Intelligent 3D programmable surface

Creating a highly programmable surface operating at relatively high speed and in real time is an area of research with many challenges. Such a system has applications in the field of optical telescopes, product manufacturing, and giant 3D-screens and billboards for advertising and artwork. This paper covers certain aspects of a keynote presentation at ISDT 2010 including system design, modularity, programmability and the system control intelligence. An overview of the system architecture, actuator design, electronics and distributed control will provide an insight into how the system is controlled and self-tuned for a number of applications. A simulation environment that has been developed to streamline system reconfiguration will also be presented, demonstrating translation of complex mathematical functions into 3D shapes virtually before being displayed on the physical surface.

Nonlinear adaptive backstepping controller design for controlling bidirectional power flow of BESSs in DC microgrids

In this paper, a nonlinear adaptive backstepping controlleris designed to control the bidirectional power flow (charging/discharging) of battery energy storage systems (BESSs) in a DCmicrogrid under different operating conditions. The controller isdesigned in such a manner that the BESSs can store the excess energyfrom the renewable energy sources (RESs) in a DC microgrid aftersatisfying the load demand and also feeding back the stored energyto the load when RESs are not sufficient. The proposed controller isalso designed to maintain a constant voltage at the DC bus, whereall components of DC microgrids are connected, while controllingthe power flow of BESSs. This paper considers solar photovoltaic(PV) systems as the RES whereas a diesel generator equipped witha rectifier is used as a backup supply to maintain the continuity ofpower supply in the case of emergency situations. The controller isdesigned recursively based on the Lyapunov control theory whereall parameters within the model of BESSs are assumed to beunknown. These unknown parameters are then estimated throughthe adaptation laws and whose stability is ensured by formulatingsuitable control Lyapunov functions (CLFs) at different stages ofthe design process. Moreover, a scheme is also presented to monitorthe state of charge (SOC) of the BESS. Finally, the performanceof the proposed controller is verified on a test DC microgrid undervarious operating conditions. The proposed controller ensures the DCbus voltage regulation within the acceptable limits under differentoperating conditions.

Using information flow model to specify the Kanban-controlled shopfloor control system

The implementation of Kanban-based production control systems may be difficult in make-to-order environments such as job shops. The flexible manufacturing approach constitutes a promising solution to adapt the Kanban method to such environments. This paper presents an information flow modelling approach for specifying the operational planning and control functions of the Kanban-controlled shopfloor control system (KSCS) in a flexible manufacturing environment. By decomposing the KSCS control functionalities, we have created the system information flow model through the data flow diagrams of Structured Systems Analysis Methodology. The data flow diagrams serve effective system specifications for communicating the system operations to participants of different disciplines as well as the system model for the design and development of KSCS.

An autonomous trimming system of large glass fiber reinforced plastics parts using an omni-directional mobile robot and its control

This paper describes an automated trimming system of large glass fiber reinforced plastic (GFRP) using an omni-directional wheeled mobile robot (WMR) and its path control method. In trimming GFRP parts, much glass fiber and plastic powder dust occur and it becomes bad visible in environment. It is necessary to correct dead-reckoning errors of the WMR in order to control its moving path. We have discussed an external correction method of the dead-reckoning errors for the WMR using ultrasonic sensor.

On-line tool condition monitoring and control system in forging processes

Cold bulk metal forming has made large-scale production of small complex solid parts economically feasible. Tooling used in metal forming poses many uncertainties in the preliminary cost estimation and production process and continual tool replacement and maintenance dramatically reduces productivity and raises manufacturing cost. In order to tackle this, an on-line tool condition monitoring system using artificial neural network (ANN) to integrate information from multiple sensors for forging process has been developed. Together with the force, acoustic emission signals and process conditions, information developed from theoretical models is integrated into the ANN tool monitoring system to predict tool life and provide the maintenance schedule.

Knowledge sharing in professional accountancy firms : the effects of task complexity and management control system

Numerous empirical studies on knowledge management have focused on effectiveness of enablers such as organizational structure (Bennett and Gabriel, 1999; Gold et al., 2001), technology (Gold et al., 2001; O’Dell and Grayson, 1998), culture (DeLong and Fahey, 2000; Gupta and Govindarajan, 2000), managerial system (Nonaka, 1994; Sveiby, 1997) and strategy (Bierly and Chakrabarti, 1996; Holsapple and Joshi, 2001) on knowledge sharing. These enablers are organizational infrastructure or mechanism for facilitating the sharing of knowledge in a firm. In knowledge-intensive firms, task complexity and management control systems (MCS) can potentially affect the mode and effectiveness of knowledge sharing. However, these two factors have not been distinctly and explicitly investigated and discussed in literature relevant to the domain of knowledge sharing and management. This study proposes to examine how task complexity and the design of MCS could be the key determinants of the mode and effectiveness of knowledge sharing in professional accounting firms or practices.

Context-based e-health system access control mechanism

E-Health systems logically demand a sufficiently fine-grained authorization policy for access control. The access to medical information should not be just role-based but should also include the contextual condition of the role to access data. In this paper, we present a mechanism to extend the standard role-based access control to incorporate contextual information for making access control decisions in e-health application. We present an architecture consisting of authorisation and context infrastructure that work cooperatively to grant access rights based on context-aware authorization policies and context information.

Consensus control for a system of underwater swarm robots

The control of a swarm of underwater robots requires both a control algorithm and a communication system. Unfortunately, underwater communications is difficult at the best of times and so large time delays and minimal information is a concern. The control system must be able to handle a large number of robots without a master control, i.e., a decentralized control approach. This paper describes Consensus control as a way to decentralize. Consensus control allows each robot to know the final goal and then to decide, based on the position of the other robots, its best move to help achieve the goal.

Adaptive cruise control look-ahead system for energy management of vehicles

Cruise control in motor vehicles enhances safe and efficient driving by maintaining a constant speed at a preset level. Adaptive Cruise Control (ACC) is the latest development in cruise control. It controls engine throttle position and braking to maintain a safe distance behind a vehicle in front by responding to the speed of this vehicle, thus providing a safer and more relaxing driving environment. ACC can be further developed by including the look-ahead method of predicting environmental factors such as wind speed and road slope. The conventional analytical control methods for adaptive cruise control can generate good results; however they are difficult to design and computationally expensive. In order to achieve a robust, less computationally expensive, and at the same time more natural human-like speed control, intelligent control techniques can be used. This paper presents an Adaptive Neuro-Fuzzy Inference System (ANFIS) based on ACC systems that reduces the energy consumption of the vehicle and improves its efficiency. The Adaptive Cruise Control Look-Ahead (ACC-LA) system works as follows: It calculates the energy consumption of the vehicle under combined dynamic loads like wind drag, slope, kinetic energy and rolling friction using road data, and it includes a look-ahead strategy to predict the future road slope. The cruise control system adaptively controls the vehicle speed based on the preset speed and the predicted future slope information. By using the ANFIS method, the ACC-LA is made adaptive under different road conditions (slope angle and wind direction and speed). The vehicle was tested using the adaptive cruise control look-ahead energy management system, the results compared with the vehicle running the same test but without the adaptive cruise control look-ahead energy management system. The evaluation outcome indicates that the vehicle speed was efficiently controlled through the look-ahead methodology based upon the driving cycle, and that the average fuel consumption was reduced by 3%.