Methods of system identification, parameter estimation and optimisation applied to problems of modelling and control in engineering and physiology

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@PhdThesis{2009murraysmithdsc,
  author =       "David James Murray-Smith",
  title =        "Methods of system identification, parameter estimation
                 and optimisation applied to problems of modelling and
                 control in engineering and physiology",
  school =       "University of Glasgow",
  year =         "2009",
  type =         "Doctor of Science in Engineering",
  address =      "UK",
  month =        may,
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://theses.gla.ac.uk/1170/",
  URL =          "http://theses.gla.ac.uk/1170/1/2009murraysmithdsc.pdf",
  URL =          "http://encore.lib.gla.ac.uk/iii/encore/record/C__Rb2694600",
  size =         "143 679(?) pages",
  abstract =     "Mathematical and computer-based models provide the
                 foundation of most methods of engineering design. They
                 are recognised as being especially important in the
                 development of integrated dynamic systems, such as
                 control-configured aircraft or in complex robotics
                 applications. These models usually involve combinations
                 of linear or nonlinear ordinary differential equations
                 or difference equations, partial differential equations
                 and algebraic equations. In some cases models may be
                 based on differential algebraic equations. Dynamic
                 models are also important in many other fields of
                 research, including physiology where the highly
                 integrated nature of biological control systems is
                 starting to be more fully understood. Although many
                 models may be developed using physical, chemical, or
                 biological principles in the initial stages, the use of
                 experimentation is important for checking the
                 significance of underlying assumptions or
                 simplifications and also for estimating appropriate
                 sets of parameters. This experimental approach to
                 modelling is also of central importance in establishing
                 the suitability, or otherwise, of a given model for an
                 intended application, the so-called model validation
                 problem. System identification, which is the broad term
                 used to describe the processes of experimental
                 modelling, is generally considered to be a mature field
                 and classical methods of identification involve linear
                 discrete-time models within a stochastic framework. The
                 aspects of the research described in this thesis that
                 relate to applications of identification, parameter
                 estimation and optimisation techniques for model
                 development and model validation mainly involve
                 nonlinear continuous time models Experimentally-based
                 models of this kind have been used very successfully in
                 the course of the research described in this thesis
                 very in two areas of physiological research and in a
                 number of different engineering applications. In terms
                 of optimisation problems, the design, experimental
                 tuning and performance evaluation of nonlinear control
                 systems has much in common with the use of optimisation
                 techniques within the model development process and it
                 is therefore helpful to consider these two areas
                 together.",
  abstract =     "The work described in the thesis is strongly
                 applications oriented. Many similarities have been
                 found in applying modelling and control techniques to
                 problems arising in fields that appear very different.
                 For example, the areas of neurophysiology, respiratory
                 gas exchange processes, electro-optic sensor systems,
                 helicopter flight-control, hydro-electric power
                 generation and surface ship or underwater vehicles
                 appear to have little in common. However, closer
                 examination shows that they have many similarities in
                 terms of the types of problem that are presented, both
                 in modelling and in system design. In addition to
                 nonlinear behaviour; most models of these systems
                 involve significant uncertainties or require important
                 simplifications if the model is to be used in a
                 real-time application such as automatic control. One
                 recurring theme, that is important both in the
                 modelling work described and for control applications,
                 is the additional insight that can be gained through
                 the dual use of time-domain and frequency-domain
                 information. One example of this is the importance of
                 coherence information in establishing the existence of
                 linear or nonlinear relationships between variables and
                 this has proved to be valuable in the experimental
                 investigation of neuromuscular systems and in the
                 identification of helicopter models from flight test
                 data. Frequency-domain techniques have also proved
                 useful for the reduction of high-order multi-input
                 multi-output models. Another important theme that has
                 appeared both within the modelling applications and in
                 research on nonlinear control system design methods,
                 relates to the problems of optimisation in cases where
                 the associated response surface has many local optima.
                 Finding the global optimum in practical applications
                 presents major difficulties and much emphasis has been
                 placed on evolutionary methods of optimisation (both
                 genetic algorithms and genetic programming) in
                 providing usable methods for optimisation in design and
                 in complex nonlinear modelling applications that do not
                 involve real-time problems.",
  abstract =     "Another topic, considered both in the context of
                 system modelling and control, is parameter sensitivity
                 analysis and it has been found that insight gained from
                 sensitivity information can be of value not only in the
                 development of system models (e.g. through
                 investigation of model robustness and the design of
                 appropriate test inputs), but also in feedback system
                 design and in controller tuning. A technique has been
                 developed based on sensitivity analysis for the
                 semi-automatic tuning of cascade and feedback
                 controllers for multi-input multi-output feedback
                 control systems. This tuning technique has been applied
                 successfully to several problems. Inverse systems also
                 receive significant attention in the thesis. These
                 systems have provided a basis for theoretical research
                 in the control systems field over the past two decades
                 and some significant applications have been reported,
                 despite the inherent difficulties in the mathematical
                 methods needed for the nonlinear case. Inverse
                 simulation methods, developed initially by others for
                 use in handling-qualities studies for fixed-wing
                 aircraft and helicopters, are shown in the thesis to
                 provide some important potential benefits in control
                 applications compared with classical methods of
                 inversion. New developments in terms of methodology are
                 presented in terms of a novel sensitivity based
                 approach to inverse simulation that has advantages in
                 terms of numerical accuracy and a new search-based
                 optimisation technique based on the Nelder-Mead
                 algorithm that can handle inverse simulation problems
                 involving hard nonlinearities. Engineering applications
                 of inverse simulation are presented, some of which
                 involve helicopter flight control applications while
                 others are concerned with feed-forward controllers for
                 ship steering systems. The methods of search-based
                 optimisation show some important advantages over
                 conventional gradient-based methods, especially in
                 cases where saturation and other nonlinearities are
                 significant. The final discussion section takes the
                 form of a critical evaluation of results obtained using
                 the chosen methods of system identification, parameter
                 estimation and optimisation for the modelling and
                 control applications considered. Areas of success are
                 highlighted and situations are identified where
                 currently available techniques have important
                 limitations. The benefits of an inter-disciplinary and
                 applications-oriented approach to problems of modelling
                 and control are also discussed and the value in terms
                 of cross-fertilisation of ideas resulting from
                 involvement in a wide range of applications is
                 emphasised. Areas for further research are discussed.",
  notes =        "page x 'Note that all Submitted Papers have been
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