear forces in any planar direction. Efficiency and effectiveness of the proposed decentralized algorithm are investigated by quantitative performance metrics of settling time, steady-state error, path efficiency, and object velocity profiles in comparison with a force-optimal centralized version that requires complete information. Employing impedance control during manipulation of an object provides a mean to control its dynamic interactions with the environment. The proposed decentralized algorithm is extended to achieve a desired multi-dimensional impedance behavior of the object during a collective manipulation without inter-agent communication. The proposed algorithm extension is built upon the concept of ``virtual coordination\u27 which demands every agent to locally coordinate with one virtual teammate. Since the real population of the team is unknown to the agents, the resultant force applied to the manipulated object would be directly scaled with the team population. Although this scaling effect proves useful during position control of the object, it leads to a deviation from the desired dynamic response when employed in an impedance control scheme. To minimize such deviations, a gradient descent algorithm is implemented to determine a scaling parameter defined on the control action. The simulation results of a multi-robot system with different populations and formations verify the effectiveness of the proposed method in both generating the desired impedance response and estimating the population of the group. Eventually, as two case studies, the introduced algorithm is used in robotic collective manipulation and human- assistance scenarios. Simulation and experimental results indicate that the proposed decentralized communication- free algorithm successfully performs collective manipulation in all tested scenarios, and matches the performance of the centralized controller for increasing number of agents, demonstrating its utility in communication- limited systems, remote environments, and access-limited objects

Distributed Model Predictive Control of Load Frequency for Power Networks

In recent years, there has been an increase of interest in smart grid concept, to adapt the power grid to improve the reliability, efficiency and economics of the electricity production and distribution. One of the generator side problem in this is to meet the power requirement while not wasting unnecessary power, thus keeping the cost down, which must be done while the frequency is kept in a suitable range that will not damage any equipment connected to the power grid. It would theoretically be most logical to have a centralized controller that gathers the full networks data, calculates the control signals and adjusts the generators. However in practice this is not practical, mostly due to distance. The transmission of sensor data to the controller and the transmission of control signals to the generators would have to travel far, thus taking up to much time before the generators could act. This paper presents a distributed model predictive control based method to control the frequency of the power network. First, an augmented matrix model predictive controller is introduced and implemented on a two homogeneous subsystems network. Later the control method is changed to a state space model predictive controller and is then utilized on a four heterogeneous subsystems network. This controller implementation also includes state observers by Kalman filtering, constraints handler utilizing quadratic programming, and different connection topology setups to observe how the connectivity affects the outcome of the system. The effectiveness of the proposed distributed control method was compared against the corresponding centralized and decentralized controller implementation results. It is also compared to other control algorithms, specifically, an iterative gradient method, and a model predictive controller generated by the MATLAB MPC Toolbox. The results show that the usage of a distributed setup improves the outcome compared to the decentralized case, whilst keeping a more convenient setup than the centralized case. It it also shown that the level of connectivity for a chosen network topology matters for the outcome of the system, the results are improved when more connections exists