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.

Distributed control of computer communication systems

Flow control in Computer Communication systems is generally a multi-layered structure, consisting of several mechanisms operating independently at different levels. Evaluation of the performance of networks in which different flow control mechanisms act simultaneously is an important area of research, and is examined in depth in this thesis. This thesis presents the modelling of a finite resource computer communication network equipped with three levels of flow control, based on closed queueing network theory. The flow control mechanisms considered are: end-to-end control of virtual circuits, network access control of external messages at the entry nodes and the hop level control between nodes. The model is solved by a heuristic technique, based on an equivalent reduced network and the heuristic extensions to the mean value analysis algorithm. The method has significant computational advantages, and overcomes the limitations of the exact methods. It can be used to solve large network models with finite buffers and many virtual circuits. The model and its heuristic solution are validated by simulation. The interaction between the three levels of flow control are investigated. A queueing model is developed for the admission delay on virtual circuits with end-to-end control, in which messages arrive from independent Poisson sources. The selection of optimum window limit is considered. Several advanced network access schemes are postulated to improve the network performance as well as that of selected traffic streams, and numerical results are presented. A model for the dynamic control of input traffic is developed. Based on Markov decision theory, an optimal control policy is formulated. Numerical results are given and throughput-delay performance is shown to be better with dynamic control than with static control.

Resonant cavity Fibre Bragg grating sensor interrogation

This thesis presents a novel high-performance approach to time-division-multiplexing (TDM) fibre Bragg grating (FBG) optical sensors, known as the resonant cavity architecture. A background theory of FBG optical sensing includes several techniques for multiplexing sensors. The limitations of current wavelength-division-multiplexing (WDM) schemes are contrasted against the technological and commercial advantage of TDM. The author’s hypothesis that ‘it should be possible to achieve TDM FBG sensor interrogation using an electrically switched semiconductor optical amplifier (SOA)’ is then explained. Research and development of a commercially viable optical sensor interrogator based on the resonant cavity architecture forms the remainder of this thesis. A fully programmable SOA drive system allows interrogation of sensor arrays 10km long with a spatial resolution of 8cm and a variable gain system provides dynamic compensation for fluctuating system losses. Ratiometric filter- and diffractive-element spectrometer-based wavelength measurement systems are developed and analysed for different commercial applications. The ratiometric design provides a low-cost solution that has picometre resolution and low noise using 4% reflective sensors, but is less tolerant to variation in system loss. The spectrometer design is more expensive, but delivers exceptional performance with picometre resolution, low noise and tolerance to 13dB system loss variation. Finally, this thesis details the interrogator’s peripheral components, its compliance for operation in harsh industrial environments and several examples of commercial applications where it has been deployed. Applications include laboratory instruments, temperature monitoring systems for oil production, dynamic control for wind-energy and battery powered, self-contained sub-sea strain monitoring.

A methodology for analysis and control of discrete event dynamic systems

The rapid developments in computer technology have resulted in a widespread use of discrete event dynamic systems (DEDSs). This type of system is complex because it exhibits properties such as concurrency, conflict and non-determinism. It is therefore important to model and analyse such systems before implementation to ensure safe, deadlock free and optimal operation. This thesis investigates current modelling techniques and describes Petri net theory in more detail. It reviews top down, bottom up and hybrid Petri net synthesis techniques that are used to model large systems and introduces on object oriented methodology to enable modelling of larger and more complex systems. Designs obtained by this methodology are modular, easy to understand and allow re-use of designs. Control is the next logical step in the design process. This thesis reviews recent developments in control DEDSs and investigates the use of Petri nets in the design of supervisory controllers. The scheduling of exclusive use of resources is investigated and an efficient Petri net based scheduling algorithm is designed and a re-configurable controller is proposed. To enable the analysis and control of large and complex DEDSs, an object oriented C++ software tool kit was developed and used to implement a Petri net analysis tool, Petri net scheduling and control algorithms. Finally, the methodology was applied to two industrial DEDSs: a prototype can sorting machine developed by Eurotherm Controls Ltd., and a semiconductor testing plant belonging to SGS Thomson Microelectronics Ltd.

Establishing a framework for dynamic risk management in 'intelligent' aero-engine control

The behaviour of control functions in safety critical software systems is typically bounded to prevent the occurrence of known system level hazards. These bounds are typically derived through safety analyses and can be implemented through the use of necessary design features. However, the unpredictability of real world problems can result in changes in the operating context that may invalidate the behavioural bounds themselves, for example, unexpected hazardous operating contexts as a result of failures or degradation. For highly complex problems it may be infeasible to determine the precise desired behavioural bounds of a function that addresses or minimises risk for hazardous operation cases prior to deployment. This paper presents an overview of the safety challenges associated with such a problem and how such problems might be addressed. A self-management framework is proposed that performs on-line risk management. The features of the framework are shown in context of employing intelligent adaptive controllers operating within complex and highly dynamic problem domains such as Gas-Turbine Aero Engine control. Safety assurance arguments enabled by the framework necessary for certification are also outlined.

Conditional distribution modeling for estimating and exploiting uncertainty in control systems

This paper presents a general methodology for estimating and incorporating uncertainty in the controller and forward models for noisy nonlinear control problems. Conditional distribution modeling in a neural network context is used to estimate uncertainty around the prediction of neural network outputs. The developed methodology circumvents the dynamic programming problem by using the predicted neural network uncertainty to localize the possible control solutions to consider. A nonlinear multivariable 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.

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.

Computer control of chemical process plants with special reference to distillation

A sieve plate distillation column has been constructed and interfaced to a minicomputer with the necessary instrumentation for dynamic, estimation and control studies with special bearing on low-cost and noise-free instrumentation. A dynamic simulation of the column with a binary liquid system has been compiled using deterministic models that include fluid dynamics via Brambilla's equation for tray liquid holdup calculations. The simulation predictions have been tested experimentally under steady-state and transient conditions. The simulator's predictions of the tray temperatures have shown reasonably close agreement with the measured values under steady-state conditions and in the face of a step change in the feed rate. A method of extending linear filtering theory to highly nonlinear systems with very nonlinear measurement functional relationships has been proposed and tested by simulation on binary distillation. The simulation results have proved that the proposed methodology can overcome the typical instability problems associated with the Kalman filters. Three extended Kalman filters have been formulated and tested by simulation. The filters have been used to refine a much simplified model sequentially and to estimate parameters such as the unmeasured feed composition using information from the column simulation. It is first assumed that corrupted tray composition measurements are made available to the filter and then corrupted tray temperature measurements are accessed instead. The simulation results have demonstrated the powerful capability of the Kalman filters to overcome the typical hardware problems associated with the operation of on-line analyzers in relation to distillation dynamics and control by, in effect, replacirig them. A method of implementing estimator-aided feedforward (EAFF) control schemes has been proposed and tested by simulation on binary distillation. The results have shown that the EAFF scheme provides much better control and energy conservation than the conventional feedback temperature control in the face of a sustained step change in the feed rate or multiple changes in the feed rate, composition and temperature. Further extensions of this work are recommended as regards simulation, estimation and EAFF control.

Dynamic measurement of accommodative responses while viewing stereoscopic images

Using video refraction accommodative and convergence dynamic responses were measured to stepped changes in convergence stimuli with unchanged accommodative stimuli (conflicting stereoscopic image) and compared with responses to non-conflicting target stimuli. Three targets were used that varied in their spatial frequency components. An accommodative transient overshoot was evident in four out of seven subjects for only conflicting stimuli. One showed accommodative and convergence oscillation probably due to difficulty in fusing the stereoscopic target when it had a higher spatial component, however, this oscillation diminished when the target was spatial low-pass filtered. We hypothesise that transient responses to step stimuli is initiated by convergence-driven accommodation and subsequently followed by slower fine-control of accommodation modulated by the amount of blur. Inter-subject differences in convergence-driven accommodation may also be a factor to consider. For stereoscopic stimuli, it is proposed that the increase in blur immediately after the onset of the accommodative response inhibits cessation of the response.

Managing the dynamic configuration of enterprises

Due to environmental changes and business trends such as globalisation, outsourcing and virtualisation, more and more companies get involved in business activities that are outside their direct control. This typically occurs by entering into collaborative relationships and joint ventures with specialised companies in order to fulfil the demands of customers quickly (DiMaggio, 2001). Organisational structures that results from such collaborative relationships and joint ventures are referred to in this paper as enterprises and the management of them known as enterprise management. The authors use the definition of the European Commission (2003) that defines an enterprise as “… an entity, regardless of its legal form … including partnerships or associations regularly engaged in economic activities.” Therefore in its most simple form an enterprise could be a single integrated company. However, findings from this research show that enterprises can also be made up of parts of different companies and the structure of the enterprise is contingent upon a variety of different factors. The success of the enterprise as a collaborative venture depends on the ability of companies to intermediate their internal core competencies into other participating companies’ value streams and simultaneously outsource their own peripheral activities to companies that can perform them quicker, cheaper, and more effectively (Lal et al., 1995). In other words, the peripheral activities of one member-company must be complemented by a core competence of another member-company within an overall enterprise.

Motion sharpening and contrast:Gain control precedes compressive non-linearity?

Blurred edges appear sharper in motion than when they are stationary. We (Vision Research 38 (1998) 2108) have previously shown how such distortions in perceived edge blur may be accounted for by a model which assumes that luminance contrast is encoded by a local contrast transducer whose response becomes progressively more compressive as speed increases. If the form of the transducer is fixed (independent of contrast) for a given speed, then a strong prediction of the model is that motion sharpening should increase with increasing contrast. We measured the sharpening of periodic patterns over a large range of contrasts, blur widths and speeds. The results indicate that whilst sharpening increases with speed it is practically invariant with contrast. The contrast invariance of motion sharpening is not explained by an early, static compressive non-linearity alone. However, several alternative explanations are also inconsistent with these results. We show that if a dynamic contrast gain control precedes the static non-linear transducer then motion sharpening, its speed dependence, and its invariance with contrast, can be predicted with reasonable accuracy. © 2003 Elsevier Science Ltd. All rights reserved.

A model for motion sharpening: contrast gain control precedes compressive nonlinearity

Blurred edges appear sharper in motion than when they are stationary. We have previously shown how such distortions in perceived edge blur may be explained by a model which assumes that luminance contrast is encoded by a local contrast transducer whose response becomes progressively more compressive as speed increases. To test this model further, we measured the sharpening of drifting, periodic patterns over a large range of contrasts, blur widths, and speeds Human Vision. The results indicate that, while sharpening increased with speed, it was practically invariant with contrast. This contrast invariance cannot be explained by a fixed compressive nonlinearity since that predicts almost no sharpening at low contrasts.We show by computational modelling of spatiotemporal responses that, if a dynamic contrast gain control precedes the static nonlinear transducer, then motion sharpening, its speed dependence, and its invariance with contrast can be predicted with reasonable accuracy.

Effect of β-adrenoceptor antagonists on autonomic control of ciliary smooth muscle

Purpose: Pharmacological intervention with peripheral sympathetic transmission at ciliary smooth muscle neuro-receptor junctions has been used against a background of controlled parasympathetic activity to investigate the characteristics of autonomic control of ocular accommodation. Methods: A continuously recording infrared optometer was used to measure accommodation on a group of five visually normal emmetropic subjects under open- and closed-loop conditions. A double-blind protocol between saline, timolol and betaxolol was used to differentiate between the localised action on ciliary smooth muscle and effects induced by changes in stimulus conditions. Data were collected before and 45 min following the instillation of saline, timolol or betaxolol. Open-loop post-task decay was investigated following 3 min sustained near fixation of a stimulus placed 3 D above the subject's pre-task tonic accommodation level. Closed-loop dynamic responses were recorded for each treatment condition while subjects viewed sinusoidally (0.05-0.6 Hz) or stepwise vergence-modulated targets over a 2 D range (2-4 D). Results: Open-loop data demonstrate a rapid post-task regression to pre-task tonic accommodation levels for saline and betaxolol control conditions. A slow positive post-task shift was induced by timolol indicating that sympathetic inhibition contributes to accommodative adaptation during sustained near vision. Closed-loop accommodation responses to temporally modulated sinusoidal stimuli showed characteristic features for both saline and betaxolol control conditions. Timolol induced a reduced gain for low- and mid-temporal frequencies (< 0.3 Hz) but did not affect the response at higher temporal frequencies. Response times to stepwise stimuli increased following the instillation of timolol for the near-to-far fixation condition compared with the controls and was related to the period of sustained prior fixation. Conclusions: Modulation of accommodation under open- and closed-loop conditions by a non-selective β-blocker is consistent with the temporal and inhibitory features of sympathetic innervation to ciliary smooth muscle. Although parasympathetic innervation predominates there is evidence to support a role for sympathetic innervation in the control of ocular accommodation. © 2002 The College of Optometrists.

S100A4 downregulates filopodia formation through increased dynamic instability

Cell migration requires the initial formation of cell protrusions, lamellipodia and/or filopodia, the attachment of the leading lamella to extracellular cues and the formation and efficient recycling of focal contacts at the leading edge. The small calcium binding EF-hand protein S100A4 has been shown to promote cell motility but the direct molecular mechanisms responsible remain to be elucidated. In this work, we provide new evidences indicating that elevated levels of S100A4 affect the stability of filopodia and prevent the maturation of focal complexes. Increasing the levels of S100A4 in a rat mammary benign tumor derived cell line results in acquired cellular migration on the wound healing scratch assay. At the cellular levels, we found that high levels of S100A4 induce the formation of many nascent filopodia, but that only a very small and limited number of those can stably adhere and mature, as opposed to control cells, which generate fewer protrusions but are able to maintain these into more mature projections. This observation was paralleled by the fact that S100A4 overexpressing cells were unable to establish stable focal adhesions. Using different truncated forms of the S100A4 proteins that are unable to bind to myosin IIA, our data suggests that this newly identified functions of S100A4 is myosin-dependent, providing new understanding on the regulatory functions of S100A4 on cellular migration.

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.