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Scheduling of over-actuated networked control systems

IFAC-PapersOnLine 2022年第13期55卷 25-30页

作者： J. Kreiss R. Postoyan D. Nešić W.P.M.H. Heemels Université de Lorraine CNRS CRAN F-54000 Nancy France Department of Electrical and Electronic Engineering University of Melbourne Parkville VIC 3010 Australia Control Systems Technology Section Department of Mechanical Engineering Eindhoven University of Technology Netherlands

We investigate the scenario where an over-actuated plant is controlled over a network. We concentrate on the effect of two network-induced phenomena: varying transmission intervals and scheduling, in the sense that only one of the actuators receives new data at each transmission instant. We present an emulation-based solution for the controller design, i.e., the controller is first designed to stabilize the origin of the plant ignoring the network and second, the packet-based network is taken into account and conditions on the maximum allowable transmission interval (MATI) and the scheduling protocol are given to preserve the stability of the closed-loop system. Our results are tailored to over-actuated plants leading to significant improvements compared to applying off-the-shelf results available in the literature. In particular, a new model is derived and new conditions on the scheduling protocol are given, which lead to a two-measure stability property for the networked control system. We illustrate how new classes of scheduling protocols can be derived by exploiting over-actuation, which leads to larger MATI bounds compared to applying existing results, as shown on a numerical example.

关键词： Networked control systems over-actuated systems hybrid systems stability of hybrid systems Lyapunov methods

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Chinese automation Congress (CAC)

作者： Yumin Lang Jiande Wu Xun Lang Wanke Yu Chuanyan Yang Hongye Su Department of Electronic Engineering Information School Yunnan University Kunming China Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan University Kunming China School of Automation China University of Geosciences Wuhan China State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Oscillation is a significant indication of the deterioration of control system performance and needs to be carefully monitored to ensure safe and stable process operations. However, industrial processes are often prone to noisy artifacts and nonstationary trends, resulting in low signal-to-noise ratios. In order to tackle this problem, this study introduces a novel framework for enhanced trend removal and noise reduction, which is featured by the following steps:(i) The circulant singular spectrum analysis (CiSSA) is used to decompose oscillation data into several reconstructed components (RCs). (ii) The estimated power spectral density (PSD) of these RCs is then smoothed using the Savitzky-Golay filter (SGF) to eliminate noise and identify the RCs corresponding to oscillatory components. (iii) These identified RCs are subsequently reconstructed to produce purified oscillatory data. The effectiveness of the suggested approach is validated using simulations and real-world industrial case studies. The findings indicate that the method notably enhances the quality of oscillatory data.

关键词： Power filters Noise reduction Process control Market research Information filters Noise measurement Oscillators Spectral analysis Monitoring Signal to noise ratio

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Quantification of Valve Stiction in control Loops Using Adaptive Differential Evolution Algorithm

Quantification of Valve Stiction in Control Loops Using Adap...

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Chinese automation Congress (CAC)

作者： Dong Yang Xun Lang Jiande Wu Wanke Yu Songhua Liu Lei Xie Department of Electronic Engineering Information School Yunnan University Kunming China Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan University Kunming China School of Automation China University of Geosciences Wuhan China State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Accurately and promptly quantifying stiction is crucial for valve maintenance in industrial settings and ensuring the stability of control loop performance. However, current Hammerstein-based stiction quantification methods overlook valve dynamics, potentially leading to inaccurate quantification. Therefore, this paper proposes a novel stiction quantification method based on an adaptive differential evolution algorithm. In addition to considering the impact of valve dynamics on stiction, the proposed method demonstrates a certain level of robustness against the interference of unknown noise. Finally, the effectiveness of the proposed method is demonstrated through a series of simulations and industrial case studies.

关键词： Adaptation models Heuristic algorithms Noise Interference Valves Stability analysis Robustness Data models Maintenance Classification algorithms

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Stochastic Modeling and Inference for Type 2 Diabetes

TechRxiv

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TechRxiv 2023年

作者： Ahdab, Mohamad Al Papež, Milan Knudsen, Torben Aradóttir, Tinna Björk Schmidt, Signe Nørgaard, Kirsten Leth, John Section of Automation and Control Dept. of Electronic Systems Aalborg University Aalborg Øst Denmark The Artificial Intelligence Center Czech Technical University Prague Czech Republic Novo Nordisk A/S Bagsværd Denmark Steno Diabetes Center Copenhagen Gentofte Denmark and Hvidovre University Hospital Hvidovre Denmark

Type 2 diabetes (T2D) is a common metabolic disorder that poses threat to human health. Blood glucose (BG) concentrations in T2D subjects can be influenced by various factors, such as stress, physical activity, and meal consumption. Obtaining personalized mathematical models for people with T2D can be beneficial for developing effective T2D management strategies, such as insulin dosing algorithms. However, fitting these models for T2D subjects can be challenging due to the limited data typically available during treatment, consisting of only Continuous Glucose Monitoring (CGM) readings and injected insulin amounts. To address this issue, we propose a stochastic jump diffusion model that incorporates the uncertainties from meal consumption behavior together with other disturbances. Additionally, we provide an inference strategy that enables us to estimate both physiological (e.g., insulin sensitivity) and behavioral (e.g., average number of meals per day) parameters using only CGM data and injected insulin amounts. We validate the proposed stochastic model and inference strategy with synthetic and clinical data, assessing their ability to estimate various parameters of the model and fit CGM data. The results demonstrate that our proposed method, along with the model, manages to estimates parameters with different interquartile range (IQR) values. Moreover, the model, in combination with the method, provide a good fit for CGM data, and demonstrates the ability to obtain estimates of unannounced meal times. © 2023, CC BY.

关键词： Stochastic models

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Distance-based Multiple Non-cooperative Ground Target Encirclement for Complex Environments

arXiv

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arXiv 2024年

作者： Liu, Fen Yuan, Shenghai Cao, Kun Meng, Wei Xie, Lihua School of Electrical and Electronic Engineering Nanyang Technological University Singapore639798 Singapore Department of Control Science and Engineering College of Electronics and Information Engineering Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai200000 China Guangdong Provincial Key Laboratory of Intelligent Decision and Cooperative Control School of Automation Guangdong University of Technology Guangzhou510006 China

This paper proposes a comprehensive strategy for complex multi-target-multi-drone encirclement in an obstacle-rich and GPS-denied environment, motivated by practical scenarios such as pursuing vehicles or humans in urban canyons. The drones have omnidirectional range sensors that can robustly detect ground targets and obtain noisy relative distances. After each drone task is assigned, a novel distance-based target state estimator (DTSE) is proposed by estimating the measurement output noise variance and utilizing the Kalman filter. By integrating anti-synchronization techniques and pseudo-force functions, an acceleration controller enables two tasking drones to cooperatively encircle a target from opposing positions while navigating obstacles. The algorithm’s effectiveness for the discrete-time double-integrator system is established theoretically, particularly regarding observability. Moreover, the versatility of the algorithm is showcased in aerial-to-ground scenarios, supported by compelling simulation results. Experimental validation demonstrates the effectiveness of the proposed approach. © 2024, CC BY.

关键词： Drones

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Consistent and Asymptotically Efficient Localization from Range-Difference Measurements

arXiv

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arXiv 2023年

作者： Zeng, Guangyang Mu, Biqiang Shi, Ling Chen, Jiming Wu, Junfeng The School of Data Science Chinese University of Hong Kong Shenzhen Shenzhen China The Department of Automation University of Science and Technology of China Hefei China Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China The Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong The College of Control Science and Engineering The State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou310027 China

We consider signal source localization from range-difference measurements. First, we give some readily-checked conditions on measurement noises and sensor deployment to guarantee the asymptotic identifiability of the model and show the consistency and asymptotic normality of the maximum likelihood (ML) estimator. Then, we devise an estimator that owns the same asymptotic property as the ML one. Specifically, we prove that the negative log-likelihood function converges to a function, which has a unique minimum and positive definite Hessian at the true source's position. Hence, it is promising to execute local iterations, e.g., the Gauss-Newton (GN) algorithm, following a consistent estimate. The main issue involved is obtaining a preliminary consistent estimate. To this aim, we construct a linear least-squares problem via algebraic operation and constraint relaxation and obtain a closed-form solution. We then focus on deriving and eliminating the bias of the linear least-squares estimator, which yields an asymptotically unbiased (thus consistent) estimate. Noting that the bias is a function of the noise variance, we further devise a consistent noise variance estimator that involves 3-order polynomial rooting. Based on the preliminary consistent location estimate, a one-step GN iteration suffices to achieve the same asymptotic property as the ML estimator. Simulation results demonstrate the superiority of our proposed algorithm in the large sample case. Copyright © 2023, The Authors. All rights reserved.

关键词： Iterative methods

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control of Wall Mounting Robot: Practical Implementation and Experiments

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IFAC-PapersOnLine 2020年第2期53卷 10025-10030页

作者： Malte R. Damgaard Rasmus Pedersen Karl D. Hansen Thomas Bak Department of Electronic Systems Automation and Control Aalborg University Denmark

Robots are gaining traction in all industries, not only to replace manual labour but also to collaborate and enhance both human and robot skills and abilities. In this paper, we revisit the trajectory following control design for the WallMo Robot, which is a collaborative wall mounting robot used in the construction industry. The theoretical foundation for a model-free control strategy, handling actuator constraints was presented by Sloth and Pedersen (2017) and verified through simulations. In this paper, the research is extended to also include practical implementation considerations and experimental testing on a real WallMo robot. The implemented control strategy differs from what was presented earlier, but still exhibits tight trajectory tracking - solving the control problem in a practical setting.

关键词： Robotics technology Motion control systems Robots in construction

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HAVOK Model Predictive control for Time-Delay systems with Applications to District Heating

arXiv

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arXiv 2022年

作者： Jensen, Christian M. Frederiksen, Mathias C. Kallesøe, Carsten S. Jensen, Jeppe N. Andersen, Laurits H. Izadi-Zamanabadi, Roozbeh Department of Electronic Systems Automation and Control Aalborg University Aalborg9210 Denmark Grundfos A/S Poul Due Jensens Vej Bjerringbro Denmark Danfoss A/S Nordborgvej 81 Nordborg Denmark

A computationally efficient Model-Predictive control (MPC) approach is proposed for systems with unknown delay using only input/output data. We use the Koopman operator framework and the related Hankel Alternative View of Koopman (HAVOK) algorithm to identify a model in a basis of projected time-delay coordinates and demonstrate a novel MPC structure that reduces and bounds the computational complexity. The proposed HAVOK-MPC approach is validated experimentally on a laboratory-scale District Heating System (DHS), demonstrating excellent prediction and tracking performance while only requiring knowledge of a conservative upper bound on the system delay. © 2022, CC BY-NC-SA.

关键词： Dynamic mode decomposition

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IEEE Transactions on Instrumentation and Measurement 2024年 1-1页

作者： Wu, Jin Wang, Chaoqun Li, Chong Jiang, Yi Zhang, Chengxi Huang, Yulong Qi, Yuhua Xue, Bohuan Jiao, Jianhao Fan, Rui Zhang, Wei Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong China School of Control Science and Engineering Shandong University Jinan China Department of Automation and Measurement Ocean University of China Qingdao China Department of Electrical Engineering City University of Hong Kong Hong Kong China School of Internet of Things Jiangnan University Wuxi China Department of Automation Harbin Engineering University Harbin China School of Systems Science and Engineering Sun Yat-Sen University China College of Electronics and Information Engineering Tongji University Shanghai China

Similarity transformation problems are important in robotic instrumentation and computer vision based measurements since in many cases the information of visually observed scene scale is unknown and must be restored for accurate 3-dimensional reconstruction. In existing solvers, the scale is often considered as a scalar, i.e., isotropic, which may be invalid for anisotropic-scale setups. This paper exploits some mathematical coincidences that will lead to efficient solution to these problems. Possible further applications also include hand-eye calibration and structure-from-motion. We revisit pose estimation problems within the framework of similarity transformation, the one that considers scale-stretching, rotation and translation simultaneously. Two major problems are taken into account, i.e., the scale-stretching point-cloud registration and perspective-n-points (PnP). It has been found out that these two problems are quite similar. Moreover, we solve the anisotropic-scale registration problem that is important and is a remaining unsolved one in previous literatures. To compute the globally optimal solution of these non-convex problems, algebraic solution is obtained to compute all local minima using computationally efficient methods. The designed algorithm is deployed for robotic-arm pose estimation. We also extend the algorithm for solving the problem of robust magnetometer calibration. Visual pose experiments verify the superiority of the proposed method compared with representatives, including P3P, Lambda-Twist P3P and EPnP, which can be reproduced by repository in https://***/zarathustr/APnP. IEEE

关键词： Calibration

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Adaptive Stiffness control of Series Elastic Actuator Manipulators Based on Dynamic System

Adaptive Stiffness Control of Series Elastic Actuator Manipu...

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IEEE International Conference on automation Science and Engineering (CASE)

作者： Kunlin Guo Chao Zeng Weiyong Si Ning Wang Chenguang Yang Key Laboratory of Autonomous Systems and Networked Control School of Automation Science and Engineering South China University of Technology Guangzhou China Department of Computer Science University of Liverpool Liverpool UK School of Computer Science and Electronic Engineering University of Essex Colchester Bristol Robotics Laboratory University of the West of England Bristol UK

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

In traditional control methods, Series Elastic Actuator (SEA) joint manipulators are limited by their hardware and can only perform simple tasks with low stiffness. To address this issue, we propose a stiffness adjustment control strategy for SEA manipulators based on Dynamic systems (DS) with good generalization performance. By enhancing the generalization capability of DS in complex tasks and combining posture control, the SEA manipulators can autonomously adjust control gains and postures according to task requirements to achieve higher stiffness at the end-effector. Experimental results involving the activation of air switches with different stiffness levels and installation angles have demonstrated the effectiveness of our proposed method. The results indicate that compared to traditional methods of adjusting the control gain and retraining DS for similar tasks, our approach exhibits superior generalization performance while maintaining end-effector stiffness during interactions.

关键词： Actuators Computer aided software engineering automation Adaptive systems control systems End effectors Hardware Dynamical systems Manipulator dynamics

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