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.

Probability distribution modelling to improve stability in nonlinear MIMO control

We consider the direct adaptive inverse control of nonlinear multivariable systems with different delays between every input-output pair. In direct adaptive inverse control, the inverse mapping is learned from examples of input-output pairs. This makes the obtained controller sub optimal, since the network may have to learn the response of the plant over a larger operational range than necessary. Moreover, in certain applications, the control problem can be redundant, implying that the inverse problem is ill posed. In this paper we propose a new algorithm which allows estimating and exploiting uncertainty in nonlinear multivariable control systems. This approach allows us to model strongly non-Gaussian distribution of control signals as well as processes with hysteresis. The proposed algorithm circumvents the dynamic programming problem by using the predicted neural network uncertainty to localise the possible control solutions to consider.

Responsive systems:an introduction

This paper introduces responsive systems: systems that are real-time, event-based, or time-dependent. There are a number of trends that are accelerating the adoption of responsive systems: timeliness requirements for business information systems are becoming more prevalent, embedded systems are increasingly integrated into soft real-time command-and-control systems, improved message-oriented middleware is facilitating growth in event-processing applications, and advances in service-oriented and component-based techniques are lowering the costs of developing and deploying responsive applications. The use of responsive systems is illustrated here in two application areas: the defense industry and online gaming. The papers in this special issue of the IBM Systems Journal are then introduced. The paper concludes with a discussion of the key remaining challenges in this area and ideas for further work.

Pragmatic approach to the development of robust real-time protocols

This research is concerned with the development of distributed real-time systems, in which software is used for the control of concurrent physical processes. These distributed control systems are required to periodically coordinate the operation of several autonomous physical processes, with the property of an atomic action. The implementation of this coordination must be fault-tolerant if the integrity of the system is to be maintained in the presence of processor or communication failures. Commit protocols have been widely used to provide this type of atomicity and ensure consistency in distributed computer systems. The objective of this research is the development of a class of robust commit protocols, applicable to the coordination of distributed real-time control systems. Extended forms of the standard two phase commit protocol, that provides fault-tolerant and real-time behaviour, were developed. Petri nets are used for the design of the distributed controllers, and to embed the commit protocol models within these controller designs. This composition of controller and protocol model allows the analysis of the complete system in a unified manner. A common problem for Petri net based techniques is that of state space explosion, a modular approach to both the design and analysis would help cope with this problem. Although extensions to Petri nets that allow module construction exist, generally the modularisation is restricted to the specification, and analysis must be performed on the (flat) detailed net. The Petri net designs for the type of distributed systems considered in this research are both large and complex. The top down, bottom up and hybrid synthesis techniques that are used to model large systems in Petri nets are considered. A hybrid approach to Petri net design for a restricted class of communicating processes is developed. Designs produced using this hybrid approach are modular and allow re-use of verified modules. In order to use this form of modular analysis, it is necessary to project an equivalent but reduced behaviour on the modules used. These projections conceal events local to modules that are not essential for the purpose of analysis. To generate the external behaviour, each firing sequence of the subnet is replaced by an atomic transition internal to the module, and the firing of these transitions transforms the input and output markings of the module. Thus local events are concealed through the projection of the external behaviour of modules. This hybrid design approach preserves properties of interest, such as boundedness and liveness, while the systematic concealment of local events allows the management of state space. The approach presented in this research is particularly suited to distributed systems, as the underlying communication model is used as the basis for the interconnection of modules in the design procedure. This hybrid approach is applied to Petri net based design and analysis of distributed controllers for two industrial applications that incorporate the robust, real-time commit protocols developed. Temporal Petri nets, which combine Petri nets and temporal logic, are used to capture and verify causal and temporal aspects of the designs in a unified manner.

The design of robust protocols for distributed real-time systems

Modern distributed control systems comprise of a set of processors which are interconnected using a suitable communication network. For use in real-time control environments, such systems must be deterministic and generate specified responses within critical timing constraints. Also, they should be sufficiently robust to survive predictable events such as communication or processor faults. This thesis considers the problem of coordinating and synchronizing a distributed real-time control system under normal and abnormal conditions. Distributed control systems need to periodically coordinate the actions of several autonomous sites. Often the type of coordination required is the all or nothing property of an atomic action. Atomic commit protocols have been used to achieve this atomicity in distributed database systems which are not subject to deadlines. This thesis addresses the problem of applying time constraints to atomic commit protocols so that decisions can be made within a deadline. A modified protocol is proposed which is suitable for real-time applications. The thesis also addresses the problem of ensuring that atomicity is provided even if processor or communication failures occur. Previous work has considered the design of atomic commit protocols for use in non time critical distributed database systems. However, in a distributed real-time control system a fault must not allow stringent timing constraints to be violated. This thesis proposes commit protocols using synchronous communications which can be made resilient to a single processor or communication failure and still satisfy deadlines. Previous formal models used to design commit protocols have had adequate state coverability but have omitted timing properties. They also assumed that sites communicated asynchronously and omitted the communications from the model. Timed Petri nets are used in this thesis to specify and design the proposed protocols which are analysed for consistency and timeliness. Also the communication system is mcxielled within the Petri net specifications so that communication failures can be included in the analysis. Analysis of the Timed Petri net and the associated reachability tree is used to show the proposed protocols always terminate consistently and satisfy timing constraints. Finally the applications of this work are described. Two different types of applications are considered, real-time databases and real-time control systems. It is shown that it may be advantageous to use synchronous communications in distributed database systems, especially if predictable response times are required. Emphasis is given to the application of the developed commit protocols to real-time control systems. Using the same analysis techniques as those used for the design of the protocols it can be shown that the overall system performs as expected both functionally and temporally.

The development of hard real-time systems using a formal approach

Hard real-time systems are a class of computer control systems that must react to demands of their environment by providing `correct' and timely responses. Since these systems are increasingly being used in systems with safety implications, it is crucial that they are designed and developed to operate in a correct manner. This thesis is concerned with developing formal techniques that allow the specification, verification and design of hard real-time systems. Formal techniques for hard real-time systems must be capable of capturing the system's functional and performance requirements, and previous work has proposed a number of techniques which range from the mathematically intensive to those with some mathematical content. This thesis develops formal techniques that contain both an informal and a formal component because it is considered that the informality provides ease of understanding and the formality allows precise specification and verification. Specifically, the combination of Petri nets and temporal logic is considered for the specification and verification of hard real-time systems. Approaches that combine Petri nets and temporal logic by allowing a consistent translation between each formalism are examined. Previously, such techniques have been applied to the formal analysis of concurrent systems. This thesis adapts these techniques for use in the modelling, design and formal analysis of hard real-time systems. The techniques are applied to the problem of specifying a controller for a high-speed manufacturing system. It is shown that they can be used to prove liveness and safety properties, including qualitative aspects of system performance. The problem of verifying quantitative real-time properties is addressed by developing a further technique which combines the formalisms of timed Petri nets and real-time temporal logic. A unifying feature of these techniques is the common temporal description of the Petri net. A common problem with Petri net based techniques is the complexity problems associated with generating the reachability graph. This thesis addresses this problem by using concurrency sets to generate a partial reachability graph pertaining to a particular state. These sets also allows each state to be checked for the presence of inconsistencies and hazards. The problem of designing a controller for the high-speed manufacturing system is also considered. The approach adopted mvolves the use of a model-based controller: This type of controller uses the Petri net models developed, thus preservIng the properties already proven of the controller. It. also contains a model of the physical system which is synchronised to the real application to provide timely responses. The various way of forming the synchronization between these processes is considered and the resulting nets are analysed using concurrency sets.

Aspects of design for a spare parts provisioning system

This thesis describes an investigation by the author into the spares operation of compare BroomWade Ltd. Whilst the complete system, including the warehousing and distribution functions, was investigated, the thesis concentrates on the provisioning aspect of the spares supply problem. Analysis of the historical data showed the presence of significant fluctuations in all the measures of system performance. Two Industrial Dynamics simulation models were developed to study this phenomena. The models showed that any fluctuation in end customer demand would be amplified as it passed through the distributor and warehouse stock control systems. The evidence from the historical data available supported this view of the system's operation. The models were utilised to determine which parts of the total system could be expected to exert a critical influence on its performance. The lead time parameters of the supply sector were found to be critical and further study showed that the manner in which the lead time changed with work in progress levels was also an important factor. The problem therefore resolved into the design of a spares manufacturing system. Which exhibited the appropriate dynamic performance characteristics. The gross level of entity presentation, inherent in the Industrial Dynamics methodology, was found to limit the value of these models in the development of detail design proposals. Accordingly, an interacting job shop simulation package was developed to allow detailed evaluation of organisational factors on the performance characteristics of a manufacturing system. The package was used to develop a design for a pilot spares production unit. The need for a manufacturing system to perform successfully under conditions of fluctuating demand is not limited to the spares field. Thus, although the spares exercise provides an example of the approach, the concepts and techniques developed can be considered to have broad application throughout batch manufacturing industry.

Automation, rationalisation and concentration : a case study in the British chemical industry

This thesis is based upon a case study of the adoption of digital, electronic, microprocessor-based control systems by Albright & Wilson Limited - a UK chemical producer. It offers an explanation of the company's changing technology policy between 1978 and 1981, by examining its past development, internal features and industrial environment. Part One of the thesis gives an industry-level analysis which relates the development of process control technology to changes in the economic requirements of production . The rapid diffusion of microcomputers and other microelectronic equipment in the chemical industry is found to be a response to general need to raise the efficiency of all processes, imposed by the economic recession following 1973. Part Two examines the impaot of these technical and eoonomic ohanges upon Albright & Wilson Limited. The company's slowness in adopting new control technology is explained by its long history in which trends are identified whlich produced theconservatism of the 1970s. By contrast, a study of Tenneco Incorporated, a much more successful adoptor of automating technology, is offered with an analysis of the new technology policy of adoption of such equipment which it imposed upon Albright & Wilson, following the latter's takeover by Tenneco in 1978. Some indications of the consequences by this new policy of widespread adoptions of microprocessor-based control equipment are derived from a study of the first Albright & Wilson plant to use such equipment. The thesis concludes that companies which fail to adopt rapidly the new control technology may not survive in the recessionary environment, the long- established British companies may lack the flexibility to make such necessary changes and that multi-national companies may have an important role jn the planned transfer and adoption of new production technology through their subsidiaries in the UK.

A contingency theory perspective on the risk management control system within Birmingham City Council

In recent years the topic of risk management has moved up the agenda of both government and industry, and private sector initiatives to improve risk and internal control systems have been mirrored by similar promptings for change in the public sector. Both regulators and practitioners now view risk management as an integral part of the process of corporate governance, and an aid to the achievement of strategic objectives. The paper uses case study material on the risk management control system at Birmingham City Council to extend existing theory by developing a contingency theory for the public sector. The case demonstrates that whilst the structure of the control system fits a generic model, the operational details indicate that controls are contingent upon three core variables—central government policies, information and communication technology and organisational size. All three contingent variables are suitable for testing the theory across the broader public sector arena.

A mixture density network approach to modelling and exploiting uncertainty in nonlinear control problems

In nonlinear and stochastic control problems, learning an efficient feed-forward controller is not amenable to conventional neurocontrol methods. For these approaches, estimating and then incorporating uncertainty in the controller and feed-forward models can produce more robust control results. Here, we introduce a novel inversion-based neurocontroller for solving control problems involving uncertain nonlinear systems which 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. Based on importance sampling from these distributions a novel robust inverse control approach is obtained. This importance sampling provides a structured and principled approach to constrain the complexity of the search space for the ideal control law. The developed methodology circumvents the dynamic programming problem by using the predicted neural network uncertainty to localise the possible control solutions to consider. A nonlinear multi-variable system with different delays between the input-output pairs is used to demonstrate the successful application of the developed control algorithm. The proposed method is suitable for redundant control systems and allows us to model strongly non-Gaussian distributions of control signal as well as processes with hysteresis. © 2004 Elsevier Ltd. All rights reserved.

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.

Experimental comparison of dynamic tracking performance of iGPS and laser tracker

External metrology systems are increasingly being integrated with traditional industrial articulated robots, especially in the aerospace industries, to improve their absolute accuracy for precision operations such as drilling, machining and jigless assembly. While currently most of the metrology assisted robotics control systems are limited in their position update rate, such that the robot has to be stopped in order to receive a metrology coordinate update, some recent efforts are addressed toward controlling robots using real-time metrology data. The indoor GPS is one of the metrology systems that may be used to provide real-time 6DOF data to a robot controller. Even if there is a noteworthy literature dealing with the evaluation of iGPS performance, there is, however, a lack of literature on how well the iGPS performs under dynamic conditions. This paper presents an experimental evaluation of the dynamic measurement performance of the iGPS, tracking the trajectories of an industrial robot. The same experiment is also repeated using a laser tracker. Besides the experiment results presented, this paper also proposes a novel method for dynamic repeatability comparisons of tracking instruments. © 2011 Springer-Verlag London Limited.