20,946 research outputs found

    Integrated sensor and controller framework : a thesis presented in partial fulfilment of the requirements for the degree of Master of Engineering in Information and Telecommunications Engineering at Massey University, Palmerston North, New Zealand

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    This thesis presents a software platform to integrate sensors, controllers, actuators and instrumentation within a common framework. This provides a flexible, reusable, reconfigurable and sealable system for designers to use as a base for any sensing and control platform. The purpose of the framework is to decrease system development time, and allow more time to be spent on designing the control algorithms, rather than implementing the system. The architecture is generic, and finds application in many areas such as home, office and factory automation, process and environmental monitoring, surveillance and robotics. The framework uses a data driven design, which separates the data storage areas (dataslots) from the components of the framework that process the data (processors). By separating all the components of the framework in this way, it allows a flexible configuration. When a processor places data into a dataslot, the dataslot queues all the processors that use that data to run. A system that is based on this framework is configured by a text file. All the components are defined in the file, with the interactions between them. The system can be thought of as multiple boxes, with the text file defining how these boxes are connected together. This allows rapid configuration of the system, as separate text files can be maintained for different configurations. A text file is used for the configuration instead of a graphical environment to simplify the development process, and to reduce development time. One potential limitation of the approach of separating the computational components is an increased overhead or latency. It is acknowledged that this is an important consideration in many control applications, so the framework is designed to minimise the latency through implementation of prioritized queues and multitasking. This prevents one slow component from degrading the performance of the rest of the system. The operation of the framework is demonstrated through a range of different applications. These show some of the key features including: acquiring data, handling multiple dataslots that a processor reads from or writes to, controlling actuators, how the virtual instrumentation works, network communications, where controllers fit into the framework, data logging, image and video dataslots. timers and dynamically linked libraries. A number of experiments show the framework under real conditions. The framework's data passing mechanisms are demonstrated, a simple control and data logging application is shown and an image processing application is shown to demonstrate the system under load. The latency of the framework is also determined. These illustrate how the framework would operate under different hardware and software applications. Work can still be done on the framework, as extra features can be added to improve the usability. Overall, this thesis presents a flexible system to integrate sensors, actuators, instrumentation and controllers that can be utilised in a wide range of applications

    Design and development of a modular framework to integrate sensors and actuators : a thesis presented in partial fulfilment of the requirements for the degree of Masters of Engineering in Mechatronics at Massey University, Manawatu, New Zealand

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    This thesis details the research and development of a versatile electronic monitoring and control platform, influenced by the Internet of Things (IoT), mass configurability, modularity, expandability and ease of use. The generic framework which has been designed and tested aims to provide a platform to build a wide variety of specialised systems to integrate sensors and actuators. A central processing unit manages modular hardware devices connected by a serial network. Only the required hardware units are chosen to constitute a system for an application. The processing unit uses modular task handlers to manage the system. The web-based user interface provides multi-platform system access using a web browser. The website is dynamically generated from the system configuration. While the framework is generic, for testing its efficacy, it was applied to a seed and fertilizer spreader to monitor and control the application rate. This application requires coordinated control of actuators using inputs from multiple sources, including sensors, machine states, a database, other processing tasks, and the operator. The implementation was successful in achieving reliable control of the seeding rate, based on the tractor ground speed. The practical implementation exhibited a high level of expandability and modularity. The prototype system has also highlighted a few issues which can be addressed in future revisions to improve the versatility and robustness of the framework

    Concurrent Design of Embedded Control Software

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    Embedded software design for mechatronic systems is becoming an increasingly time-consuming and error-prone task. In order to cope with the heterogeneity and complexity, a systematic model-driven design approach is needed, where several parts of the system can be designed concurrently. There is however a trade-off between concurrency efficiency and integration efficiency. In this paper, we present a case study on the development of the embedded control software for a real-world mechatronic system in order to evaluate how we can integrate concurrent and largely independent designed embedded system software parts in an efficient way. The case study was executed using our embedded control system design methodology which employs a concurrent systematic model-based design approach that ensures a concurrent design process, while it still allows a fast integration phase by using automatic code synthesis. The result was a predictable concurrently designed embedded software realization with a short integration time
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