Static output feedback control via PDE boundary and ODE measurements in linear cascaded ODE–beam systems

This paper addresses the problem of feedback control design for a class of linear cascaded ordinary differential equation (ODE)–partial differential equation (PDE) systems via a boundary interconnection, where the ODE system is linear time-invariant and the PDE system is described by an Euler–Bernoulli beam (EBB) equation with variable coefficients. The objective of this paper is to design a static output feedback (SOF) controller via EBB boundary and ODE measurements such that the resulting closed-loop cascaded system is exponentially stable. The Lyapunov’s direct method is employed to derive the stabilization condition for the cascaded ODE–beam system, which is provided in terms of a set of bilinear matrix inequalities (BMIs). Furthermore, in order to compute the gain matrices of SOF controllers, a two-step procedure is presented to solve the BMI feasibility problem via the existing linear matrix inequality (LMI) optimization techniques. Finally, the numerical simulation is given to illustrate the effectiveness of the proposed design method.     

Decentralized observers with consensus filters for distributed discrete-time linear systems

This paper presents a decentralized observer with a consensus filter for the state observation of discrete-time linear distributed systems. Each agent in the distributed system has an observer with a model of the plant that utilizes the set of locally available measurements, which may not make the full plant state detectable. This lack of detectability is overcome by utilizing a consensus filter that blends the state estimate of each agent with its neighbors’ estimates. It is proven that the state estimates of the proposed observer exponentially converge to the actual plant states under arbitrarily changing, but connected, communication and pseudo-connected sensing graph topologies. Except these connectivity properties, full knowledge of the sensing and communication graphs is not needed at the design time. As a byproduct, we obtained a result on the location of eigenvalues, i.e., the spectrum, of the Laplacian for a family of graphs with self-loops.     

Robust adaptive control of a thruster assisted position mooring system

In this paper, robust adaptive control is developed for a thruster assisted position mooring system in the transverse direction. To provide an accurate and concise representation for the dynamic behavior of the mooring system, the flexible mooring lines are modeled as a distributed parameter system of partial differential equations (PDEs). The proposed control is applied at the top boundary of the mooring lines for station keeping via Lyapunov’s direct method. Adaptive control is designed to handle the system parametric uncertainties. With the proposed robust adaptive control, uniform boundedness of the system under the ocean current disturbance is achieved. The proposed control is implementable with actual instrumentations since all the signals in the control can be measured by sensors or calculated by using a backward difference algorithm. The effectiveness of the proposed control is verified by numerical simulations.     

Adaptive output-feedback stabilization of non-local hyperbolic PDEs

We address the problem of adaptive output-feedback stabilization of general first-order hyperbolic partial integro-differential equations (PIDE). Such systems are also referred to as PDEs with non-local (in space) terms. We apply control at one boundary, take measurements on the other boundary, and allow the system’s functional coefficients to be unknown. To deal with the absence of both full-state measurement and parameter knowledge, we introduce a pre-transformation (which happens to be based on backstepping) of the system into an observer canonical form. In that form, the problem of adaptive observer design becomes tractable. Both the parameter estimator and the control law employ only the input and output signals (and their histories over one unit of time). Prior to presenting the adaptive design, we present the non-adaptive/baseline controller, which is novel in its own right and facilitates the understanding of the more complex, adaptive system. The parameter estimator is of the gradient type, based on a parametric model in the form of an integral equation relating delayed values of the input and output. For the closed-loop system we establish boundedness of all signals, pointwise in space and time, and convergence of the PDE state to zero pointwise in space. We illustrate our result with a simulation.     

Local artificial boundary conditions for Schrödinger and heat equations by using high-order azimuth derivatives on circular artificial boundary

The aim of the paper is to design high-order artificial boundary conditions for the Schrödinger equation on unbounded domains in parallel with a treatment of the heat equation. We first introduce a circular artificial boundary to divide the unbounded definition domain into a bounded computational domain and an unbounded exterior domain. On the exterior domain, the Laplace transformation in time and Fourier series in space are applied to achieve the relation of special functions. Then the rational functions are used to approximate the relation of the special functions. Applying the inverse Laplace transformation to a series of simple rational function, we finally obtain the corresponding high-order artificial boundary conditions, where a sequence of auxiliary variables are utilized to avoid the high-order derivatives in respect to time and space. Furthermore, the finite difference method is formulated to discretize the reduced initial–boundary value problem with high-order artificial boundary conditions on a bounded computational domain. Numerical experiments are presented to illustrate the performance of our method.     

A strengthened analysis of a local algorithm for the minimum dominating set problem in planar graphs

In recent years growing interest in local distributed algorithms has widely been observed. This results from their high resistance to errors and damage, as well as from their good performance, which is independent of the size of the network. A local deterministic distributed algorithm finding an approximation of a Minimum Dominating Set in planar graphs has been presented by Lenzen et al., and they proved that the algorithm returns a 130-approximation of the Minimum Dominating Set. In this article we will show that the algorithm is two times more effective than was previously assumed, and we prove that the algorithm by Lenzen et al. outputs a 52-approximation to a Minimum Dominating Set. Therefore the gap between the lower bound and the approximation ratio of the best yet local deterministic distributed algorithm is reduced by half.     

Acquiring logistics process intelligence: Methodology and an application for a Chinese bulk port

The processes of logistics service providers are considered as highly human-centric, flexible and complex. Deviations from the standard operating procedures as described in the designed process models, are not uncommon and may result in significant uncertainties. Acquiring insight in the dynamics of the actual logistics processes can effectively assist in mitigating the uncovered risks and creating strategic advantages, which are the result of uncertainties with respectively a negative and a positive impact on the organizational objectives.In this paper a comprehensive methodology for applying process mining in logistics is presented, covering the event log extraction and preprocessing as well as the execution of exploratory, performance and conformance analyses. The applicability of the presented methodology and roadmap is demonstrated with a case study at an important Chinese port that specializes in bulk cargo.     

On reactive routing protocols in ZigBee wireless sensor networks

ZigBee is the primary standard solution for wireless sensor networks, implementing the Ad hoc On‐Demand Distance Vector (AODV) protocol in the network layer and supported by the standard IEEE 802.15.4. This study is focused on mesh topologies and the critical problems encountered when AODV is executed in conjunction with the Carrier Sense Multiple Access with Collision Avoidance protocol. These problems are mainly related to the packet overhead required to carry out route creation. To perform preliminary experiments to be able to implement AODV in a real network, a new metric is proposed herein. This metric uses fuzzy logic to help in the decision‐making process. The objective of the fuzzy routine is to determine, during the route‐discovery process, the best node to forward request/reply packets, with the aim of reducing packet overhead and energy consumption. Moreover, minor changes are also added to the discovery procedure of AODV to improve the performance of the route‐creation process. This intelligent version of AODV has provided promising experimental results, greatly reducing the number of packets required, with the consequent energy saving while selecting the best nodes to be part of the routes.     

Detecting stable locality-aware predicates

In a large-scale locality-driven network such as in modular robotics and wireless sensor networks, knowing the state of a local area is sometimes necessary due to either interactions being local and driven by neighborhood proximity or the users being interested in the state of a certain region. We define locality-aware predicates (LAP) that aim at detecting a predicate within a specified area. We model the area of interest as the set of processes that are within a breadth-first search tree (BFST) of height k$k$ rooted at the initiator process. Although a locality-aware predicate specifies a predicate only within a local area, observing the area consistently requires considering the entire system in a consistent manner. This raises the challenge of making the complexities of the corresponding predicate detection algorithms scale-free, i.e., independent of the size of the system. Since all existing algorithms for getting a consistent view of the system require either a global snapshot of the entire system or vector clocks of the size of the system, a new solution is needed. We focus on stable LAP, which are those LAP that remain true once they become true. We propose a scale-free algorithm to detect stable LAP within a k$k$-height BFST. Our algorithm can detect both stable conjunctive LAP and stable relational LAP. In the process of designing our algorithm, we also propose the first distributed algorithm for building a BFST within an area of interest in a graph, and the first distributed algorithm for recording a consistent sub-cut within the area of interest. This paper demonstrates that LAPs are a natural fit for detecting distributed properties in large-scale distributed systems, and stable LAPs can be practically detected at low cost.     

A uniform approach for programming distributed heterogeneous computing systems

Large-scale compute clusters of heterogeneous nodes equipped with multi-core CPUs and GPUs are getting increasingly popular in the scientific community. However, such systems require a combination of different programming paradigms making application development very challenging.In this article we introduce libWater, a library-based extension of the OpenCL programming model that simplifies the development of heterogeneous distributed applications. libWater consists of a simple interface, which is a transparent abstraction of the underlying distributed architecture, offering advanced features such as inter-context and inter-node device synchronization. It provides a runtime system which tracks dependency information enforced by event synchronization to dynamically build a DAG of commands, on which we automatically apply two optimizations: collective communication pattern detection and device-host-device copy removal.We assess libWater’s performance in three compute clusters available from the Vienna Scientific Cluster, the Barcelona Supercomputing Center and the University of Innsbruck, demonstrating improved performance and scaling with different test applications and configurations.