Massey Documents by Type

Permanent URI for this communityhttps://mro.massey.ac.nz/handle/10179/294

Browse

Subject: search.filters.subject.Adaptive control systems

Search Results

Now showing 1 - 4 of 4
  • Thumbnail Image
    Item
    Non-RSSI based energy efficient transmission power control protocol for low power indoor wireless sensor networks : a thesis presented in partial fulfilment of the requirements for the degree of PhD in Engineering at Massey University, Palmerston North, New Zealand
    (Massey University, 2016) Basu, Debraj
    In this thesis, we present the state-based adaptive power control (S-APC) protocol that is aimed to reduce energy consumption in low power wireless sensors while maintaining an application specific packet success rate requirement. The state-based approach is unique of its kind that dynamically adapt to the varying path losses caused by the movement of mobile sensors, by obstructions appearing between the stationary sensor and the base-station and movements of objects or humans in between two communicating stations. Since the primary reason for a drop in transmitted packets is the poor signal-to-noise ratio, it is important for the sensor to select a set of RF transmission power levels that will deliver the packets within a specified error rate while using the least amount of energy. In a battery-powered wireless sensor node, the use of ARQ (Automatic Repeat reQuest) protocol will lead to retransmissions when an attempt to send a packet fails. The proposed adaptive protocol does not use received signal strength indication (RSSI) based beacon or probe packets nor does it listen to the channel before transmitting for channel estimation. The use of the proposed S-APC protocol is not limited to only sensor network. It is applicable to any kind of radio communication when the transmitting radio frequency (RF) modules have configurable output power and options for retransmission. This proposed protocol can comfortably work on top of existing MAC protocol that is contention based and listens to channel before transmitting. The hardware used for evaluating the protocol parameters is the nRF24L01p transceiver module from Nordic Semiconductor Inc. This radio module is cheaper than other modules that provide the RSSI values to the chip and the application of the adaptive power control protocol can further reduce the overall deployment and running cost of a sensor network. The proposed protocol is designed to respond to an unknown and variable radio channel in an energy-efficient manner. The adaptive protocol uses past transmission experience or memory to decide the power level at which the new packet transmission will start. It also uses a drop-off algorithm to ramp down power level as and when required. Simulation has been used to compare the performance with the existing RSSI and non-RSSI based adaptive power control protocol. Results have shown that when the channel condition is between average and poor (ratio of bit energy (Eb) and noise power spectral density (N0) is less than 20 dB), the RSSI based adaptive protocol consumes 10-20% more energy. Following the simulations, exhaustive experimental trials were done to compare S-APC with the existing protocols. It was found that there can be an increase of energy efficiency up-to 33% over fixed power transmission. This protocol could be applied in mobile robots that collect data in real time from sensors and transmit to the base station as well as to body wearable sensors used for monitoring the health conditions of patients in a health facility centre. Overall, this adaptive protocol can be used in radio communication where the channel has dynamic temporal and spatial characteristics to enhance the lifetime of battery powered wireless sensors.
  • Thumbnail Image
    Item
    Optimised dynamic motion control of near spherical objects : a thesis presented in the partial fulfilment of the requirements for the degree of PhD in Engineering at Massey University, Palmerston North, New Zealand
    (Massey University, 2013) Edmondson, Michael Charles
    This research investigates the development of an automated packing machine for a New Zealand Industrial Company (NZIC). NZIC is a leading international manufacturer that produces automated equipment for a labour intensive industry. The proposed system aims to solve the complex packing of near spherical objects (OBJ) which is currently the most labour intensive task. A review of the existing full or partially autonomous systems has identified multiple units that have attempted to remove human labour from relevant or simplified versions of the task. Three areas are identified as requiring in-depth investigation and this research sets out to investigate these issues and propose possible solutions. One failing aspect of the existing systems is the apparent lack of prior analysis on how such a machine would deliver on commercial requirements. This research made an indepth motion analysis on possible automated solutions and laid the foundation for engineering development.
  • Thumbnail Image
    Item
    A distributed shop floor control system based on the principles of heterarchical control and multi agent paradigm : a dissertation presented in partial fulfilment of the requirements for a PhD degree in Production Technology - Computer Integrated Manufacturing (CIM) Systems at Massey University
    (Massey University, 2004) Colak, Goran D
    In progressive firms, major efforts are underway to reduce the time to design, manufacture, and deliver products. The programs have a variety of objectives, from reducing lead-time to increasing product quality. The process of improvement starts with customer requirements, which in turn lead to customer-driven manufacturing, incorporating customer requirements more directly into the manufacturing processes. Forecasting customer requirements has not become any easier, in fact, just the contrary. The implication is clear: that if demands cannot be forecast, the manufacturing function must be designed to respond to these demands. To do this rapidly, more and more of the manufacturing decisions are being delegated to the factory floor. To paraphrase; the customer is saying what is to be made, the due date is now, and the work force is figuring out how to do it online. As the manufacturing world moves toward the "zero everything" vision of the future (zero inventory, zero set-up time, zero defects, zero waste), fundamental changes will take place in the factory. These changes will necessitate changes in manufacturing planning and control systems and particularly changes in planning and control on the shop floor level. This dissertation addresses the possible direction that some of these changes might take on the shop floor. The starting preamble of this research is that forecasting in certain type of manufacturing systems is not possible. An example might be systems in which product orders arrive randomly, such as manufacturing facilities involved in production of replacement spare parts). Additionally, in many other manufacturing systems, forecasting generates results that are of a very low level of certainty. In many occasions they are practically useless, since they are applicable only for short time horizons. As an example, small-quantity batch manufacturing systems usually operate under conditions where frequent disturbances make this production unstable at all times. Therefore, addressing these systems, the main idea embodied in this dissertation could be expressed as follows: "Instead of focusing efforts on how to improve the old, or develop new methods for controlling material flows in manufacturing systems, methods that are solely based on the main premise of predicting the future circumstances, this research takes another course. It considers an alternative approach - developing of manufacturing control mechanisms that are "more reactive" to the changes in the systems and "less dependant on prediction" of future events. It is believed that the modern job shop manufacturing facilities, such as mentioned above, can further increase their competitiveness by adopting approaches for shop floor control systems that are discussed in this research study. This is because the proposed system is capable, both dynamically and in real time, of promptly responding to frequent changes in production conditions, always attempting to find the best possible solution for given circumstances.
  • Thumbnail Image
    Item
    Applying Matsuoka Neuronal Oscillator in traffic light control of intersections : a thesis presented in partial fulfillment of the requirements of the degree of Master of Engineering in Mechatronics at Massey University, Auckland, New Zealand
    (Massey University, 2009) Lin, Kuo-Chun
    The quality of Machine Translation (MT) can often be poor due to it appearing incoherent and lacking in fluency. These problems consist of word ordering, awkward use of words and grammar, and translating text too literally. However we should not consider translations such as these failures until we have done our best to enhance their quality, or more simply, their fluency. In the same way various processes can be applied to touch up a photograph, various processes can also be applied to touch up a translation. This research outlines the improvement of MT quality through the application of Fluency Enhancement (FE), which is a process we have created that reforms and evaluates text to enhance its fluency. We have tested our FE process on our own MT system which operates on what we call the SAM fundamentals, which are as follows: Simplicity - to be simple in design in order to be portable across different languages pairs, Adaptability - to compensate for the evolution of language, and Multiplicity - to determine a final set of translations from as many candidate translations as possible. Based on our research, the SAM fundamentals are the key to developing a successful MT system, and are what have piloted the success of our FE process.