An application of the individual channel analysis and design approach to control of a two-input two-output coupled-tanks system

Frequency-domain methods have provided an established approach to the analysis and design of single-loop feedback control systems in many application areas for many years. Individual Channel Analysis and Design (ICAD) is a more recent development that allows neo-classical frequency-domain analysis and design methods to be applied to multi-input multi-output control problems. This paper provides a case study illustrating the use of the ICAD methodology for an application involving liquid-level control for a system based on two coupled tanks. The complete nonlinear dynamic model of the plant is presented for a case involving two input flows of liquid and two output variables, which are the depths of liquid in the two tanks. Linear continuous proportional plus integral controllers are designed on the basis of linearised plant models to meet a given set of performance specifications for this two-input two-output multivariable control system and a computer simulation of the nonlinear model and the controllers is then used to demonstrate that the overall closed-loop performance meets the given requirements. The resulting system has been implemented in hardware and the paper includes experimental results which demonstrate good agreement with simulation predictions. The performance is satisfactory in terms of steady-state behaviour, transient responses, interaction between the controlled variables, disturbance rejection and robustness to changes within the plant. Further simulation results, some of which involve investigations that could not be carried out in a readily repeatable fashion by experimental testing, give support to the conclusion that this neo-classical ICAD framework can provide additional insight within the analysis and design processes for multi-input multi-output feedback control systems

A mathematical model of the human respiratory system during exercise

This paper describes a respiratory control system model and the associated computer simulations for human subjects during incremental exercise, involving work rates from zero up to the highest level in the heavy exercise domain. Modelling the respiratory control system for conditions above lactate threshold has rarely been attempted because many subsystems begin to lose proportionality in their responses. Our model is built on the basis of putative mechanisms and is based on information identified from a large body of published work. Simulation results are presented and validated using experimental results from published sources. The model confirms that the human body employs an open-loop control strategy for ventilation during exercise, which contrasts with the negative feedback control mode employed for the rest condition. It is suggested that control of ventilation simultaneously involves at least two variables, one being proportional to the pulmonary CO2 output and another being proportional to blood acidity

Optimisation of the weighting functions of an H_∞ controller using genetic algorithms and structured genetic algorithms

In this paper the optimisation of the weighting functions for an H<sub>∞</sub> controller using genetic algorithms and structured genetic algorithms is considered. The choice of the weighting functions is one of the key steps in the design of an H<sub>∞</sub> controller. The performance of the controller depends on these weighting functions since poorly chosen weighting functions will provide a poor controller. One approach that can solve this problem is the use of evolutionary techniques to tune the weighting parameters. The paper presents the improved performance of structured genetic algorithms over conventional genetic algorithms and how this technique can assist with the identification of appropriate weighting functions' orders

Development of an inverse simulation method for the analysis of train performance

Conventional methods of computer-based simulation allow prediction of output variables, often as a function of time, for a given model of a physical system for a given set of initial conditions and input variables. In the case of train performance simulation models, the possible output variables include train speed or distance travelled, both expressed as functions of time. The corresponding input variables, also expressed as functions of time, are the tractive force or power levels for given train characteristics and route information such as gradients, track curvature and speed restrictions. Inverse simulation methods, on the other hand, allow selected model variables (such as the tractive force at any time instant) to be found from other specified model variables applied as input (such as the train speed or distance travelled versus time) for a given set of route conditions and train characteristics. The specific inverse simulation method presented in the paper is based on feedback principles. Illustrative results are used to verify this inverse simulation approach for train performance applications, and further cases are used to show that the inverse formulation provides an insight that is different from that obtained using more conventional forward simulation techniques

Genetic programming for the automatic design of controllers for a surface ship

In this paper, the implementation of genetic programming (GP) to design a contoller structure is assessed. GP is used to evolve control strategies that, given the current and desired state of the propulsion and heading dynamics of a supply ship as inputs, generate the command forces required to maneuver the ship. The controllers created using GP are evaluated through computer simulations and real maneuverability tests in a laboratory water basin facility. The robustness of each controller is analyzed through the simulation of environmental disturbances. In addition, GP runs in the presence of disturbances are carried out so that the different controllers obtained can be compared. The particular vessel used in this paper is a scale model of a supply ship called CyberShip II. The results obtained illustrate the benefits of using GP for the automatic design of propulsion and navigation controllers for surface ships

In situ trap properties in CCDs: the donor level of the silicon divacancy

The silicon divacancy is one of the main defects of concern in radiation damage studies of Charge-Coupled Devices (CCDs) and, being immobile at room temperature, the defect is accessible to a variety of characterisation techniques. As such, there is a large amount of (often conflicting) information in the literature regarding this defect. Here we study the donor level of the divacancy, one of three energy levels which lie between the silicon valence and conduction bands. The donor level of the divacancy acts as a trap for holes in silicon and therefore can be studied through the use of a p-channel CCD. The method of trap-pumping, linked closely to the process of pocket-pumping, has been demonstrated in the literature over the last two years to allow for in-situ analysis of defects in the silicon of CCDs. However, most work so far has been a demonstartion [sic] of the techinique [sic]. We begin here to use the technique for detailed studies of a specific defect centre in silicon, the donor level of the divacancy. The trap density post-irradiation can be found, and each instance of the trap identified independently of all others. Through the study of the trap response at different clocking frequencies one can measure directly the defect emission time constant, and through tracking this at different temperatures, it is possible to use Shockley-Read-Hall theory to calculate the trap energy level and cross-section. A large population of traps, all with parameters consistent with the donor level of the divacancy, has been studied, leading to a measure of the distribution of properties. The emission time constant, energy level and cross-section are found to have relatively large spreads, significantly beyond the small uncertainty in the measurement technique. This spread has major implications on the correction of charge transfer inefficiency effects in space applications in which high precision is required

Divide and conquer identification using Gaussian process priors

We investigate the reconstruction of nonlinear systems from locally identified linear models. It is well known that the equilibrium linearisations of a system do not uniquely specify the global dynamics. Information about the dynamics near to equilibrium provided by the equilibrium linearisations is therefore combined with other information about the dynamics away from equilibrium provided by suitable measured data. That is, a hybrid local/global modelling approach is considered. A non-parametric Gaussian process prior approach is proposed for combining in a consistent manner these two distinct types of data. This approach seems to provide a framework that is both elegant and powerful, and which is potentially in good accord with engineering practice

Multisensory Processes: A Balancing Act across the Lifespan.

Multisensory processes are fundamental in scaffolding perception, cognition, learning, and behavior. How and when stimuli from different sensory modalities are integrated rather than treated as separate entities is poorly understood. We review how the relative reliance on stimulus characteristics versus learned associations dynamically shapes multisensory processes. We illustrate the dynamism in multisensory function across two timescales: one long term that operates across the lifespan and one short term that operates during the learning of new multisensory relations. In addition, we highlight the importance of task contingencies. We conclude that these highly dynamic multisensory processes, based on the relative weighting of stimulus characteristics and learned associations, provide both stability and flexibility to brain functions over a wide range of temporal scales

Divide and conquer identification using Gaussian process priors

We investigate the reconstruction of nonlinear systems from locally identified linear models. It is well known that the equilibrium linearisations of a system do not uniquely specify the global dynamics. Information about the dynamics near to equilibrium provided by the equilibrium linearisations is therefore combined with other information about the dynamics away from equilibrium provided by suitable measured data. That is, a hybrid local/global modelling approach is considered. A non-parametric Gaussian process prior approach is proposed for combining in a consistent manner these two distinct types of data. This approach seems to provide a framework that is both elegant and powerful, and which is potentially in good accord with engineering practice

Measurement of throughput variation across a large format volume-phase holographic grating

In this paper, we report measurements of diffraction efficiency and angular dispersion for a large format (~ 25 cm diameter) Volume-Phase Holographic (VPH) grating optimized for near-infrared wavelengths (0.9 ~ 1.8 μm). The aim of this experiment is to see whether optical characteristics vary significantly across the grating. We sampled three positions in the grating aperture with a separation of 5 cm between each. A 2 cm diameter beam is used to illuminate the grating. At each position, throughput and diffraction angle were measured at several wavelengths. It is found that whilst the relationship between diffraction angle and wavelength is nearly he same at the three positions, the throughputs vary by up to ~ 10% from position to position. We explore the origin of the throughput variation by comparing the data with predictions from coupled-wave analysis. We find that it can be explained by a combination of small variations over the grating aperture in gelatin depth and/or refractive index modulation amplitude, and amount of energy loss by internal absorption and/or surface reflection