The human factors of automatic speech recognition in control room systems

This thesis addresses the viability of automatic speech recognition for control room systems; with careful system design, automatic speech recognition (ASR) devices can be useful means for human computer interaction in specific types of task. These tasks can be defined as complex verbal activities, such as command and control, and can be paired with spatial tasks, such as monitoring, without detriment. It is suggested that ASR use be confined to routine plant operation, as opposed the critical incidents, due to possible problems of stress on the operators' speech.  It is proposed that using ASR will require operators to adapt a commonly used skill to cater for a novel use of speech. Before using the ASR device, new operators will require some form of training. It is shown that a demonstration by an experienced user of the device can lead to superior performance than instructions. Thus, a relatively cheap and very efficient form of operator training can be supplied by demonstration by experienced ASR operators. From a series of studies into speech based interaction with computers, it is concluded that the interaction be designed to capitalise upon the tendency of operators to use short, succinct, task specific styles of speech. From studies comparing different types of feedback, it is concluded that operators be given screen based feedback, rather than auditory feedback, for control room operation. Feedback will take two forms: the use of the ASR device will require recognition feedback, which will be best supplied using text; the performance of a process control task will require task feedback integrated into the mimic display. This latter feedback can be either textual or symbolic, but it is suggested that symbolic feedback will be more beneficial. Related to both interaction style and feedback is the issue of handling recognition errors. These should be corrected by simple command repetition practices, rather than use error handling dialogues. This method of error correction is held to be non intrusive to primary command and control operations. This thesis also addresses some of the problems of user error in ASR use, and provides a number of recommendations for its reduction.

Computerised control of cellular manufacturing systems

This thesis reviews the existing manufacturing control techniques and identifies their practical drawbacks when applied in a high variety, low and medium volume environment. It advocates that the significant drawbacks inherent in such systems, could impair their applications under such manufacturing environment. The key weaknesses identified in the system were: capacity insensitive nature of Material Requirements Planning (MRP); the centralised approach to planning and control applied in Manufacturing Resources Planning (MRP IT); the fact that Kanban can only be used in repetitive environments; Optimised Productivity Techniques's (OPT) inability to deal with transient bottlenecks, etc. On the other hand, cellular systems offer advantages in simplifying the control problems of manufacturing and the thesis reviews systems designed for cellular manufacturing including Distributed Manufacturing Resources Planning (DMRP) and Flexible Manufacturing System (FMS) controllers. It advocates that a newly developed cellular manufacturing control methodology, which is fully automatic, capacity sensitive and responsive, has the potential to resolve the core manufacturing control problems discussed above. It's development is envisaged within the framework of a DMRP environment, in which each cell is provided with its own MRP II system and decision making capability. It is a cellular based closed loop control system, which revolves on single level Bill-Of-Materials (BOM) structure and hence provides better linkage between shop level scheduling activities and relevant entries in the MPS. This provides a better prospect of undertaking rapid response to changes in the status of manufacturing resources and incoming enquiries. Moreover, it also permits automatic evaluation of capacity and due date constraints and hence facilitates the automation of MPS within such system. A prototype cellular manufacturing control model, was developed to demonstrate the underlying principles and operational logic of the cellular manufacturing control methodology, based on the above concept. This was shown to offer significant advantages from the prospective of operational planning and control. Results of relevant tests proved that the model is capable of producing reasonable due date and undertake automation of MPS. The overall performance of the model proved satisfactory and acceptable.

Neural network enhanced self tuning adaptive control application for non-linear control of dynamic systems

The main theme of research of this project concerns the study of neutral networks to control uncertain and non-linear control systems. This involves the control of continuous time, discrete time, hybrid and stochastic systems with input, state or output constraints by ensuring good performances. A great part of this project is devoted to the opening of frontiers between several mathematical and engineering approaches in order to tackle complex but very common non-linear control problems. The objectives are: 1. Design and develop procedures for neutral network enhanced self-tuning adaptive non-linear control systems; 2. To design, as a general procedure, neural network generalised minimum variance self-tuning controller for non-linear dynamic plants (Integration of neural network mapping with generalised minimum variance self-tuning controller strategies); 3. To develop a software package to evaluate control system performances using Matlab, Simulink and Neural Network toolbox. An adaptive control algorithm utilising a recurrent network as a model of a partial unknown non-linear plant with unmeasurable state is proposed. Appropriately, it appears that structured recurrent neural networks can provide conveniently parameterised dynamic models for many non-linear systems for use in adaptive control. Properties of static neural networks, which enabled successful design of stable adaptive control in the state feedback case, are also identified. A survey of the existing results is presented which puts them in a systematic framework showing their relation to classical self-tuning adaptive control application of neural control to a SISO/MIMO control. Simulation results demonstrate that the self-tuning design methods may be practically applicable to a reasonably large class of unknown linear and non-linear dynamic control systems.

A novel actuated digit with tactile feedback for clinical applications

This thesis describes the work carried out on the development of a novel digit actuator system with tactile perception feedback to a user and demonstrated as a master-slave system. For the tactile surface of the digit, contrasting sensor elements of resistive strain gauges and optical fibre Bragg grating sensors were evaluated. A distributive tactile sensing system consisting of optimised neural networking schemes was developed, resulting in taxonomy of artificial touch. The device is suitable for use in minimal invasive surgical (MIS) procedures as a steerable tip and a digit constructed wholly from polymers makes it suitable for use in Magnetic Resonance Imaging (MRI) environments enabling active monitoring of the patient during a procedure. To provide a realistic template of the work the research responded to the needs of two contrasting procedures: palpation of the prostate and endotracheal intubation in anaesthesia where the application of touch sense can significantly assist navigation. The performance of the approach was demonstrated with an experimental digit constructed for use in the laboratory in phantom trials. The phantom unit was developed to resemble facets of the clinical applications and digit system is able to evaluate reactive force distributions acting over the surface of the digit as well as different descriptions of contact and motion relative to the surface of the lumen. Completing control of the digit is via an instrumented glove, such that the digit actuates in sympathy with finger gesture and tactile information feedback is achieved by a combination of the tactile and visual means.

Design methodology for the servo control of high speed multi-axis machinery (BL): decoupling and synchronisation of a generic machine by blockwise decentralised MIMO control

Traditional machinery for manufacturing processes are characterised by actuators powered and co-ordinated by mechanical linkages driven from a central drive. Increasingly, these linkages are replaced by independent electrical drives, each performs a different task and follows a different motion profile, co-ordinated by computers. A design methodology for the servo control of high speed multi-axis machinery is proposed, based on the concept of a highly adaptable generic machine model. In addition to the dynamics of the drives and the loads, the model includes the inherent interactions between the motion axes and thus provides a Multi-Input Multi-Output (MIMO) description. In general, inherent interactions such as structural couplings between groups of motion axes are undesirable and needed to be compensated. On the other hand, imposed interactions such as the synchronisation of different groups of axes are often required. It is recognised that a suitable MIMO controller can simultaneously achieve these objectives and reconciles their potential conflicts. Both analytical and numerical methods for the design of MIMO controllers are investigated. At present, it is not possible to implement high order MIMO controllers for practical reasons. Based on simulations of the generic machine model under full MIMO control, however, it is possible to determine a suitable topology for a blockwise decentralised control scheme. The Block Relative Gain array (BRG) is used to compare the relative strength of closed loop interactions between sub-systems. A number of approaches to the design of the smaller decentralised MIMO controllers for these sub-systems has been investigated. For the purpose of illustration, a benchmark problem based on a 3 axes test rig has been carried through the design cycle to demonstrate the working of the design methodology.

Active vibration control at machinery feet

The unmitigated transmission of undesirable vibration can result in problems by way of causing human discomfort, machinery and equipment failure, and affecting the quality of a manufacturing process. When identifiable transmission paths are discernible, vibrations from the source can be isolated from the rest of the system and this prevents or minimises the problems. The approach proposed here for vibration isolation is active force cancellation at points close to the vibration source. It uses force feedback for multiple-input and multiple-output control at the mounting locations. This is particularly attractive for rigid mounting of machine on relative flexible base where machine alignment and motions are to be restricted. The force transfer function matrix is used as a disturbance rejection performance specification for the design of MIMO controllers. For machine soft-mounted via flexible isolators, a model for this matrix has been derived. Under certain conditions, a simple multiplicative uncertainty model is obtained that shows the amount of perturbation a flexible base has on the machine-isolator-rigid base transmissibility matrix. Such a model is very suitable for use with robust control design paradigm. A different model is derived for the machine on hard-mounts without the flexible isolators. With this model, the level of force transmitted from a machine to a final mounting structure using the measurements for the machine running on another mounting structure can be determined. The two mounting structures have dissimilar dynamic characteristics. Experiments have verified the usefulness of the expression. The model compares well with other methods in the literature. The disadvantage lies with the large amount of data that has to be collected. Active force cancellation is demonstrated on an experimental rig using an AC industrial motor hard-mounted onto a relative flexible structure. The force transfer function matrix, determined from measurements, is used to design H and Static Output Feedback controllers. Both types of controllers are stable and robust to modelling errors within the identified frequency range. They reduce the RMS of transmitted force by between 30?80% at all mounting locations for machine running at 1340 rpm. At the rated speed of 1440 rpm only the static gain controller is able to provide 30?55% reduction at all locations. The H controllers on the other hand could only give a small reduction at one mount location. This is due in part to the deficient of the model used in the design. Higher frequency dynamics has been ignored in the model. This can be resolved by the use of a higher order model that can result in a high order controller. A low order static gain controller, with some tuning, performs better. But it lacks the analytical framework for analysis and design.

Design and analysis of distributed utility maximization algorithm for multihop wireless network with inaccurate feedback

Distributed network utility maximization (NUM) is receiving increasing interests for cross-layer optimization problems in multihop wireless networks. Traditional distributed NUM algorithms rely heavily on feedback information between different network elements, such as traffic sources and routers. Because of the distinct features of multihop wireless networks such as time-varying channels and dynamic network topology, the feedback information is usually inaccurate, which represents as a major obstacle for distributed NUM application to wireless networks. The questions to be answered include if distributed NUM algorithm can converge with inaccurate feedback and how to design effective distributed NUM algorithm for wireless networks. In this paper, we first use the infinitesimal perturbation analysis technique to provide an unbiased gradient estimation on the aggregate rate of traffic sources at the routers based on locally available information. On the basis of that, we propose a stochastic approximation algorithm to solve the distributed NUM problem with inaccurate feedback. We then prove that the proposed algorithm can converge to the optimum solution of distributed NUM with perfect feedback under certain conditions. The proposed algorithm is applied to the joint rate and media access control problem for wireless networks. Numerical results demonstrate the convergence of the proposed algorithm. © 2013 John Wiley & Sons, Ltd.

Design and analysis of distributed utility maximization algorithm for multihop wireless network with inaccurate feedback

Distributed network utility maximization (NUM) is receiving increasing interests for cross-layer optimization problems in multihop wireless networks. Traditional distributed NUM algorithms rely heavily on feedback information between different network elements, such as traffic sources and routers. Because of the distinct features of multihop wireless networks such as time-varying channels and dynamic network topology, the feedback information is usually inaccurate, which represents as a major obstacle for distributed NUM application to wireless networks. The questions to be answered include if distributed NUM algorithm can converge with inaccurate feedback and how to design effective distributed NUM algorithm for wireless networks. In this paper, we first use the infinitesimal perturbation analysis technique to provide an unbiased gradient estimation on the aggregate rate of traffic sources at the routers based on locally available information. On the basis of that, we propose a stochastic approximation algorithm to solve the distributed NUM problem with inaccurate feedback. We then prove that the proposed algorithm can converge to the optimum solution of distributed NUM with perfect feedback under certain conditions. The proposed algorithm is applied to the joint rate and media access control problem for wireless networks. Numerical results demonstrate the convergence of the proposed algorithm. © 2013 John Wiley & Sons, Ltd.

Design and evaluation of a framework for cooperative and adaptive QoS control of DSRC network for road safety applications

Dedicated short-range communications (DSRC) are a promising vehicle communication technique for collaborative road safety applications (CSA). However, road safety applications require highly reliable and timely wireless communications, which present big challenges to DSRC based vehicle networks on effective and robust quality of services (QoS) provisioning due to the random channel access method applied in the DSRC technique. In this paper we examine the QoS control problem for CSA in the DSRC based vehicle networks and presented an overview of the research work towards the QoS control problem. After an analysis of the system application requirements and the DSRC vehicle network features, we propose a framework for cooperative and adaptive QoS control, which is believed to be a key for the success of DSRC on supporting effective collaborative road safety applications. A core design in the proposed QoS control framework is that network feedback and cross-layer design are employed to collaboratively achieve targeted QoS. A design example of cooperative and adaptive rate control scheme is implemented and evaluated, with objective of illustrating the key ideas in the framework. Simulation results demonstrate the effectiveness of proposed rate control schemes in providing highly available and reliable channel for emergency safety messages. © 2013 Wenyang Guan et al.

Flexible tactile digital feedback for clinical applications

Trauma and damage to the delicate structures of the inner ear frequently occurs during insertion of electrode array into the cochlea. This is strongly related to the excessive manual insertion force of the surgeon without any tool/tissue interaction feedback. The research is examined tool-tissue interaction of large prototype scale (12.5:1) digit embedded with distributive tactile sensor based upon cochlear electrode and large prototype scale (4.5:1) cochlea phantom for simulating the human cochlear which could lead to small scale digit requirements. This flexible digit classified the tactile information from the digit-phantom interaction such as contact status, tip penetration, obstacles, relative shape and location, contact orientation and multiple contacts. The digit, distributive tactile sensors embedded with silicon-substrate is inserted into the cochlea phantom to measure any digit/phantom interaction and position of the digit in order to minimize tissue and trauma damage during the electrode cochlear insertion. The digit is pre-curved in cochlea shape so that the digit better conforms to the shape of the scala tympani to lightly hug the modiolar wall of a scala. The digit have provided information on the characteristics of touch, digit-phantom interaction during the digit insertion. The tests demonstrated that even devices of such a relative simple design with low cost have potential to improve cochlear implants surgery and other lumen mapping applications by providing tactile feedback information by controlling the insertion through sensing and control of the tip of the implant during the insertion. In that approach, the surgeon could minimize the tissue damage and potential damage to the delicate structures within the cochlear caused by current manual electrode insertion of the cochlear implantation. This approach also can be applied diagnosis and path navigation procedures. The digit is a large scale stage and could be miniaturized in future to include more realistic surgical procedures.

Reporting and managing risk:a look at current practice at Tesco, RBS, local and central government

These case studies from CIMA highlight the need to embed risk management within more easily understood behaviours, consistent with the overall organisational culture. In each case, some form of internal audit team provides either an oversight function or acts as an expert link in that feedback loop. Frontline staff, managers and specialists should be completely aligned on risk, in part just to ensure that there is a consistency of approach. They should understand instinctively that good performance includes good risk management. Tesco has continued to thrive during the recession and remains a robust and efficient group of businesses despite the emergence of potential threats around consumer spending and the supply chain. RBS, by contrast, has suffered catastrophic and very public failures of risk management despite a large in-house function and stiff regulation of risk controls. Birmingham City Council, like all local authorities, is adapting to more commercial modes of operation and is facing diverse threats and opportunities emerging as a result of social change. And DCMS, like many other public sector organisations, has to handle an incredibly complex network of delivery partners within the context of a relatively recent overhaul of central government risk management processes. Key Findings: •Risk management is no longer solely a financial discipline, nor is it simply a concern for the internal control function. •Where organisations retain a discrete risk management cadre – often specialists at monitoring and evaluating a range of risks – their success is dependent on embedding risk awareness in the wider culture of the enterprise. •Risk management is most successful when it is explicitly linked to operational performance. •Clear leadership, specific goals, excellent influencing skills and open-mindedness to potential threats and opportunities are essential for effective risk management. •Bureaucratic processes and systems can hamper good risk management – either as a result of a ‘box-ticking mentality’ or because managers and staff believe they do not need to consider risk themselves.

Sympathetic control of accommodation:evidence for inter-subject variation

Autonomic innervation of ciliary smooth muscle is mediated principally by the parasympathetic nervous system and is supplemented by the sympathetic nervous system. Previous drug and nerve stimulation experiments on humans and animals have demonstrated that sympathetic innervation is inhibitory (via β-2 adrenoceptors), relatively small, slow and augmented by concurrent levels of background parasympathetic activity. These characteristics are pertinent to the sympathetic system having a specific role in our ability to adapt successfully to sustained near vision tasks and, given the clear association between near vision and the onset and development of myopia, to a putative aetiological role in myopia development in pre-disposed individuals. A fifth characteristic, namely the variation between individuals in access to an inhibitory sympathetic facility is therefore of particular interest. A novel method for continuous recording of accommodation, currently employed in a large sample longitudinal study of myopia in young adults, was used following topical instillation of non-selective (timolol) and selective (betaxolol) sympathetic β-adrenoceptor antagonists. Measures of post-task accommodative hysteresis were taken with reference to the time-course of regression of accommodation when open-loop (Difference of Gaussian) conditions were immediately imposed following short (10 s) and long (3 min) duration far (0D) and near (3D above tonic level) tasks viewed through a Badal system. Data confirm earlier informal experimental observations that only one in three individuals are likely to have access to a sympathetic inhibitory facility during sustained near vision. © 2002 The College of Optometrists.

Fully probabilistic control for stochastic nonlinear control systems with input dependent noise

Robust controllers for nonlinear stochastic systems with functional uncertainties can be consistently designed using probabilistic control methods. In this paper a generalised probabilistic controller design for the minimisation of the Kullback-Leibler divergence between the actual joint probability density function (pdf) of the closed loop control system, and an ideal joint pdf is presented emphasising how the uncertainty can be systematically incorporated in the absence of reliable systems models. To achieve this objective all probabilistic models of the system are estimated from process data using mixture density networks (MDNs) where all the parameters of the estimated pdfs are taken to be state and control input dependent. Based on this dependency of the density parameters on the input values, explicit formulations to the construction of optimal generalised probabilistic controllers are obtained through the techniques of dynamic programming and adaptive critic methods. Using the proposed generalised probabilistic controller, the conditional joint pdfs can be made to follow the ideal ones. A simulation example is used to demonstrate the implementation of the algorithm and encouraging results are obtained.

Probabilistic control for uncertain systems

In this paper a new framework has been applied to the design of controllers which encompasses nonlinearity, hysteresis and arbitrary density functions of forward models and inverse controllers. Using mixture density networks, the probabilistic models of both the forward and inverse dynamics are estimated such that they are dependent on the state and the control input. The optimal control strategy is then derived which minimizes uncertainty of the closed loop system. In the absence of reliable plant models, the proposed control algorithm incorporates uncertainties in model parameters, observations, and latent processes. The local stability of the closed loop system has been established. The efficacy of the control algorithm is demonstrated on two nonlinear stochastic control examples with additive and multiplicative noise.