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25th IEEE International Conference on Industrial Technology, ICIT 2024

作者： Liu, Xiao Chen, Luefeng Wu, Min Cao, Weihua Lu, Chengda Pedrycz, Witold School of Automation China University of Geosciences Wuhan China School of Automation The Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems The Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Istinye University Department of Computer Engineering Sariyer Istanbul34396 Turkey

Changes in coal seam hardness cause fluctuations in the feed resistance at the drill bit during the drilling process, leading to unstable feeding speed. This paper proposes a robust dynamic output feedback controller to suppress disturbances caused by the variations in coal seam hardness in the feed system. Firstly, an unknown parameter measuring coal seam hardness is introduced, and an uncertain model of the feeding system is established based on the finite element model of the drill string. By designing weighted functions based on industrial field requirements and constructing a generalized plant, the controller achieves loop shaping, reducing the low-frequency impact of coal seam hardness variations on the feed system and suppressing the systems resonance peak. Simulation results demonstrate that the controller effectively suppresses parameter variations and external disturbances caused by changes in coal seam hardness, achieving stable control of the drilling speed. © 2024 IEEE.

关键词： Robust control

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Development of a UAV-based System for Technical Diagnostics of Overhead Power Lines 24

Development of a UAV-based System for Technical Diagnostics ...

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24th International Conference on Computational Problems of electrical engineering, CPEE 2023

作者： Kozlovskyi, Oleksandr Trushakov, Dmitro Rendzinyak, Serhiy Korud, Vasyl Central Ukrainian National Technical University Department of Electrical Systems and Energy Management Kropyvnytskyi Ukraine Central Ukrainian National Technical University Department of Automation and Control in Technical Systems Kropyvnytskyi Ukraine Ivan Franko National University of Lviv Faculty of Electronics and Computer Technologies Lviv Ukraine Lviv Polytechnic National University Institute of Power Engineering and Control System Lviv Ukraine

ISBN: (纸本)9798350330342

The problems associated with the operation of overhead power lines and ways of improving control over their condition with the help of UAVs are considered. A structural diagram of the system of technical diagnostics of overhead lines based on UAVs was developed, for which the necessary diagnostic parameters were selected according to informative criteria. An analysis of types of UAVs was carried out in order to determine their suitability and efficiency of use for diagnosing the condition of overhead lines. © 2023 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Rollout-Based Interactive Motion Planning for Automated Vehicles *

Rollout-Based Interactive Motion Planning for Automated Vehi...

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International Conference on Intelligent Transportation

作者： Ning Wang Xiao Chen Jonas Mårtensson Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden

Longitudinal and lateral motion planning poses a significant challenge to achieving full autonomy in automated vehicles. This work focuses on studying the motion planning problem for automated vehicles specifically in a highwaymerging scenario. The problem is modeled as an infinite horizon optimal control problem, taking into account finite control sets for the ego agents and uncontrolled state components of surrounding traffic. For this type of control problem, obtaining a real-time solution that meets both high safety and efficiency requirements can be difficult. In this study, we employ the rollout approach, which involves online optimization following the simulation of a known baseline policy instead of relying solely on extensive offline training. We compare the performance of one and multistep lookahead rollout algorithms against several state-of-the-art benchmark policies in simulation. The simulation results indicate that the rollout algorithm significantly enhances safety while simultaneously maintaining a high average speed within the merging scenario. Furthermore, we conduct simulation studies to assess the rollout methods in adapting to varying behaviors of surrounding vehicles. Additionally, we investigate the impact of different horizon settings and the introduction of terminal cost approximation.

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Invariant Safe Contingency Model Predictive control for Intersection Coordination of Mixed Traffic

Invariant Safe Contingency Model Predictive Control for Inte...

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International Conference on Intelligent Transportation

作者： Xiao Chen Jonas Mårtensson Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden

This paper addresses the coordination challenge at intersections of mixed traffic involving both Human-Driven Vehicles (HDVs) and Connected and Autonomous Vehicles (CAVs). To strike a balance between coordination performance and safety guarantees, we propose an invariant safe Contingency Model Predictive control (CMPC) framework. The CMPC framework incorporates two parallel horizons for the ego vehicle: a nominal horizon optimized for performance based on the most likely prediction of the opponent HDV, and a contingency horizon designed to maintain an invariant safe backup plan for emergencies. In the contingency horizon, we consider the worst-case behavior of the human driver and formulate safety constraints using the forward reachable sets of the HDV within the planning horizon. These safety constraints are complemented by maximal invariant safe sets as terminal constraints. The two horizons are tied together by enforcing equality of the feedback inputs at the beginning of the horizons. We provide theoretical evidence supporting the recursive feasibility and persistent performance improvement of the invariant safe CMPC compared to our previously proposed nominal invariant safe Model Predictive control (MPC). Through simulation studies, we evaluate the proposed method. The simulation results demonstrate that the CMPC approach achieves enhanced performance by reducing conservatism while simultaneously preserving the invariant safety property.

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Unknown Input Observers Breaking Confidentiality of controller States

Unknown Input Observers Breaking Confidentiality of Controll...

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IEEE Conference on Decision and control

作者： Enno Breukelman Henrik Sandberg School of Electrical Engineering and Computer Science Division of Decision and Control Systems KTH Royal Institute of Technology Malvinas väg 10 Stockholm Sweden

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

Driven by ubiquitous digitalization and cyberattacks on critical infrastructure, there is a high interest in research on the security of cyber-physical systems. If an attacker gains access to protected and sensitive information, such as the internal states of a control system, this is considered a breach of confidentiality. Access to sensitive information can be the first step in a larger cyber-attack scheme, such as a stealthy false data injection attack. Considering process and measurement noise in the plant, existing research investigated when an attacker equipped with a Kalman filter can perfectly estimate the internal controller states if the attacker has access to plant measurements and all model parameters. For this estimate to converge, the controller is required to have stable poles. In this paper, we show that if the attacker has access to the control inputs instead of the plant measurements, the controller needs to have stable zeros. Additionally, we demonstrate that an attacker equipped with an Unknown Input Observer, using tools from delayed system inversion, can get a delayed yet perfect estimate of the controller states from the control inputs without knowledge of the plant’s parameters and noise characteristics. Lastly, we present simulation results from a three-tank system to showcase the differences in controller state estimation.

关键词： Simulation Noise Process control Observers Cyber-physical systems Critical infrastructure Noise measurement Security Kalman filters Cyberattack

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A Novel Semantic Geo-Localization Approach with Satellite Images for GPS-Free Navigation of UAV 30

A Novel Semantic Geo-Localization Approach with Satellite Im...

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Artificial Intelligence and Image and Signal Processing for Remote Sensing XXX 2024

作者： Cheng, Yu-Cheng Yan, Yung-Jhe Chen, Peng-Jie Hsu, Cheng-Chuan Lo, Chun-Yan Chou, Cong-Yuan Lin, Chi-Han Ou-Yang, Mang Institute of Intelligent Systems National Yang Ming Chiao Tung University Hsinchu Taiwan Institute of Electrical and Control Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan Institute of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan Institute of Biomedical Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan Institute of Smart Industry and Green Energy National Yang Ming Chiao Tung University Hsinchu Taiwan

ISBN: (纸本)9781510681002

Image geo-localization estimates an image's global position by comparing it with a large-scale image database containing known positions. This localization technology can serve as an alternative positioning method for unmanned aerial vehicles (UAV) in situations where a global position system is unavailable. Feature-based image-matching methods typically involve descriptors constructed from pixel-level key points in the images. The number of descriptors in one image can be substantial. Filtering and comparing these large quantities of descriptors for image matching would be quite time-consuming. Due to the large scale of satellite images, matching them with aerial images using this method can be challenging to achieve in real-time. Thus, this paper proposes a semantic matching-based approach for real-time image geo-localization. The types, quantities, and geometric information of objects in satellite images are extracted and used as sematic-level descriptors. The sematic-level descriptors of an aerial image captured by UAV are extracted by an object recognition model. The quantity of semantic-level descriptors is orders of magnitude less than pixel-level descriptors. The location of the aerial image can be rapidly determined by matching the semantic-level descriptors between the aerial image and satellite images. In the experiments, the speeds of matching an aerial image with satellite images using the semantic matching and a feature-based matching method were 0.194 seconds per image and 125.68 seconds per image, respectively. Using semantic matching methods is 648 times faster than using feature matching methods. The results demonstrate that the proposed semantic matching methods have the potential for real-time image geo-localization. © 2024 SPIE.

关键词： Unmanned aerial vehicles (UAV)

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Lightweight Direct Memory Access on FPGA Using AXI Protocol

Lightweight Direct Memory Access on FPGA Using AXI Protocol

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computer Science, computer engineering, & Applied Computing (CSCE), Congress in

作者： Adam Kidwell Matthew P. Horvath Darrin Hanna Bryant Jones Dept. of Electrical and Computer Engineering Oakland University Rochester Hills MI Intrepid Control Systems Troy MI

This paper presents a lightweight AXI DMA controller architecture useful for embedded systems that do not require fully featured DMA controllers. Simulation is accomplished with VUnit, and implementation results are obtained on a Xilinx XC7Z010CLG400-1 FPGA. When compared with Xilinx's AXI DMA controller with the same configuration, the presented controller utilizes between 16 and 82% fewer resources with comparable speed.

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On the Systematic Construction of Lyapunov Functions for Polynomial systems

On the Systematic Construction of Lyapunov Functions for Pol...

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92nd Annual Meeting of the International Association of Applied Mathematics and Mechanics (GAMM)

作者： Natkowski, Lars Gerbet, Daniel Robenack, Klaus Fraunhofer Institute for Transportation and Infrastructure Systems IVI ZeunerstraBe 38 Dresden01069 Germany Institute of Control Theory Faculty of Electrical and Computer Engineering TU Dresden Georg-Schumann-StraBe 7A Dresden01187 Germany

Lyapunov functions are a widely used tool to evaluate stability properties of nonlinear dynamical systems’ equilibria. In this paper quantifier elimination is used to construct Lyapunov functions for polynomial systems from a parametric ansatz. Because the existing algorithms for quantifier elimination are inherently computationally expensive, a strategy is to simplify the quantifier elimination problem beforehand. A method is presented that may help simplifying the problem of finding suitable Lyapunov functions by deriving easier to evaluate necessary conditions. Finally, the introduced method is applied to an example system to show local asymptotic stability of an equilibrium point by constructing a Lyapunov function. © 2023 The Authors.

关键词： Lyapunov functions

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Self-Tuning Tube-based Model Predictive control

Self-Tuning Tube-based Model Predictive Control

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American control Conference (ACC)

作者： Damianos Tranos Alessio Russo Alexandre Proutiere Division of Decision and Control Systems School of Electrical Engineering and Computer Science Royal Institute of Technology (KTH) Stockholm Sweden

We present Self-Tuning Tube-based Model Predictive control (STT-MPC), an adaptive robust control algorithm for uncertain linear systems with additive disturbances based on the least-squares estimator and polytopic tubes. Our algorithm leverages concentration results to bound the system uncertainty set with prescribed confidence, and guarantees robust constraint satisfaction for this set, along with recursive feasibility and input-to-state stability. Persistence of excitation is ensured without compromising the algorithm’s asymptotic performance or increasing its computational complexity. We demonstrate the performance of our algorithm using numerical experiments.

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Symbiotic control of Uncertain Dynamical systems: Harnessing Synergy Between Fixed-Gain control and Adaptive Learning Architectures

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IEEE Transactions on Automatic control 2025年

作者： Yucelen, Tansel Sarsilmaz, Selahattin Burak Yildirim, Emre University of South Florida Department of Mechanical Engineering Laboratory for Autonomy Control Information and Systems TampaFL33620 United States Utah State University Department of Electrical and Computer Engineering LoganUT84322 United States

Both fixed-gain control and adaptive learning architectures aim to mitigate the effects of uncertainties. In particular, fixed-gain control offers more predictable closed-loop system behavior but requires the knowledge of uncertainty bounds. In contrast, while adaptive learning does not necessarily require such knowledge, it often results in less predictable closed-loop system behavior compared to fixed-gain control. To this end, this paper presents a novel symbiotic control framework that offers the strengths of fixed-gain control and adaptive learning architectures. Specifically, this framework synergistically integrates these architectures to mitigate the effects of uncertainties in a more predictable manner as compared to adaptive learning alone and it does not require any knowledge on such uncertainties. Both parametric and nonparametric uncertainties are considered, where we utilize neural networks to approximate the unknown uncertainty basis for the latter case. Counterintuitively, the proposed framework has the ability to achieve a desired level of closed-loop system behavior even with an insufficient number of neurons (e.g., when the neural network approximation error is large) or in the face of injudiciously selected adaptive learning parameters (e.g., high leakage term parameters). © 1963-2012 IEEE.

关键词： Closed loop control systems

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