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Weighted Feedback-Based Quantum Algorithm for Excited States Calculation

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arXiv 2024年

作者： Rahman, Salahuddin Abdul Karabacak, Özkan Wisniewski, Rafal Section of Automation and Control Department of Electronic Systems Aalborg University Aalborg Denmark Department of Mechatronics Engineering Kadir Has University Istanbul Turkey

Drawing inspiration from the Lyapunov control technique for quantum systems, feedback-based quantum algorithms have been proposed for calculating the ground states of Hamiltonians. In this work, we consider extending these algorithms to tackle calculating excited states. Inspired by the weighted subspace-search variational quantum eigensolver algorithm, we propose a novel weighted feedback-based quantum algorithm for excited state calculation. We show that depending on how we design the weights and the feedback law, we can prepare the pth excited state or lowest energy states up to the pth excited state. Through an application in quantum chemistry, we show the effectiveness of the proposed algorithm, evaluating its efficacy via numerical simulations. © 2024, CC BY.

关键词： Hamiltonians

Feedback-Based Quantum Algorithm for Constrained Optimization Problems

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arXiv 2024年

The feedback-based algorithm for quantum optimization (FALQON) has recently been proposed to find ground states of Hamiltonians and solve quadratic unconstrained binary optimization problems. This paper efficiently generalizes FALQON to tackle quadratic constrained binary optimization (QCBO) problems. For this purpose, we introduce a new operator that encodes the problem's solution as its ground state. Using control theory, we design a quantum control system such that the state converges to the ground state of this operator. When applied to the QCBO problem, we show that our proposed algorithm saves computational resources by reducing the depth of the quantum circuit and can perform better than FALQON. The effectiveness of our proposed algorithm is further illustrated through numerical simulations. © 2024, CC BY.

关键词： Constrained optimization

Roving with the buzzards: a TRL 5 autonomy marathon 74

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Roving with the buzzards: a TRL 5 autonomy marathon

74th International Astronautical Congress, IAC 2023

作者： Marc, R. Brayzier, B. Hamill, D. Braun, M. Dinsdale, M. Daoud-Moraru, A. Weclewski, P. Barclay, C. Sanchez-Ibanez, J.R. Hamilton, W. D'Ambrosi, E. Lee, C. Lopes, R. Douglas, J. Dysli, A. Azkarate, M. Guidance Navigation and Control Department Airbus Defence and Space Ltd. StevenageSG1 2AS United Kingdom Automation and Robotics Section ESA - European Space Agency ESTEC Keplerlaan 1 Noordwijk2201 AZ Netherlands

The Mars Sample Return (MSR) campaign constitutes a complex, long-term operation aiming at returning samples from the surface of the red planet to Earth. As part of this campaign, the Sample Fetch Rover (SFR) was conceived as a European contingency to NASA's Perseverance rover to fetch and deliver these samples to the return vehicle. Although this concept was dropped, it served to develop and validate autonomous traverse strategies that are useful for future planetary or lunar exploration missions. This is the context and motivation behind the shakedown of the Field Test Rover System (FTRS) during the Integrated BreadBoard 2 (IBB2) project. This paper presents an overview of the first real-world demonstration of such a robotic system. The IBB2 shakedown took place in September 2022 at a silica sand quarry near Leighton Buzzard, which offered both unfeatured, flat terrain and irregular, rocky terrain to cover a breadth of test scenarios. The locomotion subsystem was representative of the SFR design comprising two differential rocker bogies, eight independent actuators for steering and driving, and shape memory alloy tyres - on loan from NASA's Glenn Research Center (GRC). This test campaign served to build confidence in the Guidance Navigation and control (GNC) mobility sub-system and identify any resultant issues early in its development. In particular, this campaign encompassed a series of GNC use cases with increasing levels of autonomy, including a fully autonomous 300m traverse showcasing the novel Absolute Global Localisation (AGL) algorithm. At the end of this paper we include some discussion about the results obtained and conclusions reached that may prove useful for the conceptualisation and design of GNC strategies for future robotic exploration missions. Copyright © 2023 by the International Astronautical Federation (IAF). All rights reserved.

关键词： autonomous driving field trials GNC MSR rover SFR

Online Learning of Safety function for Markov Decision Processes

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Online Learning of Safety function for Markov Decision Proce...

European control Conference (ECC)

作者： Abhijit Mazumdar Rafal Wisniewski Manuela L. Bujorianu Section of Automation & Control Aalborg University Aalborg East Denmark Department of Computer Science University College London UK

In this paper, we aim to study safety specifications for a Markov decision process with stochastic stopping time in an almost model-free setting. Our approach involves characterizing a proxy set of the states that are near in a probabilistic sense to the set of unsafe states - forbidden set. We also provide results that relate safety function with reinforcement learning. Consequently, we develop an online algorithm based on the temporal difference method to compute the safety function. Finally, we provide simulation results that demonstrate our work in a simple example.

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From MDP to POMDP and Back: Safety and Compositionality

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From MDP to POMDP and Back: Safety and Compositionality

European control Conference (ECC)

作者： Manuela L. Bujorianu Tristan Caulfield David Pym Rafael Wisniewski Department of Computer Science University College London UK Section of Automation & Control Aalborg University Aalborg East Denmark

We propose a compositional framework for the stochastic safety of distributed Markov Decision Processes (MDPs) and Partially Observable Markov Decision Processes (POMDPs). We use MDP and POMDPs and their distributed versions as an appropriate modelling paradigm for computational ecosystems, understood in the context of distributed systems. We extend our work on stochastic safety from MDPs to POMDPs, and then to networked MDP/POMDPs. We propose a unifying mathematical framework for stochastic safety for MDPs, their partially observable version and their composition.

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Online Model-free Safety Verification for Markov Decision Processes Without Safety Violation

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arXiv 2023年

作者： Mazumdar, Abhijit Wisniewski, Rafal Bujorianu, Manuela L. The Section of Automation & Control Aalborg University Aalborg9220 Denmark The Department of Computer Science University College London United Kingdom

In this paper, we consider the problem of safety assessment for Markov decision processes without explicit knowledge of the model. We aim to learn probabilistic safety specifications associated with a given policy without compromising the safety of the process. To accomplish our goal, we characterize a subset of the state-space called proxy set, which contains the states that are near in a probabilistic sense to the forbidden set consisting of all unsafe states. We compute the safety function using the single-step temporal difference method. To this end, we relate the safety function computation to that of the value function estimation using temporal difference learning. Since the given control policy could be unsafe, we use a safe baseline sub-policy to generate data for learning. We then use an off-policy temporal difference learning method with importance sampling to learn the safety function corresponding to the given policy. Finally, we demonstrate our results using a numerical example. © 2023, CC BY-NC-ND.

关键词： Markov processes

Abnormal Status Detection of Catenary Based on TSNE Dimensionality Reduction Method and IGWO-LSSVM Model

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Recent Patents on Mechanical Engineering 2023年第3期16卷 188-202页

作者： Lingzhi, Yi Guo, Yu Yahui, Wang Tengfei, Dong Huang, Yu Haixiang, She College of Automation and Electronic Engineering Xiangtan University Hunan Xiangtan411105 China Hunan Engineering Research Center of Multi-energy Cooperative Control Technology Hunan Xiangtan411105 China College of Electrical and Information Engineering Hunan University Hunan Changsha410082 China Pu'er Infrastructure section of China Railway Kunming Group Co. Ltd Yunnan Kunming665000 China

Background: Catenary is a crucial component of an electrified railroad's traction power supply sys-tem. There is a considerable incidence of abnormal status and failures due to prolonged outside exposure. Driving safety will be directly impacted if an abnormal status or failure occurs. Currently, catenary detection vehicles are the most often utilized technique for gathering data and identifying faults based on manual experience. However, this technology cannot meet the demands of prompt detection and correction of faults in railways engineering due to its extremely low work efficiency. Objective: Based on the above, an abnormal status detection method of catenary based on the improved gray wolf (IGWO) algorithm optimized the least squares support vector machine (LSSVM) with the t-distributed stochastic neighbor embedding (TSNE) is proposed in this paper. In order to improve the accuracy of catenary abnormal status detection and shorten the detection time. Methods: Firstly, the TSNE dimensionality reduction technology is used to reduce the original catenary data to three-dimensional space. Then, in order to address the issue that the parameters of the LSSVM detection model are hard to determine, the improved GWO algorithm is used to optimize the penalty factor and kernel parameter in the LSSVM and establish the TSNE-IGWO-LSSVM catenary abnormal status detection model. Finally, contrasting experimental results of different detection models. The T-distributed Stochastic Domain Embedding (TSNE) is an improved nonlinear dimensionality reduction method based on the Stochastic Neighbor Embedding (SNE). TSNE no longer adopts the distance invariance in linear dimensionality reduction methods such as ISOMAP. TSNE is much better than the linear dimensionality reduction method in the reduction degree of the original dimension. The GWO algorithm, which is frequently used in engineering re-search, has the advantages of a simple model, great generalization capability, and good op

关键词： Support vector machines

Railroad Catenary Insulator Fault Detection Based on Improved Faster R-CNN

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Recent Patents on Mechanical Engineering 2024年第4期17卷 243-259页

作者： Yi, Lingzhi Dong, Tengfei Wang, Yahui She, Haixiang Yi, Chuyang Yu, Guo College of Automation and Electronic Engineering Xiangtan University & Hunan Engineering Research Center of Multi-energy Cooperative Control Technology Hunan Xiangtan411105 China College of Electrical and Information Engineering Hunan University Changsha410082 China Pu'er Infrastructure Section of China Railway Kunming Group Co. Ltd Yunnan Kunming665000 China Yongan Application Workshop of Fuzhou Locomotive Depot of Nanchang Railway Bureau Fujian Yongan366000 China

Background: The railroad catenary insulator, which is a crucial component of the cate-nary system and is situated between the pillar and wrist arm, is crucial for electrical conductor isolation, electrical equipment insulation, mechanical load bearing, anti-fouling, and anti-leakage. The catenary insulators will experience tarnished flash, breakage, insulation strength deterioration, and other issues as a result of the long-term outside unfavorable working circumstances. The train electrical system's ability to operate normally is greatly hampered by these problems. Although there are many patents and articles related to insulator fault detection, the precision is not high enough. Therefore, it is crucial to improve the precision of catenary insulator fault detection. Objective: An improved region-based convolutional neural networks (Faster R-CNN)-based fault detection method for railway catenary insulators is proposed in response to the long detection time of the conventional railroad catenary insulator fault, the low precision of the catenary insulator fault detection for occlusion and truncation, the poor performance of multi-scale object detection, and the processing of class unbalance problem. Methods: The Faster R-CNN is optimized from four perspectives: feature extraction, feature fusion, candidate box screening, and loss function, in accordance with the properties of the catenary insulator. First, to solve the problem of multi-scale catenary insulator fault detection, convolutional block attention module (CBAM) and feature pyramid network (FPN) are used to fuse the deep feature and shallow features of the image. This results in a feature map with more critical semantic information and higher resolution. After that, the weighted non-maximum suppression (WNMS) algorithm improved by distance-intersection over union (DIOU) and Gaussian weighting function is used instead of the traditional NMS algorithm, which effectively introduces the overlap of detection frame

关键词： Feature extraction

An Online Stochastic Optimization Approach for Insulin Intensification in Type 2 Diabetes with Attention to Pseudo-Hypoglycemia*

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arXiv 2022年

作者： Ahdab, Mohamad Al Knudsen, Torben Stoustrup, Jakob Leth, John Section of Automation and Control Department of Electronic Systems Aalborg University Aalborg Øst Denmark

In this paper, we present a model free approach to calculate long-acting insulin doses for Type 2 Diabetic (T2D) subjects in order to bring their blood glucose (BG) concentration to be within a safe range. The proposed strategy tunes the parameters of a proposed control law by using a zeroth-order online stochastic optimization approach for a defined cost function. The strategy uses gradient estimates obtained by a Recursive Least Square (RLS) scheme in an adaptive moment estimation based approach named AdaBelief. Additionally, we show how the proposed strategy with a feedback rating measurement can accommodate for a phenomena known as relative hypoglycemia or pseudo-hypoglycemia (PHG) in which subjects experience hypoglycemia symptoms depending on how quick their BG concentration is lowered. The performance of the insulin calculation strategy is demonstrated and compared with current insulin calculation strategies using simulations with three different models. © 2022, CC BY-NC-SA.

关键词： Insulin