Injection velocity control of thermoplastic injection molding via a double controller scheme

Injection velocity has been recognized as a key variable in thermoplastic injection molding. Its closed-loop control is, however, difficult due to the complexity of the process dynamic characteristics. The basic requirements of the control system include tracking of a pre-determined injection velocity curve defined in a profile, load rejection and robustness. It is difficult for a conventional control scheme to meet all these requirements. Injection velocity dynamics are first analyzed in this paper. Then a novel double-controller scheme is adopted for the injection velocity control. This scheme allows an independent design of set-point tracking and load rejection and has good system robustness. The implementation of the double-controller scheme for injection velocity control is discussed. Special techniques such as profile transformation and shifting are also introduced to improve the velocity responses. The proposed velocity control has been experimentally demonstrated to be effective for a wide range of processing conditions.

Conservation genetics of the water mouse, Xeromys myoides Thomas, 1889

The water mouse, Xeromys myoides, is currently recognised as a vulnerable species in Australia, inhabiting a small number of distinct and isolated coastal regions of Queensland and the Northern Territory. An examination of the evolutionary history and contemporary influences shaping the genetic structure of this species is required to make informed conservation management decisions. Here, we report the first analysis undertaken on the phylogeography and population genetics of the water mouse across its mainland Australian distribution. Genetic diversity was assessed at two mitochondrial DNA (Cytochrome b, 1000 bp; D-loop, 400 bp) and eight microsatellite DNA loci. Very low genetic diversity was found, indicating that water mice underwent a recent expansion throughout their Australian range and constitute a single evolutionarily significant unit. Microsatellite analyses revealed that the highest genetic diversity was found in the Mackay region of central Queensland; population substructure was also identified, suggesting that local populations may be isolated in this region. Conversely, genetic diversity in the Coomera region of south-east Queensland was very low and the population in this region has experienced a significant genetic bottleneck. These results have significant implications for future management, particularly in terms of augmenting populations through translocations or reintroducing water mice in areas where they have gone extinct.

An efficiency optimization scheme for bidirectional inductive power transfer systems

Unidirectional inductive power transfer (UIPT) systems allow loads to consume power while bidirectional IPT (BIPT) systems are more suitable for loads requiring two way power flow such as vehicle to grid (V2G) applications with electric vehicles (EVs). Many attempts have been made to improve the performance of BIPT systems. In a typical BIPT system, the output power is control using the pickup converter phase shift angle (PSA) while the primary converter regulates the input current. This paper proposes an optimized phase shift modulation strategy to minimize the coil losses of a series – series (SS) compensated BIPT system. In addition, a comprehensive study on the impact of power converters on the overall efficiency of the system is also presented. A closed loop controller is proposed to optimize the overall efficiency of the BIPT system. Theoretical results are presented in comparison to both simulations and measurements of a 0.5 kW prototype to show the benefits of the proposed concept. Results convincingly demonstrate the applicability of the proposed system offering high efficiency over a wide range of output power.

Fusion of worlds : consumers’ self-narrative in a hybrid physical/digital world

As the Internet becomes deeply embedded into consumers’ daily life, the digital virtual world brings significant influence to consumers’ self and narrative. Prior studies look at consumer self from either from a certain online space or comparing consumers’ physical and digital virtual selves but not the integration of the physical/digital world. This paper aims to explore the meanings of the digital virtual space on consumers’ narrative as a whole (their interests, dreams, or subjectivity). We utilise a postmodern concept of the cyborg to understand the cultural complexity, subjective meanings of, and the extent to which the digital virtual space plays a role in consumers’ self-narrative. We conducted in-depth interviews and gathered three consumer narratives. Our findings indicate that consumers’ narrative contains important fragments from both physical and digital virtual worlds and their physical and digital virtual selves form a feedback loop that strengthen their overall narrative.

Localization and place recognition using an ultra-wide band (UWB) radar

This paper presents an approach to mobile robot localization, place recognition and loop closure using a monostatic ultra-wide band (UWB) radar system. The UWB radar is a time-of-flight based range measurement sensor that transmits short pulses and receives reflected waves from objects in the environment. The main idea of the poposed localization method is to treat the received waveform as a signature of place. The resulting echo waveform is very complex and highly depends on the position of the sensor with respect to surrounding objects. On the other hand, the sensor receives similar waveforms from the same positions.Moreover, the directional characteristics of dipole antenna is almost omnidirectional. Therefore, we can localize the sensor position to find similar waveform from waveform database. This paper proposes a place recognitionmethod based on waveform matching, presents a number of experiments that illustrate the high positon estimation accuracy of our UWB radar-based localization system, and shows the resulting loop detection performance in a typical indoor office environment and a forest.

Tracking control of a class of Hamiltonian mechanical systems with disturbances

This paper presents a trajectory-tracking control strategy for a class of mechanical systems in Hamiltonian form. The class is characterised by a simplectic interconnection arising from the use of generalised coordinates and full actuation. The tracking error dynamic is modelled as a port-Hamiltonian Systems (PHS). The control action is designed to take the error dynamics into a desired closed-loop PHS characterised by a constant mass matrix and a potential energy with a minimum at the origin. A transformation of the momentum and a feedback control is exploited to obtain a constant generalised mass matrix in closed loop. The stability of the close-loop system is shown using the close-loop Hamiltonian as a Lyapunov function. The paper also considers the addition of integral action to design a robust controller that ensures tracking in spite of disturbances. As a case study, the proposed control design methodology is applied to a fully actuated robotic manipulator.

Toward the adaptive generation of bespoke game content

In this chapter, we explore methods for automatically generating game content—and games themselves—adapted to individual players in order to improve their playing experience or achieve a desired effect. This goes beyond notions of mere replayability and involves modeling player needs to maximize their enjoyment, involvement, and interest in the game being played. We identify three main aspects of this process: generation of new content and rule sets, measurement of this content and the player, and adaptation of the game to change player experience. This process forms a feedback loop of constant refinement, as games are continually improved while being played. Framed within this methodology, we present an overview of our recent and ongoing research in this area. This is illustrated by a number of case studies that demonstrate these ideas in action over a variety of game types, including 3D action games, arcade games, platformers, board games, puzzles, and open-world games. We draw together some of the lessons learned from these projects to comment on the difficulties, the benefits, and the potential for personalized gaming via adaptive game design.

Histogram matching and global initialization for laser-only SLAM in large unstructured environments

This paper presents an enhanced algorithm for matching laser scan maps using histogram correlations. The histogram representation effectively summarizes a map's salient features such that pairs of maps can be matched efficiently without any prior guess as to their alignment. The histogram matching algorithm has been enhanced in order to work well in outdoor unstructured environments by using entropy metrics, weighted histograms and proper thresholding of quality metrics. Thus our large-scale scan-matching SLAM implementation has a vastly improved ability to close large loops in real-time even when odometry is not available. Our experimental results have demonstrated a successful mapping of the largest area ever mapped to date using only a single laser scanner. We also demonstrate our ability to solve the lost robot problem by localizing a robot to a previously built map without any prior initialization.

Modeling and control of a 3500 tonne mining robot

Draglines are extremely large machines that are widely used in open-cut coal mines for overburden stripping. Since 1994 we have been working toward the development of a computer control system capable of automatically driving a dragline for a large portion of its operating cycle. This has necessitated the development and experimental evaluation of sensor systems, machines models, closed-loop control controllers, and an operator interface. This paper describes our steps toward the goal through scale-model and full-scale field experimentation.

Height estimation for an autonomous helicopter

Height is a critical variable for helicopter hover control. In this paper we discuss, and present experimental results for, two different height sensing techniques: ultrasonic and stereo imaging, which have complementary characteristics. Feature-based stereo is used which provides a basis for visual odometry and attitude estimation in the future.

Modeling and control of a robotic power line inspection vehicle

Power line inspection is a vital function for electricity supply companies but it involves labor-intensive and expensive procedures which are tedious and error-prone for humans to perform. A possible solution is to use an unmanned aerial vehicle (UAV) equipped with video surveillance equipment to perform the inspection. This paper considers how a small, electrically driven rotorcraft conceived for this application could be controlled by visually tracking the overhead supply lines. A dynamic model for a ducted-fan rotorcraft is presented and used to control the action of an Air Vehicle Simulator (AVS), consisting of a cable-array robot. Results show how visual data can be used to determine, and hence regulate in closed loop, the simulated vehicle’s position relative to the overhead lines.

Applying digital product memories in industrial production

Industrial production and supply chains face increased demands for mass customization and tightening regulations on the traceability of goods, leading to higher requirements concerning flexibility, adaptability, and transparency of processes. Technologies for the ’Internet of Things' such as smart products and semantic representations pave the way for future factories and supply chains to fulfill these challenging market demands. In this chapter a backend-independent approach for information exchange in open-loop production processes based on Digital Product Memories DPMs is presented. By storing order-related data directly on the item, relevant lifecycle information is attached to the product itself. In this way, information handover between several stages of the value chain with focus on the manufacturing phase of a product has been realized. In order to report best practices regarding the application of DPM in the domain of industrial production, system prototype implementations focusing on the use case of producing and handling a smart drug case are illustrated.

Adaptive compliance control of a multi‐legged stair‐climbing robot based on proprioceptive data

Purpose – The purpose of this paper is to describe an innovative compliance control architecture for hybrid multi‐legged robots. The approach was verified on the hybrid legged‐wheeled robot ASGUARD, which was inspired by quadruped animals. The adaptive compliance controller allows the system to cope with a variety of stairs, very rough terrain, and is also able to move with high velocity on flat ground without changing the control parameters. Design/methodology/approach – The paper shows how this adaptivity results in a versatile controller for hybrid legged‐wheeled robots. For the locomotion control we use an adaptive model of motion pattern generators. The control approach takes into account the proprioceptive information of the torques, which are applied on the legs. The controller itself is embedded on a FPGA‐based, custom designed motor control board. An additional proprioceptive inclination feedback is used to make the same controller more robust in terms of stair‐climbing capabilities. Findings – The robot is well suited for disaster mitigation as well as for urban search and rescue missions, where it is often necessary to place sensors or cameras into dangerous or inaccessible areas to get a better situation awareness for the rescue personnel, before they enter a possibly dangerous area. A rugged, waterproof and dust‐proof corpus and the ability to swim are additional features of the robot. Originality/value – Contrary to existing approaches, a pre‐defined walking pattern for stair‐climbing was not used, but an adaptive approach based only on internal sensor information. In contrast to many other walking pattern based robots, the direct proprioceptive feedback was used in order to modify the internal control loop, thus adapting the compliance of each leg on‐line.

Collaborative learning model of infrastructure construction: A capability perspective

Purpose Performance heterogeneity between collaborative infrastructure projects is typically examined by considering procurement systems and their governance mechanisms at static points in time. The literature neglects to consider the impact of dynamic learning capability, which is thought to reconfigure governance mechanisms over time in response to evolving market conditions. This conceptual paper proposes a new model to show how continuous joint learning of participant organisations improves project performance. Design/methodology/approach There are two stages of conceptual development. In the first stage, the management literature is analysed to explain the Standard Model of dynamic learning capability that emphasises three learning phases for organisations. This Standard Model is extended to derive a novel Circular Model of dynamic learning capability that shows a new feedback loop between performance and learning. In the second stage, the construction management literature is consulted, adding project lifecycle, stakeholder diversity and three organisational levels to the analysis, to arrive at the Collaborative Model of dynamic learning capability. Findings The Collaborative Model should enable construction organisations to successfully adapt and perform under changing market conditions. The complexity of learning cycles results in capabilities that are imperfectly imitable between organisations, explaining performance heterogeneity on projects. Originality/value The Collaborative Model provides a theoretically substantiated description of project performance, driven by the evolution of procurement systems and governance mechanisms. The Model’s empirical value will be tested in future research.