检索结果-内蒙古大学图书馆

Beta Residuals: Improving Fault-Tolerant control for Sensory Faults via Bayesian Inference and Precision Learning

IFAC-PapersOnLine 2022年第6期55卷 285-291页

作者： Mohamed Baioumy William Hartemink Riccardo M.G. Ferrari Nick Hawes Oxford Robotics Institute University of Oxford United Kingdom Amazon Web Services Texas United States Delft Center for Systems and Control Delft University of Technology Mekelweg 2 2628 CD Delft The Netherlands

Model-based fault-tolerant control (FTC) often consists of two distinct steps: fault detection & isolation (FDI), and fault accommodation. In this work we investigate posing fault-tolerant control as a single Bayesian inference problem. Previous work showed that precision learning allows for stochastic FTC without an explicit fault detection step. While this leads to implicit fault recovery, information on sensor faults is not provided, which may be essential for triggering other impact-mitigation actions. In this paper, we introduce a precision-learning based Bayesian FTC approach and a novel beta residual for fault detection. Simulation results are presented, supporting the use of beta residual against competing approaches.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Evolutionary Neural Architecture Search with Semi-supervised Accuracy Predictor

Evolutionary Neural Architecture Search with Semi-supervised...

引用

International Conference on control and Robots (ICCR)

作者： Songyi Xiao Bo Zhao Derong Liu School of Automation Guangdong University of Technology Guangzhou China School of Systems Science Beijing Normal University Beijing China Institute of Control Science and Technology Southern Unversity of Science and Technology Shenzhen China

Neural architecture search (NAS) has low efficiency in evaluating a large number of candidate architectures. As an efficient evaluation method, accuracy predictor-based NAS algorithms have become popular because the performance (accuracy) can be evaluated without training the candidate architectures. However, accuracy predictors still need some evaluated architectures that are difficult to train for achieving promising performance. In order to break this bottleneck, we investigate a semi-supervised accuracy predictor-based evolutionary NAS method (MSNAS) which requires only a small number of evaluated neural architectures. The accuracy predictor obtains high prediction performance by extracting the evaluated architectures, strong regressors and truncation mechanism. To find truly high-accuracy candidate architectures more easily, the multi-objective optimization method is presented to trade-off the prediction accuracy and confidence of candidate architectures. The MSNAS variants from different strong regressors are employed to validate the competitive performance of the MSNAS on NAS-Bench 201.

关键词： Training Radio frequency Optimization methods Predictive models Aerospace electronics Prediction algorithms Robots

来源：评论

学校读者我要写书评

暂无评论

Convergence Analysis of the Best Response Algorithm for Time-Varying Games

Convergence Analysis of the Best Response Algorithm for Time...

引用

IEEE Conference on Decision and control

作者： Zifan Wang Yi Shen Michael M. Zavlanos Karl H. Johansson Division of Decision and Control Systems School of Electrical Enginnering and Computer Science KTH Royal Institute of Technology and also with Digital Futures Stockholm Sweden Department of Mechanical Engineering and Materials Science Duke University Durham NC USA

This paper studies a class of strongly monotone games involving non-cooperative agents that optimize their own time-varying cost functions. We assume that the agents can observe other agents' historical actions and choose actions that best respond to other agents' previous actions; we call this a best response scheme. We start by analyzing the convergence rate of this best response scheme for standard time-invariant games. Specifically, we provide a sufficient condition on the strong monotonicity parameter of the time-invariant games under which the proposed best response algorithm achieves exponential convergence to the static Nash equilibrium. We further illustrate that this best response algorithm may oscillate when the proposed sufficient condition fails to hold, which indicates that this condition is tight. Next, we analyze this best response algorithm for time-varying games where the cost functions of each agent change over time. Under similar conditions as for time-invariant games, we show that the proposed best response algorithm stays asymptotically close to the evolving equilibrium. We do so by analyzing both the equilibrium tracking error and the dynamic regret. Numerical experiments on economic market problems are presented to validate our analysis.

关键词：

来源：评论

学校读者我要写书评

暂无评论

YUCML-An usage control policy language for end-to-end data sharing

YUCML-An usage control policy language for end-to-end data s...

引用

Cyber-Physical Social Intelligence (ICCSI), International Conference on

作者： Chao Li Junjian Li Ruoyu Wang Ran Li Chonghua Wang Cyberspace Institute of Advanced Technology(CIAT) Guangzhou University Guangzhou China School of Artificial Intelligence Guangdong Mechanical and Electrical Polytechnic Guangzhou China China Industrial Control Systems Cyber Emergency Response Team Guangzhou China

In today’s interconnected world, securely sharing data between devices and systems is crucial. End-to-end big data sharing enables seamless communication and collaboration, but also presents data security and control challenges. To ensure data confidentiality and integrity, data usage control is important. We designed a control policy language to provide a unified way to describe data usage control policies. The language can embed common scripting languages for policy description and can describe policy rules for various access control models like ABAC and RBAC, as well as data usage obligations and conditions. By separating the policy description model rules and embedding them in the data, only a small set of rules needs to be transmitted for data using the same policy model, without retransmit data usage policies. We implemented a policy engine on Linux. Experiments show its transmission and storage overhead is reduced by 90% compared to directly attaching XACML to data.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Optimal Strategies Trajectory with Multi-Local-Worlds Graph

引用

Computers, Materials & Continua 2023年第4期75卷 2079-2099页

作者： Xiang Yu Chonghua Wang Xiaojing Zheng Chaoyu Zeng Brij BGupta School of Electronics and Information Engineering Taizhou UniversityTaizhouZhejiang318000China China Industrial Control Systems Cyber Emergency Response Team Beijing100040China School of Economics and Management Weifang University of Science and TechnologyShouguangShandong262700China National Computer System Engineering Research Institute of China Beijing102699China Department of Computer Science and Information Engineering Asia UniversityTaiwanTaichung413China Research and Innovation Department Skyline University CollegeSharjahP.O.Box 1797United Arab Emirates Staffordshire University Stoke-on-TrentST42DEUK

This paper constructs a non-cooperative/cooperative stochasticdifferential game model to prove that the optimal strategies trajectory ofagents in a system with a topological configuration of a Multi-Local-Worldgraph would converge into a certain attractor if the system’s configuration isfixed. Due to the economics and management property, almost all systems aredivided into several independent Local-Worlds, and the interaction betweenagents in the system is more complex. The interaction between agents inthe same Local-World is defined as a stochastic differential cooperativegame;conversely, the interaction between agents in different Local-Worldsis defined as a stochastic differential non-cooperative game. We construct anon-cooperative/cooperative stochastic differential game model to describethe interaction between agents. The solutions of the cooperative and noncooperativegames are obtained by invoking corresponding theories, and thena nonlinear operator is constructed to couple these two solutions *** last, the optimal strategies trajectory of agents in the system is proven toconverge into a certain attractor, which means that strategies trajectory arecertainty as time tends to infinity or a large positive integer. It is concluded thatthe optimal strategy trajectory with a nonlinear operator of cooperative/noncooperativestochastic differential game between agents can make agentsin a certain Local-World coordinate and make the Local-World paymentmaximize, and can make the all Local-Worlds equilibrated;furthermore, theoptimal strategy of the coupled game can converge into a particular attractorthat decides the optimal property.

关键词： Multi-Local-world graph stochastic differential game optimal strategy attractor

来源：评论

学校读者我要写书评

暂无评论

LSBO-NAS: Latent Space Bayesian Optimization for Neural Architecture Search

LSBO-NAS: Latent Space Bayesian Optimization for Neural Arch...

引用

International Conference on control and Robots (ICCR)

作者： Xuan Rao Songyi Xiao Jiaxin Li Qiuye Wu Bo Zhao Derong Liu School of Automation Guangdong University of Technology Guangzhou China School of Systems Science Beijing Normal University Beijing China Institute of Control Science and Technology Southern University of Science and Technology Shenzhen China

From the perspective of data stream, neural architecture search (NAS) can be formulated as a graph optimization problem. However, many state-of-the-art black-box optimization algorithms, such as Bayesian optimization and simulated annealing, operate in continuous space primarily, which does not match the NAS optimization due to the discreteness of graph structures. To tackle this problem, the latent space Bayesian optimization NAS (LSBO-NAS) algorithm is developed in this paper. In LSBO-NAS, the neural architectures are represented as sequences, and a variational auto-encoder (VAE) is trained to convert the discrete search space of NAS into a continuous latent space by learning the continuous representation of neural architectures. Hereafter, a Bayesian optimization (BO) algorithm, i.e., the tree-structure parzen estimator (TPE) algorithm, is developed to obtain admirable neural architectures. The optimization loop of LSBO-NAS consists of two stages. In the first stage, the BO algorithm generates a preferable architecture representation according to its search strategy. In the second stage, the decoder of VAE decodes the representation into a discrete neural architecture, whose performance evaluation is regarded as the feedback signal for the BO algorithm. The effectiveness of the developed LSBO-NAS is demonstrated on the NAS-Bench-301 benchmark, where the LSBO-NAS achieves a better performance than several NAS baselines.

关键词： Representation learning Performance evaluation Closed box Simulated annealing Benchmark testing Search problems Bayes methods

来源：评论

学校读者我要写书评

暂无评论

Risk-Sensitive Inhibitory control for Safe Reinforcement Learning

Risk-Sensitive Inhibitory Control for Safe Reinforcement Lea...

引用

IEEE Conference on Decision and control

作者： Armin Lederer Erfaun Noorani John S. Baras Sandra Hirche Chair of Information-oriented Control (ITR) School of Computation Information and Technology Technical University of Munich Munich Germany Department of Electrical and Computer Engineering Institute for Systems Research (ISR) at the University of Maryland College Park MD USA

Humans have the ability to deviate from their natural behavior when necessary, which is a cognitive process called response inhibition. Similar approaches have independently received increasing attention in recent years for ensuring the safety of control. Realized using control barrier functions or predictive safety filters, these approaches can effectively ensure the satisfaction of state constraints through an online adaptation of nominal control laws, e.g., obtained through reinforcement learning. While the focus of these realizations of inhibitory control has been on risk-neutral formulations, human studies have shown a tight link between response inhibition and risk attitude. Inspired by this insight, we propose a flexible, risk-sensitive method for inhibitory control. Our method is based on a risk-aware condition for value functions, which guarantees the satisfaction of state constraints. We propose a method for learning these value functions using common techniques from reinforcement learning and derive sufficient conditions for its success. By enforcing the derived safety conditions online using the learned value function, risk-sensitive inhibitory control is effectively achieved. The effectiveness of the developed control scheme is demonstrated in simulations.

关键词：

来源：评论

学校读者我要写书评

暂无评论

On state-space representations of general discrete-time dynamical systems

arXiv

引用

arXiv 2022年

作者： Rojas, Cristian R. Wachel, Pawel The School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm100 44 Sweden The Department of Control Systems and Mechatronics Wroclaw University of Science and Technology Wroclaw Poland

In this paper we establish that every (deterministic) non-autonomous, discrete-time, causal, time invariant system has a state-space representation, and discuss its minimality. Copyright © 2022, The Authors. All ... 详细信息

关键词： Nonlinear dynamical systems

来源：评论

学校读者我要写书评

暂无评论

Asymptotic Observers for Heterogeneous Reaction systems using the Concepts of Reaction and Mass-transfer Extents

Asymptotic Observers for Heterogeneous Reaction Systems usin...

引用

control Conference (ICC), 2019 Sixth Indian

作者： Nirav Bhatt Department of Biotechnology Bhupat and Jyoti Mehta School of Biosciences and prospective Centre of Excellence for Network Systems Learning Control and Evolution Indian Institute of Technology Madras India

For reaction systems, the state variables (the number of moles) can be expressed using the concepts of extents of reaction and mass transfer for homogeneous and heterogeneous reaction systems. In this work, a general framework for designing asymptotic observers for homogeneous and gas-liquid reaction systems is presented using the concept of the extents. For gas-liquid reaction systems, it is shown that asymptotic observers can be designed using measurements in the gas-phase. The effect of noisy measurements on the estimation of unmeasured concentrations is also discussed. The proposed asymptotic observer approach is illustrated using an example of the chlorination of butanoic acid (gas-liquid reaction system).

关键词： Phase measurement Liquids Ethanol Estimation Observers Noise measurement

来源：评论

学校读者我要写书评

暂无评论

Comparative Analysis of Interval Reachability for Robust Implicit and Feedforward Neural Networks

arXiv

引用

arXiv 2022年

作者： Davydov, Alexander Jafarpour, Saber Abate, Matthew Bullo, Francesco Coogan, Samuel The Center for Control Dynamical Systems and Computation University of California Santa Barbara United States The School of Electrical and Computer Engineering Georgia Institute of Technology United States

We use interval reachability analysis to obtain robustness guarantees for implicit neural networks (INNs). INNs are a class of implicit learning models that use implicit equations as layers and have been shown to exhibit several notable benefits over traditional deep neural networks. We first establish that tight inclusion functions of neural networks, which provide the tightest rectangular over-approximation of an input-output map, lead to sharper robustness guarantees than the well-studied robustness measures of local Lipschitz constants. Like Lipschitz constants, tight inclusions functions are computationally challenging to obtain, and we thus propose using mixed monotonicity and contraction theory to obtain computationally efficient estimates of tight inclusion functions for INNs. We show that our approach performs at least as well as, and generally better than, applying state-of-the-art interval bound propagation methods to INNs. We design a novel optimization problem for training robust INNs and we provide empirical evidence that suitably-trained INNs can be more robust than comparably-trained feedforward networks. Copyright © 2022, The Authors. All rights reserved.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：