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2021 Australian & New Zealand Control Conference (ANZCC)最新文献

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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
Pub Date : 2021-11-25 DOI: 10.1109/anzcc53563.2021.9628330
M. Lees
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.
数据通常需要上下文或含义才能有价值。在应用意义上,上下文通常以数据模型的形式实现。现代制造环境依赖于数据模型的使用,无论是在整个自动化环境中,还是在大多数业务操作层中。工业4.0(预计到2026年左右市场支出将超过1500亿美元)严重依赖于数据模型的使用。在向工业4.0迁移的下一个阶段,数据模型的规模、复杂性和集成水平将显著提高。然而,数据模型的性质、位置和重要性并不总是被企业中的许多涉众所理解。这可能导致围绕系统架构、所有权和责任的决策,从而导致企业的次优结果。本文阐明了制造企业中数据模型的性质和特征,为利益相关者和决策者提供了一个背景和理解。
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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
Pub Date : 2021-11-25 DOI: 10.1109/anzcc53563.2021.9628344
Rodrigo Possidônio Noronha
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.
本文提出了一种基于有限脉冲响应(FIR)滤波器的自适应间接逆控制(IAIC)方法,使控制器由自适应FIR滤波器表示。FIR滤波器权向量的估计可以通过基于随机梯度下降的自适应算法来实现,因此IAIC的性能受到权向量更新性能的影响,在收敛速度和稳态均方误差(MSE)方面,从而受到自适应算法步长的影响。为了解决这一问题,本文提出了一种新的NLMS算法,该算法通过Mamdani模糊推理系统(MFIS)调整步长。在IAIC合成中对该算法进行了验证,并将其应用于控制信号中加入正弦干扰信号的非最小相位对象。
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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*
Pub Date : 2021-11-25 DOI: 10.1109/anzcc53563.2021.9628313
Xiu Liu, C. Aldrich
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.
泡沫浮选在选矿中广泛应用于从脉石或废料中分离有价矿物。因此,改善浮选系统的监测和控制可以对选矿效率产生重大影响。为此目的,浮选池的录像监测已在商业上得到很好的建立,以便在工厂作业中支持决策,但其在自动化监测和控制方面的应用仍在出现。本文将迁移学习与深度卷积神经网络结合到传统的多变量过程监测中。研究表明,尽管泡沫图像特征具有高维数,但用AlexNet提取的泡沫图像特征比传统的多元图像方法提供了更好的性能。
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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
Pub Date : 2021-11-25 DOI: 10.1109/anzcc53563.2021.9628220
J. Kennedy, P. Dower, Airlie Chapman
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.
用于分配移动代理以覆盖所需区域的控制器在运动协调文献中已经变得流行,包括对该问题的许多变体。在大多数情况下,覆盖控制器将Lyapunov意义上的渐近稳定性目标定位于Voronoi细胞的质心。常用的代价函数具有多个局部最小值和最大值,而计算全局最小值的问题是np困难的。本文给出了使用分布式覆盖控制器的网络收敛速率的明确定义。此外,在强局部凸性的假设下,给出了控制器对局部极小值具有指数稳定性的交替稳定性证明。给出了一个例子来说明强局部凸性成立的条件。
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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
Pub Date : 2021-11-25 DOI: 10.1109/anzcc53563.2021.9628391
Sharmila Kayastha, A. Fowler, A. Cameron
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.
本文对通用BB2型水下航行器的非线性运动控制技术进行了比较研究。开发了两种不同的非线性控制器,状态反馈线性化控制和非线性模型预测控制(NMPC),以跟踪车辆的定义动作。水下航行器的高度非线性和耦合动力学、系统不确定性和环境扰动给其控制设计带来了困难。本文试图利用所提出的非线性控制器来补偿这些非线性。所提出的非线性控制器的主要目标是有效地跟踪BB2车辆的期望状态。通过数值仿真验证了所提控制器的有效性。对所提控制器的仿真结果进行了比较和讨论。仿真结果表明了所提控制器的有效性,对BB2水下机器人的安全运行至关重要。
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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
Pub Date : 2021-11-25 DOI: 10.1109/anzcc53563.2021.9628286
Jian Zhang, Hailong Huang
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.
无人机已成为包括但不限于实时监控、监视、边境巡逻、搜救、民用、科学和军事任务等广泛活动的必要工具。它们的优势是前所未有和不可替代的,特别是在对人类有危险的环境中,例如在辐射或污染暴露地区。提出了一种基于遮挡感知的无人机路径规划方法,该方法能保证目标地面上的每个点在一个完整的监视圈内至少被看到一次。此外,我们的研究还考虑了具有遮挡的几何复杂环境。与现有的许多方法相比,我们将该问题分解为一个路点确定问题和一个旅行商问题的实例。
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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
Pub Date : 2021-11-25 DOI: 10.1109/anzcc53563.2021.9628298
Vickneswaran Artheec Kumar, Z. Cao, Deshan Thayabaran, Don Bombuwela
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.
在控制系统中,通信信道中的不确定性延迟是不可避免的。此外,跟踪和抑制周期信号的要求在工程中有许多应用。然而,在大多数情况下,要补偿的干扰不仅是周期性的,也可以是非周期性的。本文提出了一种新的基于重复控制器的干扰观测器(RCDOB),它既能抑制周期和非周期干扰,又能在具有不确定通信延迟的系统中跟踪周期信号。
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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
Pub Date : 2021-11-25 DOI: 10.1109/anzcc53563.2021.9628387
W. Pooja, N. Snehal, K. Sonam, S. Wagh, Navdeep M. Singh
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.
机器学习在医学领域被广泛应用于疾病诊断和研究。机器学习领域主要分为监督学习、无监督学习和强化学习三部分。本文使用监督机器学习(ML)算法进行建模,并显示增加测试对每日COVID-19确诊病例数量的影响。进行本研究使用的算法是决策树回归和随机森林回归。用于建模的机器学习已被证明对预测和未来行动过程的决策非常重要。本文采用高斯过程回归对韩国每日确诊病例进行建模和预测。结果表明,如果对韩国人口进行检测的数量增加,大约等于51,286,183,则每日病例的高峰将提前出现,因此每日病例总数与目前的病例相比较少。
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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
Pub Date : 2021-11-25 DOI: 10.1109/anzcc53563.2021.9628305
Jesse Cranney, Angus Guihot, J. Doná, F. Rigaut
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.
在这项工作中,我们提出探索和优化自适应光学波前传感的新概念。正在研究的概念是超分辨率,其目的是通过引入不同波前传感器的多样性来提高层析自适应光学的空间分辨率。超分辨率的优化需要有效地计算波前估计误差。本文提出了一种兼容超分辨率的波前传感器模型,并提出了合适的成本函数来优化超分辨率几何结构。我们提供了通过端到端模拟验证的初始优化结果。在未来的工作中,我们将研究优化例程的并行化和替代优化方法。
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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
Pub Date : 2021-11-25 DOI: 10.1109/anzcc53563.2021.9628389
Z. Salehi, Yijun Chen, E. Ratnam, I. Petersen, Guodong Shi
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.
本文研究了在单个智能体上分配资源的多智能体系统。代理做出本地资源分配决策,在某些情况下,包括交易决策——根据资源价格和系统级资源可用性产生收入或支出。代理人寻求从资源分配收入和支出中获得的个人收益最大化。我们定义了系统的社会塑造问题,并表明最优价格总是低于规定的社会弹性价格阈值。通过探索每个智能体的最优性条件,我们用关于单位资源价格的分段线性函数来表达资源分配决策。我们进一步建立了线性二次效用系数的窄范围,在此范围内,最优定价始终具有社会弹性。
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引用次数: 4
期刊
2021 Australian & New Zealand Control Conference (ANZCC)
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