Shareholder value application in UK listed companies

This paper is based upon the initial findings of a CIMA research project into the way in which corporate performance measurement systems are influenced by the use of shareholder value management techniques. It compares and contrasts the techniques in use in a sample of 10 companies that either explicitly use shareholder value techniques also known as Value-Based Management (VBM), or explicitly do not use such techniques. The analysis undertaken is based upon the finding of semi-structured interviews with company representatives which formed the first part of the data collection process of the project. The analysis traces the interactions between corporate objectives, decision making criteria, performance measurement systems and executive incentive schemes in order to develop an understanding of the effects of such shareholder value techniques upon corporate behaviour. The literature reviewed suggests that the other aspects of the planning and control system should be aligned with the corporate objectives whether a company has adopted VBM or not. Therefore this research contributes new evidence on the use of VBM techniques in the UK and also more generally on whether VBM and non-VBM companies internal planning and control systems are aligned.

Modelling and control of a hybrid stepping motor

The integration of a microprocessor and a medium power stepper motor in one control system brings together two quite different disciplines. Various methods of interfacing are examined and the problems involved in both hardware and software manipulation are investigated. Microprocessor open-loop control of the stepper motor is considered. The possible advantages of microprocessor closed-loop control are examined and the development of a system is detailed. The system uses position feedback to initiate each motor step. Results of the dynamic response of the system are presented and its performance discussed. Applications of the static torque characteristic of the stepper motor are considered followed by a review of methods of predicting the characteristic. This shows that accurate results are possible only when the effects of magnetic saturation are avoided or when the machine is available for magnetic circuit tests to be carried out. A new method of predicting the static torque characteristic is explained in detail. The method described uses the machine geometry and the magnetic characteristics of the iron types used in the machine. From this information the permeance of each iron component of the machine is calculated and by using the equivalent magnetic circuit of the machine, the total torque produced is predicted. It is shown how this new method is implemented on a digital computer and how the model may be used to investigate further aspects of the stepper motor in addition to the static torque.

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.

Mathematical modelling and control of agitated extraction columns

Liquid-liquid extraction has long been known as a unit operation that plays an important role in industry. This process is well known for its complexity and sensitivity to operation conditions. This thesis presents an attempt to explore the dynamics and control of this process using a systematic approach and state of the art control system design techniques. The process was studied first experimentally under carefully selected. operation conditions, which resembles the ranges employed practically under stable and efficient conditions. Data were collected at steady state conditions using adequate sampling techniques for the dispersed and continuous phases as well as during the transients of the column with the aid of a computer-based online data logging system and online concentration analysis. A stagewise single stage backflow model was improved to mimic the dynamic operation of the column. The developed model accounts for the variation in hydrodynamics, mass transfer, and physical properties throughout the length of the column. End effects were treated by addition of stages at the column entrances. Two parameters were incorporated in the model namely; mass transfer weight factor to correct for the assumption of no mass transfer in the. settling zones at each stage and the backmixing coefficients to handle the axial dispersion phenomena encountered in the course of column operation. The parameters were estimated by minimizing the differences between the experimental and the model predicted concentration profiles at steady state conditions using non-linear optimisation technique. The estimated values were then correlated as functions of operating parameters and were incorporated in·the model equations. The model equations comprise a stiff differential~algebraic system. This system was solved using the GEAR ODE solver. The calculated concentration profiles were compared to those experimentally measured. A very good agreement of the two profiles was achieved within a percent relative error of ±2.S%. The developed rigorous dynamic model of the extraction column was used to derive linear time-invariant reduced-order models that relate the input variables (agitator speed, solvent feed flowrate and concentration, feed concentration and flowrate) to the output variables (raffinate concentration and extract concentration) using the asymptotic method of system identification. The reduced-order models were shown to be accurate in capturing the dynamic behaviour of the process with a maximum modelling prediction error of I %. The simplicity and accuracy of the derived reduced-order models allow for control system design and analysis of such complicated processes. The extraction column is a typical multivariable process with agitator speed and solvent feed flowrate considered as manipulative variables; raffinate concentration and extract concentration as controlled variables and the feeds concentration and feed flowrate as disturbance variables. The control system design of the extraction process was tackled as multi-loop decentralised SISO (Single Input Single Output) as well as centralised MIMO (Multi-Input Multi-Output) system using both conventional and model-based control techniques such as IMC (Internal Model Control) and MPC (Model Predictive Control). Control performance of each control scheme was. studied in terms of stability, speed of response, sensitivity to modelling errors (robustness), setpoint tracking capabilities and load rejection. For decentralised control, multiple loops were assigned to pair.each manipulated variable with each controlled variable according to the interaction analysis and other pairing criteria such as relative gain array (RGA), singular value analysis (SVD). Loops namely Rotor speed-Raffinate concentration and Solvent flowrate Extract concentration showed weak interaction. Multivariable MPC has shown more effective performance compared to other conventional techniques since it accounts for loops interaction, time delays, and input-output variables constraints.

An institutional perspective on management accounting change in the public sector : a case study from Canada

This thesis reports on a four-year field study conducted at the Saskatchewan regional office of the Department of Indian Affairs and Northern Development, a large department of the Government of Canada. Over the course of the study, a sweeping government-wide accounting reform took place entitled the Financial Information Strategy. An ethnographic study was conducted that documented the management accounting processes in place at the regional office prior to the Financial Information Strategy reform, the organization’s adoption of the new accounting system associated with this initiative, and the state of the organization’s management accounting system once the implementation was complete. This research, therefore, captures in detail a management accounting change process in a public sector organization. This study employs an interpretive perspective and draws on institution theory as a theoretical framework. The concept of loose coupling and insights from the literature on professions were also employed in the explanation-building process for the case. This research contributes to institution theory and the study of management accounting change by recognizing conflicting institutional forces at the organizational level. An existing Old Institutional Economics-based conceptual framework for management accounting change is advanced and improved upon through the development of a new conceptual framework that incorporates the influence of wider institutional forces, the concepts of open and closed organizational systems and loose coupling, and the recognition of varying rates of change and institutionalization of organizational activity sets. Our understanding of loose coupling is enhanced by the interpretation of institutional influences developed in this study as is the role of professionalization as a normative influence in public sector organizations.

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.

Simulation of robot manipulator control strategies

The high capital cost of robots prohibit their economic application. One method of making their application more economic is to increase their operating speed. This can be done in a number of ways e.g. redesign of robot geometry, improving actuators and improving control system design. In this thesis the control system design is considered. It is identified in the literature review that two aspects in relation to robot control system design have not been addressed in any great detail by previous researchers. These are: how significant are the coupling terms in the dynamic equations of the robot and what is the effect of the coupling terms on the performance of a number of typical independent axis control schemes?. The work in this thesis addresses these two questions in detail. A program was designed to automatically calculate the path and trajectory and to calculate the significance of the coupling terms in an example application of a robot manipulator tracking a part on a moving conveyor. The inertial and velocity coupling terms have been shown to be of significance when the manipulator was considered to be directly driven. A simulation of the robot manipulator following the planned trajectory has been established in order to assess the performance of the independent axis control strategies. The inertial coupling was shown to reinforce the control torque at the corner points of the trajectory, where there was an abrupt demand in acceleration in each axis but of opposite sign. This reduced the tracking error however, this effect was not controllable. A second effect was due to the velocity coupling terms. At high trajectory speeds it was shown, by means of a root locus analysis, that the velocity coupling terms caused the system to become unstable.

Differences between theoretical predictions and operational performance in a stock control application

Over the past decade, several experienced Operational Researchers have advanced the view that the theoretical aspects of model building have raced ahead of the ability of people to use them. Consequently, the impact of Operational Research on commercial organisations and the public sector is limited, and many systems fail to achieve their anticipated benefits in full. The primary objective of this study is to examine a complex interactive Stock Control system, and identify the reasons for the differences between the theoretical expectations and the operational performance. The methodology used is to hypothesise all the possible factors which could cause a divergence between theory and practice, and to evaluate numerically the effect each of these factors has on two main control indices - Service Level and Average Stock Value. Both analytical and empirical methods are used, and simulation is employed extensively. The factors are divided into two main categories for analysis - theoretical imperfections in the model, and the usage of the system by Buyers. No evidence could be found in the literature of any previous attempts to place the differences between theory and practice in a system in quantitative perspective nor, more specifically, to study the effects of Buyer/computer interaction in a Stock Control system. The study reveals that, in general, the human factors influencing performance are of a much higher order of magnitude than the theoretical factors, thus providing objective evidence to support the original premise. The most important finding is that, by judicious intervention into an automatic stock control algorithm, it is possible for Buyers to produce results which not only attain but surpass the algorithmic predictions. However, the complexity and behavioural recalcitrance of these systems are such that an innately numerate, enquiring type of Buyer needs to be inducted to realise the performance potential of the overall man/computer system.

The dynamics and control of a remotely piloted plan-symmetric helicopter

Prior to the development of a production standard control system for ML Aviation's plan-symmetric remotely piloted helicopter system, SPRITE, optimum solutions to technical requirements had yet to be found for some aspects of the work. This thesis describes an industrial project where solutions to real problems have been provided within strict timescale constraints. Use has been made of published material wherever appropriate, new solutions have been contributed where none existed previously. A lack of clearly defined user requirements from potential Remotely Piloted Air Vehicle (RPAV) system users is identified, A simulation package is defined to enable the RPAV designer to progress with air vehicle and control system design, development and evaluation studies and to assist the user to investigate his applications. The theoretical basis of this simulation package is developed including Co-axial Contra-rotating Twin Rotor (CCTR), six degrees of freedom motion, fuselage aerodynamics and sensor and control system models. A compatible system of equations is derived for modelling a miniature plan-symmetric helicopter. Rigorous searches revealed a lack of CCTR models, based on closed form expressions to obviate integration along the rotor blade, for stabilisation and navigation studies through simulation. An economic CCTR simulation model is developed and validated by comparison with published work and practical tests. Confusion in published work between attitude and Euler angles is clarified. The implementation of package is discussed. dynamic adjustment of assessment. the theory into a high integrity software Use is made of a novel technique basing the integration time step size on error Simulation output for control system stability verification, cross coupling of motion between control channels and air vehicle response to demands and horizontal wind gusts studies are presented. Contra-Rotating Twin Rotor Flight Control System Remotely Piloted Plan-Symmetric Helicopter Simulation Six Degrees of Freedom Motion ( i i)

Modelling manufacturing planning and control systems:the application of object-oriented principles and discrete-event simulation

Manufacturing planning and control systems are fundamental to the successful operations of a manufacturing organisation. 10 order to improve their business performance, significant investment is made by companies into planning and control systems; however, not all companies realise the benefits sought Many companies continue to suffer from high levels of inventory, shortages, obsolete parts, poor resource utilisation and poor delivery performance. This thesis argues that the fit between the planning and control system and the manufacturing organisation is a crucial element of success. The design of appropriate control systems is, therefore, important. The different approaches to the design of manufacturing planning and control systems are investigated. It is concluded that there is no provision within these design methodologies to properly assess the impact of a proposed design on the manufacturing facility. Consequently, an understanding of how a new (or modified) planning and control system will perform in the context of the complete manufacturing system is unlikely to be gained until after the system has been implemented and is running. There are many modelling techniques available, however discrete-event simulation is unique in its ability to model the complex dynamics inherent in manufacturing systems, of which the planning and control system is an integral component. The existing application of simulation to manufacturing control system issues is limited: although operational issues are addressed, application to the more fundamental design of control systems is rarely, if at all, considered. The lack of a suitable simulation-based modelling tool does not help matters. The requirements of a simulation tool capable of modelling a host of different planning and control systems is presented. It is argued that only through the application of object-oriented principles can these extensive requirements be achieved. This thesis reports on the development of an extensible class library called WBS/Control, which is based on object-oriented principles and discrete-event simulation. The functionality, both current and future, offered by WBS/Control means that different planning and control systems can be modelled: not only the more standard implementations but also hybrid systems and new designs. The flexibility implicit in the development of WBS/Control supports its application to design and operational issues. WBS/Control wholly integrates with an existing manufacturing simulator to provide a more complete modelling environment.

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.

A multi-modular second life hybrid battery energy storage system for utility grid applications

The modern grid system or the smart grid is likely to be populated with multiple distributed energy sources, e.g. wind power, PV power, Plug-in Electric Vehicle (PEV). It will also include a variety of linear and nonlinear loads. The intermittent nature of renewable energies like PV, wind turbine and increased penetration of Electric Vehicle (EV) makes the stable operation of utility grid system challenging. In order to ensure a stable operation of the utility grid system and to support smart grid functionalities such as, fault ride-through, frequency response, reactive power support, and mitigation of power quality issues, an energy storage system (ESS) could play an important role. A fast acting bidirectional energy storage system which can rapidly provide and absorb power and/or VARs for a sufficient time is a potentially valuable tool to support this functionality. Battery energy storage systems (BESS) are one of a range suitable energy storage system because it can provide and absorb power for sufficient time as well as able to respond reasonably fast. Conventional BESS already exist on the grid system are made up primarily of new batteries. The cost of these batteries can be high which makes most BESS an expensive solution. In order to assist moving towards a low carbon economy and to reduce battery cost this work aims to research the opportunities for the re-use of batteries after their primary use in low and ultra-low carbon vehicles (EV/HEV) on the electricity grid system. This research aims to develop a new generation of second life battery energy storage systems (SLBESS) which could interface to the low/medium voltage network to provide necessary grid support in a reliable and in cost-effective manner. The reliability/performance of these batteries is not clear, but is almost certainly worse than a new battery. Manufacturers indicate that a mixture of gradual degradation and sudden failure are both possible and failure mechanisms are likely to be related to how hard the batteries were driven inside the vehicle. There are several figures from a number of sources including the DECC (Department of Energy and Climate Control) and Arup and Cenex reports indicate anything from 70,000 to 2.6 million electric and hybrid vehicles on the road by 2020. Once the vehicle battery has degraded to around 70-80% of its capacity it is considered to be at the end of its first life application. This leaves capacity available for a second life at a much cheaper cost than a new BESS Assuming a battery capability of around 5-18kWhr (MHEV 5kWh - BEV 18kWh battery) and approximate 10 year life span, this equates to a projection of battery storage capability available for second life of >1GWhrs by 2025. Moreover, each vehicle manufacturer has different specifications for battery chemistry, number and arrangement of battery cells, capacity, voltage, size etc. To enable research and investment in this area and to maximize the remaining life of these batteries, one of the design challenges is to combine these hybrid batteries into a grid-tie converter where their different performance characteristics, and parameter variation can be catered for and a hot swapping mechanism is available so that as a battery ends it second life, it can be replaced without affecting the overall system operation. This integration of either single types of batteries with vastly different performance capability or a hybrid battery system to a grid-tie 3 energy storage system is different to currently existing work on battery energy storage systems (BESS) which deals with a single type of battery with common characteristics. This thesis addresses and solves the power electronic design challenges in integrating second life hybrid batteries into a grid-tie energy storage unit for the first time. This study details a suitable multi-modular power electronic converter and its various switching strategies which can integrate widely different batteries to a grid-tie inverter irrespective of their characteristics, voltage levels and reliability. The proposed converter provides a high efficiency, enhanced control flexibility and has the capability to operate in different operational modes from the input to output. Designing an appropriate control system for this kind of hybrid battery storage system is also important because of the variation of battery types, differences in characteristics and different levels of degradations. This thesis proposes a generalised distributed power sharing strategy based on weighting function aims to optimally use a set of hybrid batteries according to their relative characteristics while providing the necessary grid support by distributing the power between the batteries. The strategy is adaptive in nature and varies as the individual battery characteristics change in real time as a result of degradation for example. A suitable bidirectional distributed control strategy or a module independent control technique has been developed corresponding to each mode of operation of the proposed modular converter. Stability is an important consideration in control of all power converters and as such this thesis investigates the control stability of the multi-modular converter in detailed. Many controllers use PI/PID based techniques with fixed control parameters. However, this is not found to be suitable from a stability point-of-view. Issues of control stability using this controller type under one of the operating modes has led to the development of an alternative adaptive and nonlinear Lyapunov based control for the modular power converter. Finally, a detailed simulation and experimental validation of the proposed power converter operation, power sharing strategy, proposed control structures and control stability issue have been undertaken using a grid connected laboratory based multi-modular hybrid battery energy storage system prototype. The experimental validation has demonstrated the feasibility of this new energy storage system operation for use in future grid applications.

High-Order Control Variations and Small-Time Local Controllability

The importance of “control variations” for obtaining local approximations of the reachable set of nonlinear control systems is well known. Heuristically, if one can construct control variations in all possible directions, then the considered control system is small-time locally controllable (STLC). Two concepts of control variations of higher order are introduced for the case of smooth control systems. The relation between these variations and the small-time local controllability is studied and a new sufficient STLC condition is proved.

Large volume metrology technologies for the light controlled factory

In the Light Controlled Factory part-to-part assembly and reduced weight will be enabled through the use of predictive fitting processes; low cost high accuracy reconfigurable tooling will be made possible by active compensation; improved control will allow accurate robotic machining; and quality will be improved through the use of traceable uncertainty based quality control throughout the production system. A number of challenges must be overcome before this vision will be realized; 1) controlling industrial robots for accurate machining; 2) compensation of measurements for thermal expansion; 3) Compensation of measurements for refractive index changes; 4) development of Embedded Metrology Tooling for in-tooling measurement and active tooling compensation; and 5) development of Software for the Planning and Control of Integrated Metrology Networks based on Quality Control with Uncertainty Evaluation and control systems for predictive processes. This paper describes how these challenges are being addressed, in particular the central challenge of developing large volume measurement process models within an integrated dimensional variation management (IDVM) system.