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Data model considerations in the manufacturing enterprise 制造企业中的数据模型注意事项
2021 Australian & New Zealand Control Conference (ANZCC) Pub Date : 2021-11-25 DOI: 10.1109/anzcc53563.2021.9628330
M. Lees
{"title":"Data model considerations in the manufacturing enterprise","authors":"M. Lees","doi":"10.1109/anzcc53563.2021.9628330","DOIUrl":"https://doi.org/10.1109/anzcc53563.2021.9628330","url":null,"abstract":"Data typically requires context or meaning in order to be of value. In an applied sense the context is often implemented in the form of a data model. Contemporary manufacturing environments rely on the use of data models both throughout their automation landscape as well as within most layers of business operations. Industry 4.0 (with a projected market spend of over US$150 billion by around 2026) relies heavily on the use of data models. The scale, complexity and level of integration of data models is set to increase markedly over the next phases of migration towards Industry 4.0.However the nature, location(s) and significance of data models are not always understood by many of the stakeholders within the enterprise. This can lead to decisions around system architecture, ownership and accountability that result in sub-optimal outcomes for the enterprise.This paper clarifies the nature and characteristics of data models in the manufacturing enterprise, providing a context and understanding for stakeholders and decision makers.","PeriodicalId":246687,"journal":{"name":"2021 Australian & New Zealand Control Conference (ANZCC)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128222793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Adaptive Inverse Control Synthesis Subject to Sinusoidal Disturbance for Non-Minimum Phase Plant via FVSS-NLMS Algorithm 基于FVSS-NLMS算法的非最小相位对象正弦扰动自适应逆控制综合
2021 Australian & New Zealand Control Conference (ANZCC) Pub Date : 2021-11-25 DOI: 10.1109/anzcc53563.2021.9628344
Rodrigo Possidônio Noronha
{"title":"Adaptive Inverse Control Synthesis Subject to Sinusoidal Disturbance for Non-Minimum Phase Plant via FVSS-NLMS Algorithm","authors":"Rodrigo Possidônio Noronha","doi":"10.1109/anzcc53563.2021.9628344","DOIUrl":"https://doi.org/10.1109/anzcc53563.2021.9628344","url":null,"abstract":"In this paper, an Adaptive Indirect Inverse Control (IAIC) methodology based on the Finite Impulse Response (FIR) Filter is proposed, such that the controller is represented by an adaptive FIR Filter. The estimate of the weights vector of FIR Filter can be performed through an adaptive algorithm based on stochastic gradient descent, such that the performance of IAIC is influenced by the performance of update of the weights vector, in terms of convergence speed and steady-state Mean Square Error (MSE), that, consequently, is influenced by the step size of an adaptive algorithm. Aiming to present a proposal to solve this problem, a new version of NLMS algorithm is proposed, with the adapted step size through Mamdani Fuzzy Inference System (MFIS). The proposed algorithm was evaluated in the IAIC syhnthesis and applied in non-minimum phase plant, in the presence of a sinusoidal disturbance signal added to the control signal.","PeriodicalId":246687,"journal":{"name":"2021 Australian & New Zealand Control Conference (ANZCC)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133895501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Monitoring of Froth Flotation with Transfer Learning and Principal Component Models* 基于迁移学习和主成分模型的泡沫浮选监测*
2021 Australian & New Zealand Control Conference (ANZCC) Pub Date : 2021-11-25 DOI: 10.1109/anzcc53563.2021.9628313
Xiu Liu, C. Aldrich
{"title":"Monitoring of Froth Flotation with Transfer Learning and Principal Component Models*","authors":"Xiu Liu, C. Aldrich","doi":"10.1109/anzcc53563.2021.9628313","DOIUrl":"https://doi.org/10.1109/anzcc53563.2021.9628313","url":null,"abstract":"Froth flotation is widely used in mineral processing to separate valuable mineral ores from gangue or waste material. As such, improved monitoring and control of flotation systems can have a significant impact on mineral processing efficiency. To this end, videographic monitoring of flotation cells is well established commercially to enable decision support in plant operations, but its application in automated monitoring and control is still emerging. In this paper, the incorporation of transfer learning with deep convolutional neural networks in traditional multivariate process monitoring is considered. It is shown that despite their high dimensionality, froth image features extracted with AlexNet provides better performance than achievable with traditional multivariate image methods.","PeriodicalId":246687,"journal":{"name":"2021 Australian & New Zealand Control Conference (ANZCC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114468675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Exponential Convergence in Voronoi-based Coverage Control 基于voronoi的覆盖控制的指数收敛性
2021 Australian & New Zealand Control Conference (ANZCC) Pub Date : 2021-11-25 DOI: 10.1109/anzcc53563.2021.9628220
J. Kennedy, P. Dower, Airlie Chapman
{"title":"Exponential Convergence in Voronoi-based Coverage Control","authors":"J. Kennedy, P. Dower, Airlie Chapman","doi":"10.1109/anzcc53563.2021.9628220","DOIUrl":"https://doi.org/10.1109/anzcc53563.2021.9628220","url":null,"abstract":"Controllers for distributing mobile agents to cover a desired region have become popular in the motion-coordination literature, including numerous variations on the problem. In most cases, coverage controllers target asymptotic stability, in the Lyapunov sense, to the centroids of Voronoi cells. The popular cost function used exhibits multiple local minima and maxima, and the problem of computing the global minimum is known to be NP-hard. This paper provides explicit definitions for the rate of convergence of the network utilising a distributed coverage controller. In addition, under an assumption of strong local convexity, we provide an alternate stability proof that shows the controller exhibits exponential stability to local minima. An example is provided to illustrate conditions which strong local convexity holds.","PeriodicalId":246687,"journal":{"name":"2021 Australian & New Zealand Control Conference (ANZCC)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123657740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Nonlinear Motion Control for Manoeuvring of an Underwater Vehicle 水下航行器操纵的非线性运动控制
2021 Australian & New Zealand Control Conference (ANZCC) Pub Date : 2021-11-25 DOI: 10.1109/anzcc53563.2021.9628391
Sharmila Kayastha, A. Fowler, A. Cameron
{"title":"Nonlinear Motion Control for Manoeuvring of an Underwater Vehicle","authors":"Sharmila Kayastha, A. Fowler, A. Cameron","doi":"10.1109/anzcc53563.2021.9628391","DOIUrl":"https://doi.org/10.1109/anzcc53563.2021.9628391","url":null,"abstract":"This paper provides a comparative study of nonlinear motion control techniques for a generic BB2 underwater vehicle. Two different nonlinear controllers, state feedback linearisation control and Nonlinear Model Predictive Control (NMPC), are developed to track defined manoeuvres of the vehicle. The highly nonlinear and coupled dynamics, system uncertainties and environmental disturbances of underwater vehicles make their control design difficult. This paper attempts to compensate these nonlinearities by applying the proposed nonlinear controllers. The primary objective of the proposed nonlinear controllers is to track the desired states of the BB2 vehicle effectively. The effectiveness of these proposed controllers are examined through numerical simulations. The simulation results of the proposed controllers are then compared and discussed. The simulation results show the effectiveness of the proposed controllers, which are essential for the safe operation of the BB2 underwater vehicle.","PeriodicalId":246687,"journal":{"name":"2021 Australian & New Zealand Control Conference (ANZCC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132899765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
A Path Planning Method for Video Camera Equipped UAVs Monitoring a Ground Area 装有摄像机的无人机监控地面区域的路径规划方法
2021 Australian & New Zealand Control Conference (ANZCC) Pub Date : 2021-11-25 DOI: 10.1109/anzcc53563.2021.9628286
Jian Zhang, Hailong Huang
{"title":"A Path Planning Method for Video Camera Equipped UAVs Monitoring a Ground Area","authors":"Jian Zhang, Hailong Huang","doi":"10.1109/anzcc53563.2021.9628286","DOIUrl":"https://doi.org/10.1109/anzcc53563.2021.9628286","url":null,"abstract":"Unmanned Aerial Vehicles (UAVs) have become the necessary tools for a wide range of activities including but not limited to real-time monitoring, surveillance, border patrolling, search and rescue, civilian, scientific and military missions, etc. Their advantage is unprecedented and irreplaceable especially in environments dangerous to humans, for example in radiation or pollution exposed areas. A method for occlusion-aware UAV path planning is presented in this paper, which ensures every point on the target ground area can be seen at least once in a complete surveillance circle. Besides, the geometrically complex environments with occlusions are considered in our research. Compared with many existing methods, we decompose this problem into a waypoint determination problem and an instance of the traveling salesman problem.","PeriodicalId":246687,"journal":{"name":"2021 Australian & New Zealand Control Conference (ANZCC)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124597315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Repetitive Control based Disturbance Observer for Uncertain Communication Delays 基于重复控制的不确定通信时延干扰观测器
2021 Australian & New Zealand Control Conference (ANZCC) Pub Date : 2021-11-25 DOI: 10.1109/anzcc53563.2021.9628298
Vickneswaran Artheec Kumar, Z. Cao, Deshan Thayabaran, Don Bombuwela
{"title":"Repetitive Control based Disturbance Observer for Uncertain Communication Delays","authors":"Vickneswaran Artheec Kumar, Z. Cao, Deshan Thayabaran, Don Bombuwela","doi":"10.1109/anzcc53563.2021.9628298","DOIUrl":"https://doi.org/10.1109/anzcc53563.2021.9628298","url":null,"abstract":"In control systems, uncertain delays are unavoidable in communication channels. Further, the requirement to track and reject periodic signals has many applications in engineering. However, in most cases disturbances to be compensated are not just periodic but can also be aperiodic. This paper presents a novel Repetitive controller based disturbance observer (RCDOB) to reject both periodic and aperiodic disturbances while being able to track periodic signals in systems with uncertain communication delays.","PeriodicalId":246687,"journal":{"name":"2021 Australian & New Zealand Control Conference (ANZCC)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124685541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Effect of increased number of COVID-19 tests using supervised machine learning models 使用监督机器学习模型增加COVID-19测试数量的影响
2021 Australian & New Zealand Control Conference (ANZCC) Pub Date : 2021-11-25 DOI: 10.1109/anzcc53563.2021.9628387
W. Pooja, N. Snehal, K. Sonam, S. Wagh, Navdeep M. Singh
{"title":"Effect of increased number of COVID-19 tests using supervised machine learning models","authors":"W. Pooja, N. Snehal, K. Sonam, S. Wagh, Navdeep M. Singh","doi":"10.1109/anzcc53563.2021.9628387","DOIUrl":"https://doi.org/10.1109/anzcc53563.2021.9628387","url":null,"abstract":"Machine learning is widely being used in medical field for disease diagnostics and research.The area of machine learning is mainly classified into 3 parts: supervised, unsupervised and reinforcement learning.Supervised machine learning (ML) algorithms are used in this paper for modeling and showing the impact of increased testing on the number of daily confirmed cases of COVID-19. The algorithms used to carry out this study are decision tree regression and random forest regression. Machine learning for modeling has proven to be significant for forecasting and hence decision making over the future course of actions. In this paper, Gaussian process regression has been used for modeling as well as forecasting the daily confirmed cases in South Korea. The results obtained show that if the number of tests conducted is increased to the population of South Korea, approximately equal to 51, 286, 183, the peak in the daily cases is obtained earlier and hence the overall number of daily cases is less compared to current cases.","PeriodicalId":246687,"journal":{"name":"2021 Australian & New Zealand Control Conference (ANZCC)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115261313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Optimising Wavefront Sensing Super-Resolution in the Control of Tomographic Adaptive Optics 层析自适应光学控制中的波前传感超分辨率优化
2021 Australian & New Zealand Control Conference (ANZCC) Pub Date : 2021-11-25 DOI: 10.1109/anzcc53563.2021.9628305
Jesse Cranney, Angus Guihot, J. Doná, F. Rigaut
{"title":"Optimising Wavefront Sensing Super-Resolution in the Control of Tomographic Adaptive Optics","authors":"Jesse Cranney, Angus Guihot, J. Doná, F. Rigaut","doi":"10.1109/anzcc53563.2021.9628305","DOIUrl":"https://doi.org/10.1109/anzcc53563.2021.9628305","url":null,"abstract":"In this work we propose to explore and optimise a novel concept in adaptive optics wavefront sensing. The notion being investigated is that of super-resolution, which is aimed at increasing spatial resolution in tomographic adaptive optics by introducing diversity in the alignment of different wavefront sensors. The optimisation of super-resolution requires efficient computation of the wavefront estimation error. A model of the wavefront sensor compatible with super-resolution is proposed in this paper, together with a suitable cost function to optimise the super-resolution geometry. We provide initial optimisation results verified by end-to-end simulations. In future work we will investigate the parallelisation of the optimisation routine, and alternative optimisation methods.","PeriodicalId":246687,"journal":{"name":"2021 Australian & New Zealand Control Conference (ANZCC)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116711089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Social Shaping of Linear Quadratic Multi-Agent Systems 线性二次型多智能体系统的社会塑造
2021 Australian & New Zealand Control Conference (ANZCC) Pub Date : 2021-11-25 DOI: 10.1109/anzcc53563.2021.9628389
Z. Salehi, Yijun Chen, E. Ratnam, I. Petersen, Guodong Shi
{"title":"Social Shaping of Linear Quadratic Multi-Agent Systems","authors":"Z. Salehi, Yijun Chen, E. Ratnam, I. Petersen, Guodong Shi","doi":"10.1109/anzcc53563.2021.9628389","DOIUrl":"https://doi.org/10.1109/anzcc53563.2021.9628389","url":null,"abstract":"In this paper, we study multi-agent systems with distributed resource allocation at individual agents. The agents make local resource allocation decisions including, in some cases, trading decisions — incurring income or expenditure subject to the resource price and system-level resource availability. The agents seek to maximize their individual payoffs, which accrue from both resource allocation income and expenditure. We define a social shaping problem for the system and show that the optimal price is always below a prescribed socially resilient price threshold. By exploring optimality conditions for each agent, we express resource allocation decisions in terms of piece-wise linear functions with respect to the price for unit resource. We further establish a tight range for the coefficients of the linear-quadratic utilities, under which optimal pricing is proven to be always socially resilient.","PeriodicalId":246687,"journal":{"name":"2021 Australian & New Zealand Control Conference (ANZCC)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115603453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
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