An extended PID type iterative learning control

This paper presents a new iterative learning control (ILC) for discrete-time single-input single-output (SISO) linear time-invariant (LTI) systems. To establish this ILC, the input of the controlled system is modified by using a novel four-parametric algorithm. This algorithm is called the extended proportional plus integral and derivative (EPID) type, since by eliminating the fourth parameter of it one would get to the PID type ILC, therefore PID type ILC is a special case of it. The convergence of the proposed ILC is analyzed and an optimal method is presented to determine its parameters. It is shown that the given ILC has a better performance than the PID-type one. Three illustrative examples are included to demonstrate the effectiveness and the preference of the presented ILC.     

Oscillating bubbles in teardrop cavities for microflow control

Microstreaming generated from oscillating microbubbles has great potential in microfluidic applications for localized flow control. In this study, we explore the use of teardrop-shaped cavities for trapping microbubbles. Upon acoustic actuation, these microbubbles confined in teardrop cavities can be utilized to generate a directional microstreaming flow. We further show that by altering the acoustic excitation frequency, a flow-switch for altering flow direction in microfluidic environments can be achieved using two oppositely arranged teardrop cavities with different sizes. In the end, we show that an array of such bubble-filled teardrop cavities can act as a fixated microfluidic transport system allowing for on-chip particle manipulation in complex flow patterns. This inexpensive method to create flows to switch and transport elements based on teardrop cavities can be widely employed for microfluidic applications such as drug delivery systems.     

Micro-PIV measurements of induced-charge electro-osmosis around a metal rod

A cylindrical gold-coated stainless steel rod was positioned at the center of a straight microchannel connecting two fluid reservoirs on either end. The microchannel was filled with 1 mM KCl containing 0.5 μm diameter carboxylate-modified spherical particles. Induced-charge electro-osmotic (ICEO) flow occurred around the metallic rod under a sinusoidal AC electric field applied using two platinum electrodes. The ICEO flows around the metallic rod were measured using micro particle image velocimetry (micro-PIV) technique as functions of the AC electric field strength and frequency. The present study provides experimental data about ICEO flow in the weakly nonlinear limit of thin double layers, in which, the charging dynamics of the double layer cannot be presented analytically. The measured ICEO flow pattern qualitatively agrees with the theoretical results obtained by Squires and Bazant (J Fluid Mech 509:217–252, 2004). Flow around the rod is quadrupolar, driving liquid towards the rod along the electric field and forcing it away from the rod in the direction perpendicular to the imposed electric field. The measured ICEO flow velocity is proportional to the square of the electric field strength, and depends on the applied AC frequency.     

A hybrid aggregation and compression technique for road network databases

Vector data and in particular road networks are being queried, hosted and processed in many application domains such as in mobile computing. Many client systems such as PDAs would prefer to receive the query results in unrasterized format without introducing an overhead on overall system performance and result size. While several general vector data compression schemes have been studied by different communities, we propose a novel approach in vector data compression which is easily integrated within a geospatial query processing system. It uses line aggregation to reduce the number of relevant tuples and Huffman compression to achieve a multi-resolution compressed representation of a road network database. Our experiments performed on an end-to-end prototype verify that our approach exhibits fast query processing on both client and server sides as well as high compression ratio.

Strategic advantages of interoperability for global manufacturing using CNC technology

In the domain of manufacturing, computer numerically controllers (CNC) technology is a major contributor to the production capacity of the enterprises. The advances in CNC technology coupled with enhancements in computing systems have provided the basis to re-examine the way in which computer-aided systems (CAx) can be used to enable global manufacturing. Interoperability of the various components of the CAx chain is therefore a major prerequisite for manufacturing enterprises for becoming strategically agile and consequently globally competitive. Being interoperable, resources can be utilized interchangeably in a plug-and-produce manner. Over the last 8 years the eminence of a STEP standard for machining entitled STEP-NC (numerical control) has become a well-known vehicle for research to improve the level of information availability at the CNC machine tool. In this paper, the authors introduce the background to the evolution of CNC manufacturing over the last 50 years and the current standards available for programming. A review of the literature in interoperable CNC manufacturing is then provided relating to milling, turn–mill and other NC processes. The major part of the paper provides a strategic view of how interoperability can be implemented across the CAx chain with a range of standards used to regulate the flow of information. Finally, the paper outlines the advantages and major issues for future developments in interoperability, identifying future key requirements and limiting factors.     

A supply network-modelling system for a small- to medium-sized manufacturing company

During the late 1990s and early 2000s, the profile of global manufacturing has experienced many changes. There is anecdotal evidence that many western manufacturing companies have chosen to expand their manufacturing base across geographical boundaries. The common reasons sited for these ventures are to exploit less expensive labour markets, to establish a presence in expanding markets and in response to the threat of new competition. Whilst a global manufacturing base can prove to have many cost and sales benefits, there are also many disadvantages. Logistics operations can often increase in complexity leading to higher reliance on planning and effective interpretation of demand data. In response, systems modelling has remerged as a fertile research area after many years. Many modelling and simulation techniques have been developed, but these have had very limited practical success. The authors have identified that majority of these simulation techniques rely upon a detailed market structure being known, when this is rarely the case. This paper describes the outcome of a research project to develop of a pragmatic set of tools to gather, assess and verify supply chain structure data. A hybrid collection of technologies are utilised to assist these operations and to build a dynamic supply network model.     

New product development team intelligence: Antecedents and consequences

Our study investigated the effect of team knowledge on new product development (NPD). By investigating 207 NPD projects, we found that the declarative and procedural knowledge of the team and their use of IT had a positive influence on the team's knowledge base; and that the higher the functional diversity of the project team, the greater their overall knowledge. We also found that team knowledge positively impacted new product creativity and success in the market place.     

One-dimensional partitioning for heterogeneous systems: Theory and practice

We study the problem of one-dimensional partitioning of nonuniform workload arrays, with optimal load balancing for heterogeneous systems. We look at two cases: chain-on-chain partitioning, where the order of the processors is specified, and chain partitioning, where processor permutation is allowed. We present polynomial time algorithms to solve the chain-on-chain partitioning problem optimally, while we prove that the chain partitioning problem is NP-complete. Our empirical studies show that our proposed exact algorithms produce substantially better results than heuristics, while solution times remain comparable.