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Predefined performance-based model-free adaptive fractional-order fast terminal sliding-mode control of MIMO nonlinear systems

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ISA Transactions 2022年 131卷 108-123页

作者： Esmaeili, Babak Salim, Mina Baradarannia, Mahdi Department of Control Engineering Faculty of Electrical and Computer Engineering University of Tabriz 29 Bahman Blvd. Tabriz *** Iran

The purpose of this article is to tackle with the problem of data-driven robust control of multi-input multi-output discrete-time nonlinear plants under tracking error constraints and output perturbations. Thereby, based upon the concept of dynamic linearization, a novel predefined performance based model-free adaptive fractional-order fast terminal sliding-mode controller is proposed so that the tracking errors can converge and remain within a preassigned neighborhood. The presented approach does solely rely on the real-time input/output data of the process, and the transient response together with the steady-state manner of the errors can be arbitrarily predefined. In the meantime, the closed-loop behavior is investigated by mathematical analysis, and the efficiency of the method is validated through various simulation examples. © 2022 ISA

关键词： MIMO systems

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A Physical-Data Fusion Framework for Lithium-ion Battery SOC Estimation∗ 49

A Physical-Data Fusion Framework for Lithium-ion Battery SOC...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Fu, Bingzhe Li, Yihuan Liu, Kailong Lin, Wei School of Control and Computer Engineering North China Electric Power University Beijing China School of Control Science and Engineering Shandong University Shandong China

ISBN: (纸本)9798350331820

Lithium-ion batteries have increasingly become a primary energy source in Electric Vehicles (EVs), power grid energy storage, aerospace, and other fields. Accurate State of Charge (SOC) estimation is crucial for the safe and efficient operation of lithium batteries. This paper proposes a physical-data fusion framework for accurate SOC estimation of Lithium-ion batteries. First, a fractional-order model (FOM) of lithium-ion batteries is built to describe the electrochemical reactions inside the battery, and a fractional-order Extended Kalman Filter (FOEKF) algorithm is used to achieve preliminary SOC estimation. Second, the FOM is combined with an error model established by Long Short-Term Memory (LSTM) to improve the accuracy of the FOEK-based SOC estimation by compensating for the estimation error. Finally, the proposed framework is verified on Maryland dataset, and the experimental results demonstrate that the fusion framework exhibits superior performance in improving the accuracy of SOC estimation, with at least 75% and 50% reduction in MSE and max error, respectively. © 2023 IEEE.

关键词： Long short-term memory

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Static Deadlock Detection for Interrupt-driven Embedded Software

Static Deadlock Detection for Interrupt-driven Embedded Soft...

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2024 International Conference on Cyber-Physical Social Intelligence, ICCSI 2024

作者： Zhang, Yu Zhang, Kaiwen Li, Xiaofeng Xie, Yi Guan, Jian Gu, Bin Liu, Guanjun Tongji University Department of Computer Science and Technology Shanghai China Beijing Control Engineering Institute Beijing China

ISBN: (纸本)9798350376739

Interrupt-driven embedded software is widely used in safety-critical systems, where any occurrence of errors can lead to serious consequences. Deadlock is a common concurrency error, and deadlock detection methods are mainly designed for multi-threaded programs. However, due to the differences in concurrency control and preemption mechanisms between interrupt-driven programs and multi-threaded programs, the existing deadlock detection methods for multi-threaded programs cannot be directly applied to interrupt-driven programs. A static deadlock detection method is proposed for interrupt-driven programs to enhance the reliability and safety of interrupt-driven embedded software. Building upon the traditional context-sensitive lockset analysis, this method takes into account the concurrent semantics of interrupts and extends the lock graph model. Our method effectively reduces false positives by analyzing the concurrent relationships of cycles in a lock graph. Based on these methods, we develop a deadlock detection tool, and experiments are conducted with it. The results demonstrate that the proposed method can effectively detect deadlocks related to interrupts. © 2024 IEEE.

关键词： Embedded software

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Phy-CoCo: Physical Constraint-Based Correlation Learning for Tropical Cyclone Intensity and Size Estimation 27

Phy-CoCo: Physical Constraint-Based Correlation Learning for...

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27th European Conference on Artificial Intelligence, ECAI 2024

作者： Yan, Hanting Mu, Pan Huang, Cheng Zhang, Jinglin Bai, Cong College of Computer Science Zhejiang University of Technology China School of Control Science and Engineering Shandong University China

ISBN: (纸本)9781643685489

Tropical Cyclone (TC) estimation aims to estimate various attributes of TC in real-time to alleviate and prevent disasters caused by violent TCs. As artificial intelligence technology advances, various deep learning-based multi-task estimation approaches have been proposed. However, most of them only focus on extracting common features of tasks, disregarding potential negative transfer and task interactions between different tasks. This paper is thus motivated to propose a Physical Constraint-based Correlation (Phy-CoCo) learning framework from the perspective of Multi-Task Learning (MTL). Specifically, for task-specific feature learning, we introduce Correlation Modeling (CoM) based on Centrally Expanded Pooling (CEP). Furthermore, for cross-task interaction, we propose a Multi-Domain Recurrent Convolution (MDRC) module to incorporate physical constraints into MTL. These physical constraints enable the transformation of different task features by simulating the physical relations among different attributes of TC. Lastly, in combination with a task-shared network that leverages the hybrid fusion of multi-modal data, our MTL framework accurately estimates various TC attributes. Extensive experiments conducted on our constructed dataset demonstrate that the proposed Phy-CoCo outperforms previous methods in TC estimation in terms of estimation error, verifying the potential of the physics-incorporated MTL model. © 2024 The Authors.

关键词： Tropical cyclone

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Parallel Programming in the Hybrid Model on the HPC Clusters 3rd

Parallel Programming in the Hybrid Model on the HPC Clusters

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3rd International Conference on computer Vision, High Performance Computing, Smart Devices, and Networks, CHSN 2022

作者： Rak, Tomasz Department of Computer and Control Engineering Rzeszow University of Technology Powstancow Warszawy 12 Rzeszow35-959 Poland

ISBN: (纸本)9789819966899

Support for an ever-expanding range of distributed and parallel strategies and support for performance analysis are constantly evolving. We propose message passing interface (MPI) and open multi-processing (OpenMP) standards that provide various software development tools covering a wide range of techniques not strictly limited to shared memory. The theoretical part focuses on a general overview of the current capabilities of MPI and OpenMP as application programming interfaces. The authors researched the high-performance computing (HPC) cluster environment, and this work provides results and representative examples. Also, in this study, it has been proven that to obtain favorable processing efficiency and write the code correctly— regardless of the programming paradigm used—it is necessary to know the basic concepts related to a given distributed and parallel architecture. Additionally, in this study, we investigated the need to adapt the tools used to solve a specific problem regarding improving processing efficiency. Finally, we presented that failure to apply a critical section may result in unpredictable results. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Message passing

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A dual adaptive unscented Kalman filter algorithm for SINS-based integrated navigation system

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Journal of Systems engineering and Electronics 2024年第3期35卷 732-740页

作者： LYU Xu MENG Ziyang LI Chunyu CAI Zhenyu HUANG Yi LI Xiaoyong YU Xingkai Department of Precision Instrument Tsinghua UniversityBeijing 100084China College of Mechanical and Power Engineering Three Gorges UniversityYichang 443002China Unit 91001 of the PLA Beijing 100161China School of Control and Computer Engineering North China Electric Power UniversityBeijing 100096China

In this study, the problem of measuring noise pollution distribution by the intertial-based integrated navigation system is effectively suppressed. Based on nonlinear inertial navigation error modeling, a nested dual Kalman filter framework structure is developed. It consists of unscented Kalman filter (UKF)master filter and Kalman filter slave filter. This method uses nonlinear UKF for integrated navigation state estimation. At the same time, the exact noise measurement covariance is estimated by the Kalman filter dependency filter. The algorithm based on dual adaptive UKF (Dual-AUKF) has high accuracy and robustness, especially in the case of measurement information interference. Finally, vehicle-mounted and ship-mounted integrated navigation tests are conducted. Compared with traditional UKF and the Sage-Husa adaptive UKF (SH-AUKF), this method has comparable filtering accuracy and better filtering stability. The effectiveness of the proposed algorithm is verified.

关键词： Kalman filter dual-adaptive integrated navigation unscented Kalman filter(UKF) robust

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A 6-bit Low-Area Hybrid ADC Design For System-on-Chip Measurements

A 6-bit Low-Area Hybrid ADC Design For System-on-Chip Measur...

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2024 IEEE International Conference on Design, Test and Technology of Integrated Systems, DTTIS 2024

作者： Kolahimahmoudi, Nima Insinga, Giorgio Roggi, Stefano Niederl, Josef Bernardi, Paolo Politecnico di Torino Department of Computer and Control Engineering Turin Italy Infineon Technologies AG Villach Austria

ISBN: (纸本)9798350363128

In recent years, with the declining dimensions of transistors, the system-on-chips (SoCs) have had more physical defects. These physical defects ultimately result in failures that cannot be tolerated in functional safety applications such as electric cars, aerospace, etc. For the digital peripherals of the SoCs, there are well-known methods such as scan chains, whereas there are methods for analog circuits such as analog scan chains or Analog Test Bus (ATB). This paper presents a 6-bit, low-area Analog-to-Digital Converter (ADC) for SoC analog voltage measurements. The advantage of the proposed ADC design is the low additional area cost to the design of the SoC and increasing the testability of the analog peripherals. This ADC design converts the analog signals, which are difficult to observe, to the digital domain, which is easy to route and observe. This architecture comprises two small ADCs for doing coarse and fine conversions. The ADC for the coarse conversion is a 3-bit SAR ADC, and the ADC for the fine conversion is a 3-bit flash ADC. The suggested ADC is implemented using the 130 nm technology of the Infineon, and it has a total area of 0.007 mm2. The fine ADC of the proposed ADC can be shared between the peripherals nearby inside the SoC, and the additional area per peripheral would be only 0.0015 mm2. The Signal-to-Noise Distortion Ratio (SNDR) of the design is 37dB, and the Figure of Merit (FoM) is 2.15 pJ/conv. © 2024 IEEE.

关键词： System-on-chip

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Monte Carlo tree search with state merging for reinforcement learning in Regular Decision Processes

Monte Carlo tree search with state merging for reinforcement...

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2023 International Conference of the Italian Association for Artificial Intelligence Doctoral Consortium, AIxIA-DC 2023

作者： Licks, Gabriel Paludo Sapienza University of Rome Department of Computer Control and Management Engineering Via Ariosto 25 Rome00185 Italy

This research focuses on a novel algorithm for Reinforcement Learning (RL) in Regular Decision Processes (RDPs), a model of non-Markovian decision processes where dynamics and rewards depend on regular properties of the history. Our algorithm is inspired by Monte Carlo tree search (MCTS), yet it is improved with state merging capabilities. Performing merges allows us to evolve the tree model into a graph over time, as we periodically perform similarity tests borrowed from automata learning theory to learn states that are equivalent to one another. This results in improved efficiency and scalability over standard MCTS. Empirical results demonstrate orders of magnitude performance improvement over the state-of-the-art RL algorithms for RDPs. We discuss limitations both in concerning the MCTS implementation and similarity tests from probabilistic automata. © 2023 Copyright for this paper by its authors.

关键词： Reinforcement learning

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Switching control for Identification Deception in Cyber-Physical Systems 63

Switching Control for Identification Deception in Cyber-Phys...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Mavridis, Christos Kanellopoulos, Aris Sandberg, Henrik Johansson, Karl Henrik Kth Royal Institute of Technology Division of Decision and Control School of Electrical Engineering and Computer Science Stockholm Sweden

ISBN: (纸本)9798350316339

We investigate the problem of deceiving a malicious agent employing an identification method to estimate the closed-loop dynamics of a cyber-physical system. In particular, we propose a moving target defense mechanism that utilizes stochastic switching between linear closed-loop dynamics to drive a linear system identification process of a potential adversary to sub-optimal solutions with non-vanishing error. We provide a statistical analysis of the induced identification error and show that it is not possible for any linear system identification method to reconstruct the average dynamics of a stochastic switched linear system. Finally, we utilize the theory of Markov jump linear systems to guarantee asymptotic stability of the switching system, and formulate the switching control problem as an optimization problem that guarantees stability while taking into account the trade-off between security and switching effort. Simulation results showcase the efficacy of the proposed approach in inducing identification error for the adversary using minimal switching. © 2024 IEEE.

关键词： Markov processes

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Remote sensing image encryption algorithm based on novel hyperchaos and an elliptic curve cryptosystem

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Chinese Physics B 2024年第5期33卷 292-304页

作者：田婧希金松昌张晓强杨绍武史殿习 School of Computer Science National University of Defense TechnologyChangsha 410003China Intelligent Game and Decision Laboratory (IGDL) Beijing 100091China School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116China

Remote sensing images carry crucial ground information,often involving the spatial distribution and spatiotemporal changes of surface *** safeguard this sensitive data,image encryption technology is *** this paper,a novel Fibonacci sine exponential map is designed,the hyperchaotic performance of which is particularly suitable for image encryption *** encryption algorithm tailored for handling the multi-band attributes of remote sensing images is *** algorithm combines a three-dimensional synchronized scrambled diffusion operation with chaos to efficiently encrypt multiple ***,the keys are processed using an elliptic curve cryptosystem,eliminating the need for an additional channel to transmit the keys,thus enhancing *** results and algorithm analysis demonstrate that the algorithm offers strong security and high efficiency,making it suitable for remote sensing image encryption tasks.

关键词： hyperchaotic system elliptic curve cryptosystem(ECC) 3D synchronous scrambled diffusion remote sensing image unmanned aerial vehicle(UAV)

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