Transition from time-continuous systems to discrete mappings

Detailed transport studies in plasmas require the solution of the time evolution of many different initial positions of test particles in the phase space of the systems to be investigated. To reduce this amount of numerical work, one would like to replace the integration of the time-continues system with a mapping.

Impact of reduced complexity inverse Volterra series transfer function-based nonlinear equalizer in coherent OFDM systems for next-generation core networks

A modern electronic nonlinearity equalizer (NLE) based on inverse Volterra series transfer function (IVSTF) with reduced complexity is applied on coherent optical orthogonal frequency-division multiplexing (CO-OFDM) signals for next-generation long- and ultra-long-haul applications. The OFDM inter-subcarrier crosstalk effects are explored thoroughly using the IVSTF-NLE and compared with the case of linear equalization (LE) for transmission distances of up to 7000 km. © 2013 IEEE.

Demonstration of nonlinear inverse synthesis transmission over transoceanic distances

Nonlinear Fourier transform (NFT) and eigenvalue communication with the use of nonlinear signal spectrum (both discrete and continuous), have been recently discussed as promising transmission methods to combat fiber nonlinearity impairments. In this paper, for the first time, we demonstrate the generation, detection and transmission performance over transoceanic distances of 10 Gbaud and nonlinear inverse synthesis (NIS) based signal (4 Gb/s line rate), in which the transmitted information is encoded directly onto the continuous part of the signal nonlinear spectrum. By applying effective digital signal processing techniques, a reach of 7344 km was achieved with a bit-error-rate (BER) (2.1×10-2) below the 20% FEC threshold. This represents an improvement by a factor of ~12 in data capacity x distance product compared with other previously demonstrated NFT-based systems, showing a significant advance in the active research area of NFT-based communication systems.

A novel approach to modelling and exploiting uncertainty in stochastic control systems

We consider an inversion-based neurocontroller for solving control problems of uncertain nonlinear systems. Classical approaches do not use uncertainty information in the neural network models. In this paper we show how we can exploit knowledge of this uncertainty to our advantage by developing a novel robust inverse control method. Simulations on a nonlinear uncertain second order system illustrate the approach.

Improved robust control of nonlinear stochastic systems using uncertain models

We introduce a technique for quantifying and then exploiting uncertainty in nonlinear stochastic control systems. The approach is suboptimal though robust and relies upon the approximation of the forward and inverse plant models by neural networks, which also estimate the intrinsic uncertainty. Sampling from the resulting Gaussian distributions of the inversion based neurocontroller allows us to introduce a control law which is demonstrably more robust than traditional adaptive controllers.

Multi-valued control problems and mixture density network

We have proposed a novel robust inversion-based neurocontroller that searches for the optimal control law by sampling from the estimated Gaussian distribution of the inverse plant model. However, for problems involving the prediction of continuous variables, a Gaussian model approximation provides only a very limited description of the properties of the inverse model. This is usually the case for problems in which the mapping to be learned is multi-valued or involves hysteritic transfer characteristics. This often arises in the solution of inverse plant models. In order to obtain a complete description of the inverse model, a more general multicomponent distributions must be modeled. In this paper we test whether our proposed sampling approach can be used when considering an arbitrary conditional probability distributions. These arbitrary distributions will be modeled by a mixture density network. Importance sampling provides a structured and principled approach to constrain the complexity of the search space for the ideal control law. The effectiveness of the importance sampling from an arbitrary conditional probability distribution will be demonstrated using a simple single input single output static nonlinear system with hysteretic characteristics in the inverse plant model.

Robust control of nonlinear stochastic systems by modelling conditional distributions of control signals

We introduce a novel inversion-based neuro-controller for solving control problems involving uncertain nonlinear systems that could also compensate for multi-valued systems. The approach uses recent developments in neural networks, especially in the context of modelling statistical distributions, which are applied to forward and inverse plant models. Provided that certain conditions are met, an estimate of the intrinsic uncertainty for the outputs of neural networks can be obtained using the statistical properties of networks. More generally, multicomponent distributions can be modelled by the mixture density network. In this work a novel robust inverse control approach is obtained based on importance sampling from these distributions. This importance sampling provides a structured and principled approach to constrain the complexity of the search space for the ideal control law. The performance of the new algorithm is illustrated through simulations with example systems.

Using simulation to assess the introduction of technology in a continuous operations process

Purpose – To investigate the role of simulation in the introduction of technology in a continuous operations process. Design/methodology/approach – A case-based research method was chosen with the aim to provide an exemplar of practice and test the proposition that the use of simulation can improve the implementation and running of conveyor systems in continuous process facilities. Findings – The research determines the optimum rate of re-introduction of inventory to a conveyor system generated during a breakdown event. Research limitations/implications – More case studies are required demonstrating the operational and strategic benefits that can be gained by using simulation to assess technology in organisations. Practical implications – A practical outcome of the study was the implementation of a policy for the manual re-introduction of inventory on a conveyor line after a breakdown event had occurred. Originality/value – The paper presents a novel example of the use of simulation to estimate the re-introduction rate of inventory after a breakdown event on a conveyor line. The paper highlights how by addressing this operational issue, ahead of implementation, the likelihood of the success of the strategic decision to acquire the technology can be improved.

Canonical solution groups of a homomorphism : manipulator kinematics, nonparametric regression and distributed object systems

The kinematic mapping of a rigid open-link manipulator is a homomorphism between Lie groups. The homomorphisrn has solution groups that act on an inverse kinematic solution element. A canonical representation of solution group operators that act on a solution element of three and seven degree-of-freedom (do!) dextrous manipulators is determined by geometric analysis. Seven canonical solution groups are determined for the seven do! Robotics Research K-1207 and Hollerbach arms. The solution element of a dextrous manipulator is a collection of trivial fibre bundles with solution fibres homotopic to the Torus. If fibre solutions are parameterised by a scalar, a direct inverse funct.ion that maps the scalar and Cartesian base space coordinates to solution element fibre coordinates may be defined. A direct inverse pararneterisation of a solution element may be approximated by a local linear map generated by an inverse augmented Jacobian correction of a linear interpolation. The action of canonical solution group operators on a local linear approximation of the solution element of inverse kinematics of dextrous manipulators generates cyclical solutions. The solution representation is proposed as a model of inverse kinematic transformations in primate nervous systems. Simultaneous calibration of a composition of stereo-camera and manipulator kinematic models is under-determined by equi-output parameter groups in the composition of stereo-camera and Denavit Hartenberg (DH) rnodels. An error measure for simultaneous calibration of a composition of models is derived and parameter subsets with no equi-output groups are determined by numerical experiments to simultaneously calibrate the composition of homogeneous or pan-tilt stereo-camera with DH models. For acceleration of exact Newton second-order re-calibration of DH parameters after a sequential calibration of stereo-camera and DH parameters, an optimal numerical evaluation of DH matrix first order and second order error derivatives with respect to a re-calibration error function is derived, implemented and tested. A distributed object environment for point and click image-based tele-command of manipulators and stereo-cameras is specified and implemented that supports rapid prototyping of numerical experiments in distributed system control. The environment is validated by a hierarchical k-fold cross validated calibration to Cartesian space of a radial basis function regression correction of an affine stereo model. Basic design and performance requirements are defined for scalable virtual micro-kernels that broker inter-Java-virtual-machine remote method invocations between components of secure manageable fault-tolerant open distributed agile Total Quality Managed ISO 9000+ conformant Just in Time manufacturing systems.

Analysis of computer communication systems by use of digital signal processing methods

Queueing theory is an effective tool in the analysis of canputer camrunication systems. Many results in queueing analysis have teen derived in the form of Laplace and z-transform expressions. Accurate inversion of these transforms is very important in the study of computer systems, but the inversion is very often difficult. In this thesis, methods for solving some of these queueing problems, by use of digital signal processing techniques, are presented. The z-transform of the queue length distribution for the Mj GY jl system is derived. Two numerical methods for the inversion of the transfom, together with the standard numerical technique for solving transforms with multiple queue-state dependence, are presented. Bilinear and Poisson transform sequences are presented as useful ways of representing continuous-time functions in numerical computations.

A structural method for the design of fault tolerant distributed control systems

Distributed digital control systems provide alternatives to conventional, centralised digital control systems. Typically, a modern distributed control system will comprise a multi-processor or network of processors, a communications network, an associated set of sensors and actuators, and the systems and applications software. This thesis addresses the problem of how to design robust decentralised control systems, such as those used to control event-driven, real-time processes in time-critical environments. Emphasis is placed on studying the dynamical behaviour of a system and identifying ways of partitioning the system so that it may be controlled in a distributed manner. A structural partitioning technique is adopted which makes use of natural physical sub-processes in the system, which are then mapped into the software processes to control the system. However, communications are required between the processes because of the disjoint nature of the distributed (i.e. partitioned) state of the physical system. The structural partitioning technique, and recent developments in the theory of potential controllability and observability of a system, are the basis for the design of controllers. In particular, the method is used to derive a decentralised estimate of the state vector for a continuous-time system. The work is also extended to derive a distributed estimate for a discrete-time system. Emphasis is also given to the role of communications in the distributed control of processes and to the partitioning technique necessary to design distributed and decentralised systems with resilient structures. A method is presented for the systematic identification of necessary communications for distributed control. It is also shwon that the structural partitions can be used directly in the design of software fault tolerant concurrent controllers. In particular, the structural partition can be used to identify the boundary of the conversation which can be used to protect a specific part of the system. In addition, for certain classes of system, the partitions can be used to identify processes which may be dynamically reconfigured in the event of a fault. These methods should be of use in the design of robust distributed systems.

Continuous phase synchronised drives (for a rod-making machine)

Traditional high speed machinery actuators are powered and coordinated by mechanical linkages driven from a central drive, but these linkages may be replaced by independently synchronised electric drives. Problems associated with utilising such electric drives for this form of machinery were investigated. The research concentrated on a high speed rod-making machine, which required control of high inertias (0.01-0.5kgm2), at continuous high speed (2500 r/min), with low relative phase errors between two drives (0.0025 radians). Traditional minimum energy drive selection techniques for incremental motions were not applicable to continuous applications which require negligible energy dissipation. New selection techniques were developed. A brushless configuration constant enabled the comparison between seven different servo systems; the rate earth brushless drives had the best power rates which is a performance measure. Simulation was used to review control strategies, such that a microprocessor controller with a proportional velocity loop within a proportional position loop with velocity feedforward was designed. Local control schemes were investigated as means of reducing relative errors between drives: the slave of a master/slave scheme compensates for the master's errors: the matched scheme has drives with similar absolute errors so the relative error is minimised, and the feedforward scheme minimises error by adding compensation from previous knowledge. Simulation gave an approximate velocity loop bandwidth and position loop gain required to meet the specification. Theoretical limits for these parameters were defined in terms of digital sampling delays, quantisation, and system phase shifts. Performance degradation due to mechanical backlash was evaluated. Thus any drive could be checked to ensure that the performance specification could be realised. A two drive demonstrator was commissioned with 0.01kgm2 loads. By use of simulation the performance of one drive was improved by increasing the velocity loop bandwidth fourfold. With the master/slave scheme relative errors were within 0.0024 radians at a constant 2500 r/min for two 0.01 kgm^2 loads.

Dark solitons in optical communication systems

This thesis presents experimental and theoretical work on the use of dark optical solitons as data carriers in communications systems. The background chapters provide an introduction to nonlinear optics, and to dark solitons, described as intensity dips in a bright background, with an asymmetrical phase profile. The motivation for the work is explained, considering both the superior stability of dark solitons and the need for a soliton solution suitable for the normal, rather than the anomalous (bright soliton) dispersion regime. The first chapters present two generation techniques, producing packets of dark solitons via bright pulse interaction, and generating continuous trains of dark pulses using a fibre laser. The latter were not dark solitons, but were suitable for imposition of the required phase shift by virtue of their extreme stability. The later chapters focus on the propagation and control of dark solitons. Their response to periodic loss and gain is shown to result in the exponential growth of spectral sidebands. This may be suppressed by reducing the periodicity of the loss/gain cycle or using periodic filtering. A general study of the response of dark solitons to spectral filtering is undertaken, showing dramatic differences in the behaviour of black and 99.9% grey solitons. The importance of this result is highlighted by simulations of propagation in noisy systems, where the timing jitter resulting from random noise is actually enhanced by filtering. The results of using sinusoidal phase modulation to control pulse position are presented, showing that the control is at the expense of serious modulation of the bright background. It is concluded that in almost every case, dark and bright solitons have very different properties, and to continue to make comparisons would not be so productive as to develop a deeper understanding of the interactions between the dark soliton and its bright background.

Inference by replication in densely connected systems

An efficient Bayesian inference method for problems that can be mapped onto dense graphs is presented. The approach is based on message passing where messages are averaged over a large number of replicated variable systems exposed to the same evidential nodes. An assumption about the symmetry of the solutions is required for carrying out the averages; here we extend the previous derivation based on a replica-symmetric- (RS)-like structure to include a more complex one-step replica-symmetry-breaking-like (1RSB-like) ansatz. To demonstrate the potential of the approach it is employed for studying critical properties of the Ising linear perceptron and for multiuser detection in code division multiple access (CDMA) under different noise models. Results obtained under the RS assumption in the noncritical regime give rise to a highly efficient signal detection algorithm in the context of CDMA; while in the critical regime one observes a first-order transition line that ends in a continuous phase transition point. Finite size effects are also observed. While the 1RSB ansatz is not required for the original problems, it was applied to the CDMA signal detection problem with a more complex noise model that exhibits RSB behavior, resulting in an improvement in performance. © 2007 The American Physical Society.