A review of 16 years of quality control parameters at a mass-rearing facility producing Queensland fruit fly, Bactrocera tryoni

From 1996 to 2012, the mass-rearing facility at Camden (NSW, Australia) has been producing Queensland fruit flies, Bactrocera tryoni (Froggatt) (Diptera: Tephritidae). During this time, the facility has regularly recorded fly quality parameters, creating a unique data set that provides an invaluable opportunity to evaluate the interrelationships among standard quality control (QC) parameters and test for redundant QC variables. Here, we conducted an exploratory data analysis to reveal relationships among the QC parameters. We found that pupal weight, adult lifespan, and longevity under nutritional stress (i.e., survival duration without food or water) had distinct monthly trends, suggesting that these QC parameters are sensitive to seasonal conditions. Furthermore, emergence percentage, flight ability, and adult lifespan were adversely affected by the dyeing/handling/irradiation process associated with sterile insect releases. Using a multivariate approach and controlling for monthly and yearly patterns, we showed that pupal weight and egg hatch are consistently negatively related and that percentage male and emergence rates are consistently negatively related. These results suggest that these correlation pairs measure similar quality information and hence one QC variable from each pair could be dropped. Flight ability was not strongly correlated with any of the QC variables, suggesting that this QC variable remains a useful QC metric. Finally, the longevity under nutritional stress QC appears to be fairly insensitive to QCs and we suggest that it should be replaced by the standard mortality under stress test.

Learning to minimize energy costs and maximize mechanical work in a bimanual coordination task

The authors addressed the hypothesis that economy in motor coordination is a learning phenomenon realized by both reduced energy cost for a given workload and more external work at the same prepractice metabolic and attentional energy expenditure. "Self-optimization" of movement parameters has been proposed to reflect learned motor adaptations that minimize energy costs. Twelve men aged 22.3 [+ or -] 3.9 years practiced a 90[degrees] relative phase, upper limb, independent ergometer cycling task at 60 rpm, followed by a transfer test of unpracticed (45 and 75 rpm) and self-paced cadences. Performance in all conditions was initially unstable, inaccurate, and relatively high in both metabolic and attentional energy costs. With practice, coordinative stability increased, more work was performed for the same metabolic and attentional costs, and the same work was done at a reduced energy cost. Self-paced cycling was initially below the metabolically optimal, but following practice at 60 rpm was closer to optimal cadence. Given the many behavioral options of the motor system in meeting a variety of everyday movement task goals, optimal metabolic and attentional energy criteria may provide a solution to the problem of selecting the most adaptive coordination and control parameters.

A hybrid contact state analysis methodology for robotic-based adjustment of cylindrical pair

The peg-in-hole insertion and adjustment operation is one of the most common tasks in the robotic and automatic assembly processes. Fine motion strategies associated with adjustment operations on a peg-in-hole are fundamental manipulations that can be utilised in dynamic assembly and reconfigurable workholding or fixturing systems. This paper presents a comprehensive study of robotic-based height adjustment of a cylindrical pair based on maintaining minimum contact forces between the links. The outer link is held by the end-effector of a six-DOF (Degrees of freedom) serial articulated robot manipulator. The environment represented by the inner link can be either static or dynamic. A force-based approach and a d value approach are established to determine the type of contact that exists between the links of a cylindrical pair, and to extract control parameters. Based on the comparison and analysis of these two approaches, a hybrid methodology is established by combining a d value approach with a force-based approach for contact state determination. Formulations capable of extracting necessary control parameters, which ensure minimum contact forces between the links, are established from both planar and spatial viewpoints under both static and dynamic environmental conditions. Experimental results demonstrate the effectiveness of the proposed methodology.

Weldability of duplex stainless steel

Duplex stainless steels (DSSs) have many advantages due to the unique structural combination of ferrite and austenite grains. The structural change of these materials is very complex during welding, and it deteriorates the functional properties. This research investigates different welding processes such as laser beam, resistance, tungsten inert gas, friction stir, submerged arc, and plasma arc weldings considering the research available in the literature. The welding mechanism, change of material structure, and control parameters have been analyzed for every welding process. This analysis clearly shows that DSS melts in all most all welding processes, but the thermal cycle and maximum heat input are different. This difference affects the resulting structure and functional properties of the weld significantly.

Visual feedback control of a robot in an unknown environment (learning control using neural networks)

In this paper, a visual feedback control approach based on neural networks is presented for a robot with a camera installed on its end-effector to trace an object in an unknown environment. First, the one-to-one mapping relations between the image feature domain of the object to the joint angle domain of the robot are derived. Second, a method is proposed to generate a desired trajectory of the robot by measuring the image feature parameters of the object. Third, a multilayer neural network is used for off-line learning of the mapping relations so as to produce on-line the reference inputs for the robot. Fourth, a learning controller based on a multilayer neural network is designed for realizing the visual feedback control of the robot. Last, the effectiveness of the present approach is verified by tracing a curved line using a 6-degrees-of-freedom robot with a CCD camera installed on its end-effector. The present approach does not necessitate the tedious calibration of the CCD camera and the complicated coordinate transformations.

Thermal control of high pressure die casting using computational fluid dynamics

The quality of high pressure die castings is a function of many interdependent parameters. It has been observed that many defects detected in the HPDC castings can be tracked back to poor die temperature distribution in the critical areas. It has therefore been recommended that the development of a technique to directly control the critical features - making them less sensitive to thermal related parameters - be very beneficial to the HPDC industry. From the information obtained from thermal image (processing), computational fluid dynamics has been applied to design the layout of internal cooling system and assign the flow conditions such as flow rate and pressure of the cooling water. it is observed that CFD prediction provides an excellent insight into the thermal balance of the high pressure die casting.

A reinforcement learning approach for robot control in an unknown environment

In this paper, a control approach based on reinforcement learning is present for a robot to complete a dynamic task in an unknown environment. First, a temporal difference-based reinforcement learning algorithm and its evaluation function are used to make the robot learn with its trials and errors as well as experiences. Second, the simulation are carried out to adjust the parameters of the learning algorithm and determine an optimal policy by using the models of a robot. Last, the effectiveness of the present approach is demonstrated by balancing an inverse pendulum in the unknown environment.

Location based power control for energy critical sensors in a disconnected network

This paper provides a location based power control strategy for disconnected sensory nodes deployed for long term service. Power conservation is of importance particularly when sensors communicate with a mobile robot used for data collection. The proposed algorithm uses estimations from a Robust Extended Kalman Filter (REKF) with RSSI measurements, in implementing a sigmoid function based power control algorithm which essentially approaches a desired power emission trajectory based on carrier-to-interference ratios(CIR) to ensure interferenceless reception. The more realistic modelling we use incorporates physical dynamics between the mobile robot and the sensors together with the wireless propagation parameters between the transmitter and receiver to formulate a sophisticated and effective power control strategy for the exclusive usage of energy critical disconnected nodes in a sensory network increasing their life span.

Power control in CDMA systems based on channel identification

Power control design is a critical aspect of CDMA cellular systems design. This paper develops an adaptive power controller design method for CDMA systems. The key to the power control design is on the recursive identification of the underlying wireless stochastic channel model parameters. The identification process guarantees the power controller to work well for systems in unknown or time varying network environment.

Fuzzy neural networks for control of dynamic systems

This thesis provides a unified and comprehensive treatment of the fuzzy neural networks as the intelligent controllers. This work has been motivated by a need to develop the solid control methodologies capable of coping with the complexity, the nonlinearity, the interactions, and the time variance of the processes under control. In addition, the dynamic behavior of such processes is strongly influenced by the disturbances and the noise, and such processes are characterized by a large degree of uncertainty. Therefore, it is important to integrate an intelligent component to increase the control system ability to extract the functional relationships from the process and to change such relationships to improve the control precision, that is, to display the learning and the reasoning abilities. The objective of this thesis was to develop a self-organizing learning controller for above processes by using a combination of the fuzzy logic and the neural networks. An on-line, direct fuzzy neural controller using the process input-output measurement data and the reference model with both structural and parameter tuning has been developed to fulfill the above objective. A number of practical issues were considered. This includes the dynamic construction of the controller in order to alleviate the bias/variance dilemma, the universal approximation property, and the requirements of the locality and the linearity in the parameters. Several important issues in the intelligent control were also considered such as the overall control scheme, the requirement of the persistency of excitation and the bounded learning rates of the controller for the overall closed loop stability. Other important issues considered in this thesis include the dependence of the generalization ability and the optimization methods on the data distribution, and the requirements for the on-line learning and the feedback structure of the controller. Fuzzy inference specific issues such as the influence of the choice of the defuzzification method, T-norm operator and the membership function on the overall performance of the controller were also discussed. In addition, the e-completeness requirement and the use of the fuzzy similarity measure were also investigated. Main emphasis of the thesis has been on the applications to the real-world problems such as the industrial process control. The applicability of the proposed method has been demonstrated through the empirical studies on several real-world control problems of industrial complexity. This includes the temperature and the number-average molecular weight control in the continuous stirred tank polymerization reactor, and the torsional vibration, the eccentricity, the hardness and the thickness control in the cold rolling mills. Compared to the traditional linear controllers and the dynamically constructed neural network, the proposed fuzzy neural controller shows the highest promise as an effective approach to such nonlinear multi-variable control problems with the strong influence of the disturbances and the noise on the dynamic process behavior. In addition, the applicability of the proposed method beyond the strictly control area has also been investigated, in particular to the data mining and the knowledge elicitation. When compared to the decision tree method and the pruned neural network method for the data mining, the proposed fuzzy neural network is able to achieve a comparable accuracy with a more compact set of rules. In addition, the performance of the proposed fuzzy neural network is much better for the classes with the low occurrences in the data set compared to the decision tree method. Thus, the proposed fuzzy neural network may be very useful in situations where the important information is contained in a small fraction of the available data.

Use of phosphite as a control for Phytophthora cinnamomi in southeastern Victorian vegetation communities

One of the major aims of the research presented in this thesis was to assist managers of native vegetation communities in southeastern Australia in understanding the dynamics of P. cinnamomi with an important ecological species, Xanthorrhoea australis. It trialed the use of phosphite in large-scale field applications to establish the usefulness of this management option for the first time on Victorian flora. This thesis describes the process of disease development within mature X. Australia plants. For the first time it was shown that within X. australis plants, secondary disease symptoms are related to the percentage of stem that has been infested by the disease. It was evident that after initial invasion the pathogen moves via root xylem and throughout the plant within vascular to the stem, especially within the desmium. The research shows that the pathogen could not be isolated consistently even though it was considered to be responsible for disease symptoms. Trials of a control fungicide (Foli-R-fos 200) shows that protection occurs in many susceptible plants when 2 and 6g a.i./L phosphite is applied. Phytotoxicity occurred in native plants at Anglesea and within controlled environment trials when using ≥ 6g a.i./L. It will be shown that 2g a.i./L phosphite controls disease in sprayed plots within heathlands at Anglesea and a recently burnt coastal woodland community at Wilson’s Promontory. The proportion of healthy X. australis plants treated with phosphite was significantly higher than the proportion in control plots without phosphite. The research shows that phosphite was recovered from leaves of three species treated with Foli-R-fos 200 in the field. For the first time it has been shown that seed germination was reduced in two species when high concentrations of phosphite were applied. The first documentation of the effect that phosphite has on soil properties showed that nitrogen and oxidised organic carbon were the only parameters to alter significantly. This thesis provides answers to some important questions, answers that can now be used by managers in formulating better policies and actions at an operational level. There has been a dire need in Victoria to address many issues regarding P. cinnamomi and this thesis provides relevant and informative approaches to disease control, and a better understanding of the disease progress.

Terrestrial apnoeas and the development of cardiac control in Australian fur seal (Arctocephalus pusillus doriferus) pups

The development of cardiac control in association with terrestrial respiration patterns was examined throughout the period of maternal dependence in Australian fur seal pups. Resting eupnoic heart rate and respiration rate were significantly correlated (r² = 0.49) and both decreased with age (P < 0.05 in both cases). From an early age (1 month), pups displayed terrestrial apnoeas (18.1 ± 0.5 s) accompanied by substantial bradycardia (127 beats min^-1, a 13% decrease from eupnoic HR). Terrestrial apnoea duration increased significantly with age reaching a mean of 41 s just prior to weaning, slightly lower than the mean dive duration (52 s) previously recorded for pups of the same age. Correspondingly, mean apnoic heart rate decreased with age to 74 beats min^-1 just prior to weaning, representing a 25% decrease on eupnoic heart rate. Importantly, concomitant with the decrease in mean apnoic heart rate with age, an increase in the control
of bradycardia was evident with the variability in instantaneous apnoic heart decreasing such that older pups were able to maintain a low steady heart rate for the duration of the apnoea. The changes seen in these parameters are similar to those reported during postnatal development in elephant seals (Mirounga spp.) and harbour seals (Phoca vitulina), and are considered indicative of the development of cardiac control. These findings suggest a common strategy for the development of bradycardia control in both otariid and phocid seals.

Parameters important in fabricating enzyme electrodes using self-assembled monolayers of alkanethiols

The fabrication of enzyme electrodes using self-assembled monolayers (SAMs) has attracted considerable interest because of the spatial control over the enzyme immobilization. A model system of glucose oxidase covalently bound to a gold electrode modified with a SAM of 3-mercaptopropionic acid was investigated with regard to the effect of fabrication variables such as the surface topography of the underlying gold electrode, the conditions during covalent attachment of the enzyme and the buffer used. The resultant monolayer enzyme electrodes have excellent sensitivity and dynamic range which can easily be adjusted by controlling the amount of enzyme immobilized. The major drawback of such electrodes is the response which is limited by the kinetics of the enzyme rather than mass transport of substrates. Approaches to bringing such enzyme electrodes into the mass transport limiting regime by exploiting direct electron transfer between the enzyme and the electrode are outlined.

Effect of operating parameters and cleaning on the performance of ceramic membranes treating partially clarified sugar cane juice

The performance of ceramic membranes with pore sizes of 0.05 and 0.10 mm in purifying limed and partially clarified sugar cane juice was investigated under different operating conditions. From various operating conditions and strategies, switching off the permeate for 5 seconds for every 5 minutes (S5sT5 m) by an automated control valve provided higher flux. From the three pH experiments conducted on the 0.05 mm membrane, the best performance was observed at a pH of 7.5. Amongst the four fouling models tested, the cake filtration model fitted the performance of both membranes with higher accuracy at a transmembrane pressure of 0.5 bar. Filtering the cane juice through the membrane reduced the turbidity by 99.7%, color by 15%, and the starch concentration by 80% as well as increased the purity by 1.4%. The effective cleaning chemical composition from experimental results showed that 1% NaOH and 3000 ppm NaOCl solution performed the best but only for the experiments that were treating limed and partially clarified juice at pH 7.5.

A new design of sliding mode control systems

A new sliding mode control technique for a class of SISO dynamic systems is presented in this chapter. It is seen that the stability status of the closed-loop system is first checked, based on the approximation of the most recent information of the first-order derivative of the Lyapunov function of the closed-loop system, an intelligent sliding mode controller can then be designed with the following intelligent features: (i) If the closed-loop system is stable, the correction term in the controller will continuously adjust control signal to drive the closed-loop trajectory to reach the sliding mode surface in a finite time and the desired closed-loop dynamics with the zero-error convergence can then be achieved on the sliding mode surface. (ii) If, however, the closed-loop system is unstable, the correction term is capable of modifying the control signal to continuously reduce the value of the derivative of the Lyapunov function from the positive to the negative and then drives the closed-loop trajectory to reach the sliding mode surface and ensures that the desired closed-loop dynamics can be obtained on the sliding mode surface. The main advantages of this new sliding mode control technique over the conventional one are that no chattering occurs in the sliding mode control system because of the recursive learning control structure; the system uncertainties are embedded in the Lipschitz-like condition and thus, no priori information on the upper and/or the lower bounds of the unknown system parameters and uncertain system dynamics is required for the controller design; the zero-error convergence can be achieved after the closed-loop dynamics reaches the sliding mode surface and remains on it. The performance for controlling a third-order linear system is evaluated in the simulation section to show the effectiveness and efficiency of the new sliding mode control technique.