Active Adaptive Gyrostabiliser Control System

A gyrostabiliser control system and method for stabilising marine vessel motion based on precession information only. The control system employs an Automatic Gain Control (AGC) precession controller (60). This system operates with a gain factor that is always being gradually minimized so as to let the gyro flywheel (12) develop as much precession as possible - the higher the precession, the higher the roll stabilising moment. This continuous gain change provides adaptation to changes in sea state and sailing conditions. The system effectively predicts the likelihood of maximum precession being reached. Should this event be detected, then the gain is rapidly increased so as to provide a breaking precession torque. Once the event has passed, the system again attempts to gradually decrease the gain.

A pattern adaptive thinning algorithm

A simple sequential thinning algorithm for peeling off pixels along contours is described. An adaptive algorithm obtained by incorporating shape adaptivity into this sequential process is also given. The distortions in the skeleton at the right-angle and acute-angle corners are minimized in the adaptive algorithm. The asymmetry of the skeleton, which is a characteristic of sequential algorithm, and is due to the presence of T-corners in some of the even-thickness pattern is eliminated. The performance (in terms of time requirements and shape preservation) is compared with that of a modern thinning algorithm.

Adaptive significance of the Indian caste system: an ecological perspective

Indian society is an agglomeration of several thousand endogamous groups or castes each with a restricted geographical range and a hereditarily determine mode of subsistence. These reproductively isolated castes may be compared to biological species, and the society thought of as a biological community with each caste having its specific ecological niche. In this paper we examine the ecological-niche relationships of castes which are directly dependent on natural resources. Evidence is presented to show that castes living together in the same region had so organized their pattern of resource use as to avoid excessive intercaste competition for limiting resources. Furthermore, territorial division of the total range of the caste regulated intra-caste competition. Hence, a particular plant or animal resource in a given locality was used almost exclusively by a given lineage within a caste generation after generation. This favoured the cultural evolution of traditions ensuring sustainable use of natural resources. This must have contributed significantly to the stability of Indian caste society over several thousand years. The collapse of the base of natural resources and increasing monetarization of the economy has, however, destroyed the earlier complementarity between the different castes and led to increasing conflicts between them in recent years.

Non-stationary signal analysis by least mean fourth (LMF) adaptive algorithm

A modified least mean fourth (LMF) adaptive algorithm applicable to non-stationary signals is presented. The performance of the proposed algorithm is studied by simulation for non-stationarities in bandwidth, centre frequency and gain of a stochastic signal. These non-stationarities are in the form of linear, sinusoidal and jump variations of the parameters. The proposed LMF adaptation is found to have better parameter tracking capability than the LMS adaptation for the same speed of convergence.

Structured model-following neuro-adaptive design for attitude maneuver of rigid bodies

A new structured model-following adaptive approach is presented in this paper to achieve large attitude maneuvers of rigid bodies. First, a nominal controller is designed using the dynamic inversion philosophy. Next, a neuro- adaptive design is proposed to augment the nominal design in order to assure robust performance in the presence of parameter inaccuracies as well as unknown constant external disturbances. The structured approach proposed in this paper (where kinematic and dynamic equations are handled separately), reduces the complexity of the controller structure. From simulation studies, this adaptive controller is found to be very effective in assuring robust performance.

A global convergence criterion for discrete-time multivariable adaptive systems

The paper deals with the basic problem of adjusting a matrix gain in a discrete-time linear multivariable system. The object is to obtain a global convergence criterion, i.e. conditions under which a specified error signal asymptotically approaches zero and other signals in the system remain bounded for arbitrary initial conditions and for any bounded input to the system. It is shown that for a class of up-dating algorithms for the adjustable gain matrix, global convergence is crucially dependent on a transfer matrix G(z) which has a simple block diagram interpretation. When w(z)G(z) is strictly discrete positive real for a scalar w(z) such that w-1(z) is strictly proper with poles and zeros within the unit circle, an augmented error scheme is suggested and is proved to result in global convergence. The solution avoids feeding back a quadratic term as recommended in other schemes for single-input single-output systems.

The use of F-specific coliphages to assess effluent treatment and reuse schemes

This study reports on the use of naturally occurring F-specific coliphages, as well as spiked MS-2 phage, to evaluate a land-based effluent treatment/reuse system and an effluent irrigation scheme. Both the natural phages and the spiked MS-2 phage indicated that the effluent treatment/reuse system (FILTER - Filtration and Irrigated cropping for Land Treatment and Effluent Reuse) achieved a reduction in phage levels over the treatment system by one to two log10. FILTER reduced natural F-specific phage numbers from around 103 to below 102 100-ml-1 and the spiked phage from 105 to around 104 100-ml-1 (incoming compared with outgoing water). In the effluent irrigation scheme, phage spiked into the holding ponds dropped from 106 to 102 100-ml-1 after 168 h (with no detectable levels of natural F-specific phage being found prior to spiking). Only low levels of the spiked phage (102 gm-1) could be recovered from soil irrigated with phage-spiked effluent (at 106 phage 100 ml-1) or from fruits (around 102 phage per fruit) that had direct contact with soil which had been freshly irrigated with the same phage-spiked effluent.

An adaptive power-system stabiliser which cancels the negative damping torque of a synchronous generator

The paper presents a new criterion for designing a power-system stabiliser, which is that it should cancel the negative damping torque inherent in a synchronous generator and automatic voltage regulator. The method arises from analysis based on the properties of tensor invariance, but it is easily implemented, and leads to the design of an adaptive controller. Extensive computations and simulation have been performed, and laboratory tests have been conducted on a computer-controlled micromachine system. Results are presented illustrating the effectiveness of the adaptive stabiliser.

Invited paper Application of the least mean fourth (LMF) adaptive algorithm to signals associated with gaussian noise

This paper considers the applicability of the least mean fourth (LM F) power gradient adaptation criteria with 'advantage' for signals associated with gaussian noise, the associated noise power estimate not being known. The proposed method, as an adaptive spectral estimator, is found to provide superior performance than the least mean square (LMS) adaptation for the same (or even lower) speed of convergence for signals having sufficiently high signal-to-gaussian noise ratio. The results include comparison of the performance of the LMS-tapped delay line, LMF-tapped delay line, LMS-lattice and LMF-lattice algorithms, with the Burg's block data method as reference. The signals, like sinusoids with noise and stochastic signals like EEG, are considered in this study.

An Adaptive Scheme for Learning the Probability Threshold in Pattern Recognition

The statistical minimum risk pattern recognition problem, when the classification costs are random variables of unknown statistics, is considered. Using medical diagnosis as a possible application, the problem of learning the optimal decision scheme is studied for a two-class twoaction case, as a first step. This reduces to the problem of learning the optimum threshold (for taking appropriate action) on the a posteriori probability of one class. A recursive procedure for updating an estimate of the threshold is proposed. The estimation procedure does not require the knowledge of actual class labels of the sample patterns in the design set. The adaptive scheme of using the present threshold estimate for taking action on the next sample is shown to converge, in probability, to the optimum. The results of a computer simulation study of three learning schemes demonstrate the theoretically predictable salient features of the adaptive scheme.

Spectral Sensing for Cognitive Radio: Estimation of Adaptive Frequency Hopping Signal

The issue of dynamic spectrum scene analysis in any cognitive radio network becomes extremely complex when low probability of intercept, spread spectrum systems are present in environment. The detection and estimation become more complex if frequency hopping spread spectrum is adaptive in nature. In this paper, we propose two phase approach for detection and estimation of frequency hoping signals. Polyphase filter bank has been proposed as the architecture of choice for detection phase to efficiently detect the presence of frequency hopping signal. Based on the modeling of frequency hopping signal it can be shown that parametric methods of line spectral analysis are well suited for estimation of frequency hopping signals if the issues of order estimation and time localization are resolved. An algorithm using line spectra parameter estimation and wavelet based transient detection has been proposed which resolves above issues in computationally efficient manner suitable for implementation in cognitive radio. The simulations show promising results proving that adaptive frequency hopping signals can be detected and demodulated in a non cooperative context, even at a very low signal to noise ratio in real time.

Vineland Adaptive Behavior Scales - II profile of young children with Autism Spectrum Disorder

Adaptive behaviour is a crucial area of assessment for individuals with Autism Spectrum Disorder (ASD). This study examined the adaptive behaviour profile of 77 young children with ASD using the Vineland-II, and analysed factors associated with adaptive functioning. Consistent with previous research with the original Vineland a distinct autism profile of Vineland-II age equivalent scores, but not standard scores, was found. Highest scores were in motor skills and lowest scores were in socialisation. The addition of the Autism Diagnostic Observation Schedule (ADOS) calibrated severity score did not contribute significant variance to Vineland-II scores beyond that accounted for by age and nonverbal ability. Limitations, future directions, and implications are discussed.

A novel approach to 6-DOF adaptive trajectory tracking control of an AUV in the presence of parameter uncertainties

In this paper, the trajectory tracking control of an autonomous underwater vehicle (AUVs) in six-degrees-of-freedom (6-DOFs) is addressed. It is assumed that the system parameters are unknown and the vehicle is underactuated. An adaptive controller is proposed, based on Lyapunov׳s direct method and the back-stepping technique, which interestingly guarantees robustness against parameter uncertainties. The desired trajectory can be any sufficiently smooth bounded curve parameterized by time even if consist of straight line. In contrast with the majority of research in this field, the likelihood of actuators׳ saturation is considered and another adaptive controller is designed to overcome this problem, in which control signals are bounded using saturation functions. The nonlinear adaptive control scheme yields asymptotic convergence of the vehicle to the reference trajectory, in the presence of parametric uncertainties. The stability of the presented control laws is proved in the sense of Lyapunov theory and Barbalat׳s lemma. Efficiency of presented controller using saturation functions is verified through comparing numerical simulations of both controllers.

Duckweed-based Wastewater Treatment Systems: Design Aspects and Integrated Reuse Options for Queensland Conditions

Point sources of wastewater pollution, including effluent from municipal sewage treatment plants and intensive livestock and processing industries, can contribute significantly to the degradation of receiving waters (Chambers et al. 1997; Productivity Commission 2004). This has led to increasingly stringent local wastewater discharge quotas (particularly regarding Nitrogen, Phosphorous and suspended solids), and many municipal authorities and industry managers are now faced with upgrading their existing treatment facilities in order to comply. However, with high construction, energy and maintenance expenses and increasing labour costs, traditional wastewater treatment systems are becoming an escalating financial burden for the communities and industries that operate them. This report was generated, in the first instance, for the Burdekin Shire Council to provide information on design aspects and parameters critical for developing duckweed-based wastewater treatment (DWT) in the Burdekin region. However, the information will be relevant to a range of wastewater sources throughout Queensland. This information has been collated from published literature and both overseas and local studies of pilot and full-scale DWT systems. This report also considers options to generate revenue from duckweed production (a significant feature of DWT), and provides specifications and component cost information (current at the time of publication) for a large-scale demonstration of an integrated DWT and fish production system.