Qualitative assessment of bubble behaviour for central and asymmetric injection in 2D gas-solid fluidized bed using image analysis technique and CFD modelling

Bubble characteristics such as shape, size, and trajectory control the hydrodynamics and therefore heat transfer in fluidized bed reactors. Thus understanding these characteristics is very important for the design and scaleup of fluidized beds. An earlier developed Eulerian-Eulerian two-fluid model for simulating dense gas–solid two-phase flow has been used to compare the experimental data in a pseudo-two-dimensional (2-D) bed. Bubbles are injected asymmetrically by locating the nozzle at proximity to the wall, thus presenting the effect wall has on asymmetrical injection as compared to symmetrical injection. In this work, a digital image analysis technique was developed to study the bubble behaviour in a two-dimensional bubbling bed. The high-speed photography reveals an asymmetric wake formation during detachment indicating an early onset of mixing process. The wall forces acts tangentially on thebubble and has a significant impact on the bubble shape, neck formation during detachment and its trajectory through the bed. Larger bubbles drifting away from the centre with longer paths are observed. This qualitative behaviour is well predicted by CFD modelling. Asymmetric injection can significantly influence the heat and mass transfer characteristics.

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.

Location based power control for mobile devices in a cellular network

This paper provides location estimation based power control strategy for cellular radio systems via a location based interference management scheme. Our approach considers the carrier-to-interference as dependent on the transmitter and receiver separation distance and therefore an accurate estimation of the precise locations can provide the power critical mobile user to control the transition power accordingly. In this fully
distributed algorithms, we propose using a Robust Extended Kalman Filter (REKF) to derive an estimate of the mobile user’s closest mobile base station from the user’s location, heading and altitude. Our analysis demonstrates that this algorithm can successfully track the mobile users with less system complexity, as it requires measurements from only one or two closest mobile base stations and hence enable the user to transmit at the rate that is sufficient for the interference management. Our power control
algorithms based on this estimation converges to the desired power trajectory. Further, the technique is robust against system uncertainties caused by the inherent deterministic nature of the mobility model. Through simulation, we show the accuracy of our prediction algorithm and the simplicity of its implementation.

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.

Functional status after bloodstream infection : the survivors' trajectory

There is very little information about the quality of survival for patients after bacterial and fungal bloodstream infections. This study aimed to describe the functional status and level of activities of daily living for a group of survivors of these infections. A prospective exploratory design was used to track adults for 6 months after onset of infection. Survivors were assessed for reduced or full health status. Telephone interviews, using the London Handicap Scale and the Sickness Impact Profile, provided self-assessed functional status for those able to participate; 165 adults were tracked. Before infection, only 25% of adults had an active malignancy and one-tenth required a high level of assistance with activities of daily living. Six months after infection, half of survivors had reduced health and many had not returned to their normal functional activity level. There was considerable continued reduced health in survivors, demonstrating that not only do bloodstream infections result in high short-term mortality but also in considerable longer term morbidity and profound alteration in functional health status for many survivors.

A study on look-ahead control and energy management strategies in hybrid electric vehicles

Fuel efficiency in a hybrid electric vehicle requires a fine balance between usage of combustion engine and battery power. Information about the geometry of the road and traffic ahead can have a great impact on optimized control and the power split between the main parts of a hybrid electric vehicle. This paper provides a survey on the existing methods of control and energy management emphasizing on those that consider the look-ahead road situation and trajectory information. Then it presents the future trends in the control and energy management of hybrid electric vehicles.

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.

Intelligent control and look-ahead energy management of hybrid electric vehicles

A review of the state of knowledge in the field of control and energy management in HEVs is carried out. The key innovation of the project is the development of a model of a PHEV using the real road data with an intelligent look-ahead online controller. Another novelty of this work is the method of route planning. It combines the information of vehicle sensors such as accelerometer and speedometer with the data of a GPS to create a road grade map for use within the look-ahead energy management strategy in the vehicle. For the PHEV, an adaptive cruise controller is modelled and an optimisation method is applied to obtain the best speed profile during a trajectory. Finally, the nonlinear model of the vehicle is applied with the sliding mode controller. The effect of using this controller is compared with the universal cruise controller. The stability of the system is studied and proved.

Impaired online control in children with developmental coordination disorder reflects development immaturity

The present study aimed to clarify whether a reduced ability to correct movements in-flight observed in children with developmental coordination disorder (DCD) reflects a developmental immaturity or deviance from the typical trajectory. Eighteen children with DCD (8–12 years), 18 age-matched controls, and 12 younger controls (5–7 years) completed a double-step reaching task. Compared to older controls, children with DCD and younger controls showed similarly prolonged reaching when the target unexpectedly shifted at movement onset and were equally slow to correct their reaching trajectory. These results suggest that impaired online control in DCD reflects developmental immaturity, possibly implicating the parietal-cerebellar cortices.

Does implicit motor imagery ability predict reaching correction efficiency? A test of recent models of human motor control

Neurocomputational models of reaching indicate that efficient purposive correction of movement midflight (e.g., online control) depends on one's ability to generate and monitor an accurate internal (neural) movement representation. In the first study to test this empirically, the authors investigated the relationship between healthy young adults’ implicit motor imagery performance and their capacity to correct their reaching trajectory. As expected, after controlling for general reaching speed, hierarchical regression demonstrated that imagery ability was a significant predictor of hand correction speed; that is, faster and more accurate imagery performance associated with faster corrections to reaching following target displacement at movement onset. They argue that these findings provide preliminary support for the view that a link exists between an individual's ability to represent movement mentally and correct movement online efficiently.

Rapid on-line control to reaching is preserved in children with congenital spastic hemiplegia: evidence from double-step reaching performance

This study aimed to investigate the integrity of on-line control of reaching in congenital spastic hemiplegia in light of disparate evidence. Twelve children with and without spastic hemiplegia (11-17 years old) completed a double-step reaching task requiring them to reach and touch a target that remained stationary for most trials (viz nonjump trial) but unexpectedly displaced laterally at movement onset for a minority of trials (20%: known as jump trials). Although children with spastic hemiplegia were generally slower than age-matched controls, they could account for target perturbation at age-appropriate levels shown by a lack of interaction effect on movement time and nonsignificant group difference for time to reach trajectory correction on jump trials. Our data suggest that at a group level, on-line control of reaching may be age-appropriate in spastic hemiplegia. However, our data also highlight the need to experimentally acknowledge the considerable heterogeneity of the spastic hemiplegia population when investigating motor cognition.

Adaptive fuzzy multi-surface sliding control of multiple-input and multiple-output autonomous flight systems

In this study, we proposed an adaptive fuzzy multi-surface sliding control (AFMSSC) for trajectory tracking of 6 degrees of freedom inertia coupled aerial vehicles with multiple inputs and multiple outputs (MIMO). It is shown that an adaptive fuzzy logic-based function approximator can be used to estimate the system uncertainties and an iterative multi-surface sliding control design can be carried out to control flight. Using AFMSSC on MIMO autonomous flight systems creates confluent control that can account for both matched and mismatched uncertainties, system disturbances and excitation in internal dynamics. It is proved that the AFMSSC system guarantees asymptotic output tracking and ultimate uniform boundedness of the tracking error. Simulation results are presented to validate the analysis.

Reduced motor imagery efficiency is associated with online control difficulties in children with probable developmental coordination disorder

Recent evidence indicates that the ability to correct reaching movements in response to unexpected target changes (i.e., online control) is reduced in children with developmental coordination disorder (DCD). Recent computational modeling of human reaching suggests that these inefficiencies may result from difficulties generating and/or monitoring internal representations of movement. This study was the first to test this putative relationship empirically. We did so by investigating the degree to which the capacity to correct reaching mid-flight could be predicted by motor imagery (MI) proficiency in a sample of children with probable DCD (pDCD). Thirty-four children aged 8 to 12 years (17 children with pDCD and 17 age-matched controls) completed the hand rotation task, a well-validated measure of MI, and a double-step reaching task (DSRT), a protocol commonly adopted to infer one's capacity for correcting reaching online. As per previous research, children with pDCD demonstrated inefficiencies in their ability to generate internal action representations and correct their reaching online, demonstrated by inefficient hand rotation performance and slower correction to the reach trajectory following unexpected target perturbation during the DSRT compared to age-matched controls. Critically, hierarchical moderating regression demonstrated that even after general reaching ability was controlled for, MI efficiency was a significant predictor of reaching correction efficiency, a relationship that was constant across groups. Ours is the first study to provide direct pilot evidence in support of the view that a decreased capacity for online control of reaching typical of DCD may be associated with inefficiencies generating and/or using internal representations of action.

Robust finite-time tracking control of nonholonomic mobile robots without velocity measurements

The problem of robust finite-time trajectory tracking of nonholonomic mobile robots with unmeasurable velocities is studied. The contributions of the paper are that: first, in the case that the angular velocity of the mobile robot is unmeasurable, a composite controller including the observer-based partial state feedback control and the disturbance feed-forward compensation is designed, which guarantees that the tracking errors converge to zero in finite time. Second, if the linear velocity as well as the angular velocity of mobile robot is unmeasurable, with a stronger constraint, the finite-time trajectory tracking control of nonholonomic mobile robot is also addressed. Finally, the effectiveness of the proposed control laws is demonstrated by simulation.