928 research outputs found
Control of fluid flows and other systems governed by partial differential-algebraic equations
The motion of fluids, such as air or water, is central to many engineering systems of significant
economic and environmental importance. Examples range from air/fuel mixing in combustion engines
to turbulence induced noise and fatigue on aircraft. Recent advances in novel sensor/actuator
technologies have raised the intriguing prospect of actively sensing and manipulating the motion
of the fluid within these systems, making them ripe for feedback control, provided a suitable control
model exists. Unfortunately, the models for many of these systems are described by nonlinear,
partial differential-algebraic equations for which few, if any, controller synthesis techniques exist.
In stark contrast, the majority of established control theory assumes plant models of finite (and
typically small) state dimension, expressed as a linear system of ordinary differential equations.
Therefore, this thesis explores the problem of how to apply the mainstream tools of control theory
to the class of systems described by partial differential-algebraic equations, that are either linear,
or for which a linear approximation is valid.
The problems of control system design for infinite-dimensional and algebraically constrained
systems are treated separately in this thesis. With respect to the former, a new method is presented
that enables the computation of a bound on the n-gap between a discretisation of a spatially distributed
plant, and the plant itself, by exploiting the convergence rate of the v-gap metric between
low-order models of successively finer spatial resolution. This bound informs the design, on loworder
models, of H[infinity] loop-shaping controllers that are guaranteed to robustly stabilise the actual
plant. An example is presented on a one-dimensional heat equation.
Controller/estimator synthesis is then discussed for finite-dimensional systems containing algebraic,
as well as differential equations. In the case of fluid flows, algebraic constraints typically
arise from incompressibility and the application of boundary conditions. A numerical algorithm is
presented, suitable for the semi-discrete linearised Navier-Stokes equations, that decouples the differential
and algebraic parts of the system, enabling application of standard control theory without
the need for velocity-vorticity type methods. This algorithm is demonstrated firstly on a simple
electrical circuit, and secondly on the highly non-trivial problem of flow-field estimation in the
transient growth region of a flat-plate boundary layer, using only wall shear measurements.
These separate strands are woven together in the penultimate chapter, where a transient energy
controller is designed for a channel-flow system, using wall mounted sensors and actuators
Modern control approaches for next-generation interferometric gravitational wave detectors
[no abstract
Practical robustness measures in multivariable control system analysis
The robustness of the stability of multivariable linear time invariant feedback control systems with respect to model uncertainty is considered using frequency domain criteria. Available robustness tests are unified under a common framework based on the nature and structure of model errors. These results are derived using a multivariable version of Nyquist's stability theorem in which the minimum singular value of the return difference transfer matrix is shown to be the multivariable generalization of the distance to the critical point on a single input, single output Nyquist diagram. Using the return difference transfer matrix, a very general robustness theorem is presented from which all of the robustness tests dealing with specific model errors may be derived. The robustness tests that explicitly utilized model error structure are able to guarantee feedback system stability in the face of model errors of larger magnitude than those robustness tests that do not. The robustness of linear quadratic Gaussian control systems are analyzed
Robust stability analysis of a dc/dc buck converter under multiple parametric uncertainties
Stability studies are a crucial part of the design of power electronic systems, especially for safety critical ap¬plications. Standard methods can guarantee stability under nominal conditions but do not take into account the multiple uncertainties that are inherent in the physical system or in the system model. These uncertainties, if unaccounted for, may lead to highly optimistic or even erroneous stability margins. The structured singular value-based method justifiably takes into account all possible uncertainties in the system. However, the application of the method to power electronic systems with multiple uncertainties is not widely discussed in the literature. This work presents practical approaches to applying the method in the robust stability analysis of such uncertain systems. Further, it reveals the significant impact of various types of parametric uncertainties on the reliability of stability assessments of power electronic systems. This is achieved by examining the robust stability margin of the dc/dc buck converter system, when it is subject to variations in system load, line resistance, operating temperature and uncertainties in the system model. The predictions are supported by time domain simulation and experimental results
Optimised configuration of sensing elements for control and fault tolerance applied to an electro-magnetic suspension system
New technological advances and the requirements to increasingly abide
by new safety laws in engineering design projects highly affects industrial
products in areas such as automotive, aerospace and railway industries.
The necessity arises to design reduced-cost hi-tech products with minimal
complexity, optimal performance, effective parameter robustness properties,
and high reliability with fault tolerance. In this context the control system
design plays an important role and the impact is crucial relative to the level
of cost efficiency of a product.
Measurement of required information for the operation of the design
control system in any product is a vital issue, and in such cases a number of
sensors can be available to select from in order to achieve the desired system
properties. However, for a complex engineering system a manual procedure
to select the best sensor set subject to the desired system properties can
be very complicated, time consuming or even impossible to achieve. This is
more evident in the case of large number of sensors and the requirement to
comply with optimum performance.
The thesis describes a comprehensive study of sensor selection for control
and fault tolerance with the particular application of an ElectroMagnetic
Levitation system (being an unstable, nonlinear, safety-critical system with
non-trivial control performance requirements). The particular aim of the
presented work is to identify effective sensor selection frameworks subject to
given system properties for controlling (with a level of fault tolerance) the
MagLev suspension system. A particular objective of the work is to identify
the minimum possible sensors that can be used to cover multiple sensor faults,
while maintaining optimum performance with the remaining sensors.
The tools employed combine modern control strategies and multiobjective
constraint optimisation (for tuning purposes) methods. An important part
of the work is the design and construction of a 25kg MagLev suspension
to be used for experimental verification of the proposed sensor selection
frameworks
Advances in PID Control
Since the foundation and up to the current state-of-the-art in control engineering, the problems of PID control steadily attract great attention of numerous researchers and remain inexhaustible source of new ideas for process of control system design and industrial applications. PID control effectiveness is usually caused by the nature of dynamical processes, conditioned that the majority of the industrial dynamical processes are well described by simple dynamic model of the first or second order. The efficacy of PID controllers vastly falls in case of complicated dynamics, nonlinearities, and varying parameters of the plant. This gives a pulse to further researches in the field of PID control. Consequently, the problems of advanced PID control system design methodologies, rules of adaptive PID control, self-tuning procedures, and particularly robustness and transient performance for nonlinear systems, still remain as the areas of the lively interests for many scientists and researchers at the present time. The recent research results presented in this book provide new ideas for improved performance of PID control applications
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