A tool for assessing reconfigurability of distributed manufacturing systems

In recent years, a large number of approaches to developing distributed manufacturing systems has been proposed. One of the principles reasons for these development has been to enhance the reconfigurability of a manufacturing operation; allowing it to readily adapt to changes over time. However, to date, there has only been a limited assessment of the resulting reconfigurability properties and hence it remains inconclusive as to whether a distributed manufacturing system design approach does in fact improve reconfigurability. This paper represents part of a study which investigates this issue. It proposes an assessment tool - the so called "Design Structure Matrix" as a means of assessing the modularity of elements in a manufacturing system. (Modularity has been shown to be a key characteristic of a reconfigurable manufacturing system.) The use of the Design Structure Matrix is illustrated in assessing a robot assembly cell designed on distributed manufacturing system principles. Copyright © 2006 IFAC.

Modular distributed manufacturing systems and the implications for integrated control

Driven by the need for more responsive manufacturing processes and as a consequence of increasing complexity in products and production systems, this short paper introduces a number of developments in the area of modular, distributed manufacturing systems. Requirements for the development of such systems are addressed and, in particular, the relevance to current and future integrated control systems is examined. One of the key issues for integrated control systems in the future is the need to provide support for distributed decision-making in addition to existing distributed control capabilities.

Experimental evaluation of layout designs for 3 × 3 MIMO-enabled radio-over-fiber distributed antenna systems

This paper experimentally demonstrates that, for two representative indoor distributed antenna system (DAS) scenarios, existing radio-over-fiber (RoF) DAS installations can enhance the capacity advantages of broadband 3 × 3 multiple-input-multiple-output (MIMO) radio services without requiring additional fibers or multiplexing schemes. This is true for both single-and multiple-user cases with a single base station and multiple base stations. First, a theoretical example is used to illustrate that there is a negligible improvement in signal-to-noise ratio (SNR) when using a MIMO DAS with all N spatial streams replicated at N RAUs, compared with a MIMO DAS with only one of the N streams replicated at each RAU for N ≤ 4. It is then experimentally confirmed that a 3 × 3 MIMO DAS offers improved capacity and throughput compared with a 3 × 3 MIMO collocated antenna system (CAS) for the single-user case in two typical indoor DAS scenarios, i.e., one with significant line-of-sight (LOS) propagation and the other with entirely non-line-of-sight (NLOS) propagation. The improvement in capacity is 3.2% and 4.1%, respectively. Then, experimental channel measurements confirm that there is a negligible capacity increase in the 3 × 3 configuration with three spatial streams per antenna unit over the 3 × 3 configuration with a single spatial stream per antenna unit. The former layout is observed to provide an increase of ∼1% in the median channel capacity in both the single-and multiple-user scenarios. With 20 users and three base stations, a MIMO DAS using the latter layout offers median aggregate capacities of 259 and 233 bit/s/Hz for the LOS and NLOS scenarios, respectively. It is concluded that DAS installations can further enhance the capacity offered to multiple users by multiple 3 × 3 MIMO-enabled base stations. Further, designing future DAS systems to support broadband 3 × 3 MIMO systems may not require significant upgrades to existing installations for small numbers of spatial streams. © 2013 IEEE.

Sequential decision making in general state space models

Many problems in control and signal processing can be formulated as sequential decision problems for general state space models. However, except for some simple models one cannot obtain analytical solutions and has to resort to approximation. In this thesis, we have investigated problems where Sequential Monte Carlo (SMC) methods can be combined with a gradient based search to provide solutions to online optimisation problems. We summarise the main contributions of the thesis as follows. Chapter 4 focuses on solving the sensor scheduling problem when cast as a controlled Hidden Markov Model. We consider the case in which the state, observation and action spaces are continuous. This general case is important as it is the natural framework for many applications. In sensor scheduling, our aim is to minimise the variance of the estimation error of the hidden state with respect to the action sequence. We present a novel SMC method that uses a stochastic gradient algorithm to find optimal actions. This is in contrast to existing works in the literature that only solve approximations to the original problem. In Chapter 5 we presented how an SMC can be used to solve a risk sensitive control problem. We adopt the use of the Feynman-Kac representation of a controlled Markov chain flow and exploit the properties of the logarithmic Lyapunov exponent, which lead to a policy gradient solution for the parameterised problem. The resulting SMC algorithm follows a similar structure with the Recursive Maximum Likelihood(RML) algorithm for online parameter estimation. In Chapters 6, 7 and 8, dynamic Graphical models were combined with with state space models for the purpose of online decentralised inference. We have concentrated more on the distributed parameter estimation problem using two Maximum Likelihood techniques, namely Recursive Maximum Likelihood (RML) and Expectation Maximization (EM). The resulting algorithms can be interpreted as an extension of the Belief Propagation (BP) algorithm to compute likelihood gradients. In order to design an SMC algorithm, in Chapter 8 uses a nonparametric approximations for Belief Propagation. The algorithms were successfully applied to solve the sensor localisation problem for sensor networks of small and medium size.

Radio over fibre enabled sensing and communications system for in building

This paper describes work on radio over fiber distributed antenna systems for improving the quality of radio coverage for in-building applications. The DAS network has also been shown to provide improved detection for Gen 2 UHF RFID tags. Using pre-distortion to reduce the problem of the RFID second harmonic, a simple heterogeneous sensing and communications system is demonstrated. © 2011 NOrthumbria University.

Experimental investigation of antenna selection and transmit beamforming for capacity enhancement in 3×3 MIMO-enabled radio-over-fiber DAS

This paper examines the impact of two simple precoding schemes on the capacity of 3 × 3 MIMO-enabled radio-over-fiber (RoF) distributed antenna systems (DAS) with excess transmit antennas. Specifically, phase-shift-only transmit beamforming and antenna selection are compared. It is found that for two typical indoor propagation scenarios, both strategies offer double the capacity gain that non-precoding MIMO DAS offers over traditional MIMO collocated antenna systems (CAS), with capacity improvements of 3.2-4.2 bit/s/Hz. Further, antenna selection shows similar performance to phase-only beamforming, differing by <0.5% and offering median capacities of 94 bit/s/Hz and 82 bit/s/Hz in the two propagation scenarios respectively. Because optical DASs enable precise, centralized control of remote antennas, they are well suited for implementing these beamforming schemes. Antenna selection, in particular, is a simple and effective means of increasing MIMO DAS capacity. © 2013 IEEE.