Unified modelling of aerospace systems: a bond graph approach

Systems Integration is widely accepted as the basis for improving the efficiency and performance of many engineering products. The aim is to build a unified optimised system not a collection of subsystems that are combined in some ad hoc manner. This moves traditional design boundaries and, in so doing, enables a structured evolution from an integrated system concept to an integrated system product. It is recognised that the inherent complexity cannot be handled effectively without mathematical modelling. The problem is not so much the large number of components but rather the very large number of functional interfaces that result. The costs involved are high and, if the claims of improved efficiency and performance are to be affordable (or even achievable), predictive modelling and analysis will play a major role in reducing risk. A modelling framework is required which can support integrated system development from concept through to certification. This means building a 'system' inside a computer and demonstrating the feasibility of an entire development cycle. The objective is to provide complete coverage of system functionality so as to gain confidence in the design before becoming locked into a full development programme with associated capital investment and contractual arrangements. With these points in mind the purpose of this thesis is threefold. First, to demonstrate the application of bond graphs as a unified modelling framework for aerospace systems. Second, to review the main principles involved with the modelling of engineering systems and to justify the selection of the bond graph notation as a suitable means of representing the power flow (i.e. the dynamics) of physical systems. Third, to present an exposition of the bond graph method and to evolve it into a versatile notation for integrated systems. The originality of the work is based on the recognition that systems integration is a relatively new field of interest without a mature body of academic literature or reported research. Apparently, there is no open literature on the modelling of complete air vehicles plus their embedded vehicle systems which deals with issues of integrated dynamics and control. To this end, bond graph concepts need to be developed and extended in new direction in order to facilitate an intuitive approach to the modelling of integrated systems

Plant-Wide Diagnosis: Cause-and-Effect Analysis Using Process Connectivity and Directionality Information

Production plants used in modern process industry must produce products that meet stringent environmental, quality and profitability constraints. In such integrated plants, non-linearity and strong process dynamic interactions among process units complicate root-cause diagnosis of plant-wide disturbances because disturbances may propagate to units at some distance away from the primary source of the upset. Similarly, implemented advanced process control strategies, backup and recovery systems, use of recycle streams and heat integration may hamper detection and diagnostic efforts. It is important to track down the root-cause of a plant-wide disturbance because once corrective action is taken at the source, secondary propagated effects can be quickly eliminated with minimum effort and reduced down time with the resultant positive impact on process efficiency, productivity and profitability. In order to diagnose the root-cause of disturbances that manifest plant-wide, it is crucial to incorporate and utilize knowledge about the overall process topology or interrelated physical structure of the plant, such as is contained in Piping and Instrumentation Diagrams (P&IDs). Traditionally, process control engineers have intuitively referred to the physical structure of the plant by visual inspection and manual tracing of fault propagation paths within the process structures, such as the process drawings on printed P&IDs, in order to make logical conclusions based on the results from data-driven analysis. This manual approach, however, is prone to various sources of errors and can quickly become complicated in real processes. The aim of this thesis, therefore, is to establish innovative techniques for the electronic capture and manipulation of process schematic information from large plants such as refineries in order to provide an automated means of diagnosing plant-wide performance problems. This report also describes the design and implementation of a computer application program that integrates: (i) process connectivity and directionality information from intelligent P&IDs (ii) results from data-driven cause-and-effect analysis of process measurements and (iii) process know-how to aid process control engineers and plant operators gain process insight. This work explored process intelligent P&IDs, created with AVEVA® P&ID, a Computer Aided Design (CAD) tool, and exported as an ISO 15926 compliant platform and vendor independent text-based XML description of the plant. The XML output was processed by a software tool developed in Microsoft® .NET environment in this research project to computationally generate connectivity matrix that shows plant items and their connections. The connectivity matrix produced can be exported to Excel® spreadsheet application as a basis for other application and has served as precursor to other research work. The final version of the developed software tool links statistical results of cause-and-effect analysis of process data with the connectivity matrix to simplify and gain insights into the cause and effect analysis using the connectivity information. Process knowhow and understanding is incorporated to generate logical conclusions. The thesis presents a case study in an atmospheric crude heating unit as an illustrative example to drive home key concepts and also describes an industrial case study involving refinery operations. In the industrial case study, in addition to confirming the root-cause candidate, the developed software tool was set the task to determine the physical sequence of fault propagation path within the plant. This was then compared with the hypothesis about disturbance propagation sequence generated by pure data-driven method. The results show a high degree of overlap which helps to validate statistical data-driven technique and easily identify any spurious results from the data-driven multivariable analysis. This significantly increase control engineers confidence in data-driven method being used for root-cause diagnosis. The thesis concludes with a discussion of the approach and presents ideas for further development of the methods

Large scale modeling, model reduction and control design for a real-time mechatronic system

Mechatronics is the synergistic integration of the techniques from mechanical engineering, electrical engineering and information technology, which influences each other mutually. As a multidisciplinary domain, mechatronics is more than mechanical or electronics, and the mechatronic systems are always composed of a number of subsystems with various controllers. From this point of view, a lot of such systems can be defined as large scale system. The key element of such systems is integration. Modeling of mechatronic system is a very important step in developing control design of such products, so as to simulate and analyze their dynamic responses for control design, making sure they would meet the desired requirements. The models of large scale systems are always resulted in complex form and high in dimension, making the computation for modeling, simulation and control design become very complicated, or even beyond the solutions provided by conventional engineering methods. Therefore, a simplified model obtained by using model order reduction technique, which can preserve the dominant physical parameters and reveal the performance limiting factor, is preferred. In this dissertation, the research have chosen the two-wheeled self-balancing scooter as the subject of the study in research on large scale mechatronic system, and efforts have been put on developing a completed mathematical modeling method based on a unified framework from varitional method for both mechanical subsystem and electrical subsystem in the scooter. In order to decrease the computation efforts in simulation and control design, Routh model reduction technique was chosen from various model reduction techniques so as to obtain a low dimensional model. Matlab simulation is used to predict the system response based on the simplified model and related control design. Furthermore, the final design parameters were applied in the physical system of two-wheeled self-balancing scooter to test the real performance so as to finish the design evaluation. Conclusion was made based on these results and further research directions can be predicte