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Distributed formation control of networked mechanical systems

IFAC-PapersOnLine 2022年第13期55卷 294-299页

作者： N. Javanmardi P. Borja M.J. Yazdanpanah J.M.A. Scherpen Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Department of Cognitive Robotics Delft University of Technology Delft The Netherlands Jan C. Wilems Center for Systems and Control ENTEG Faculty of Science and Engineering University of Groningen Groningen The Netherlands

This paper investigates a distributed formation tracking control law for large-scale networks of mechanical systems. In particular, the formation network is represented by a directed communication graph with leaders and followers, where each agent is described as a port-Hamiltonian system with a constant mass matrix. Moreover, we adopt a distributed parameter approach to prove the scalable asymptotic stability of the network formation, i.e., the scalability with respect to the network size and the specific formation preservation. A simulation case illustrates the effectiveness of the proposed control approach.

关键词： Autonomous systems Cooperative control Networked control systems Large-scale systems Port-Hamiltonian systems Scalability

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Distributed Optimal Load Frequency control with Stochastic Wind Power Generation

Distributed Optimal Load Frequency Control with Stochastic W...

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2021 European control Conference, ECC 2021

作者： Silani, Amirreza Cucuzzella, Michele Scherpen, Jacquelien M. A. Javad Yazdanpanah, Mohammad University of Groningen Jan C. Willems Center For Systems and Control ENTEG Faculty of Science and Engineering Groningen Netherlands University of Tehran Control Intelligent Processing Center of Excellence School of Electrical and Computer Engineering Tehran Iran Department of Electrical Computer and Biomedical Engineering University of Pavia Pavia Italy

ISBN: (纸本)9789463842365

Motivated by the inadequacy of conventional control methods for power networks with a large share of renewable generation, in this paper we study the (stochastic) passivity property of wind turbines based on the Doubly Fed Induction Generator (DFIG). Differently from the majority of the results in the literature, where renewable generation is ignored or assumed to be constant, we model wind power generation as a stochastic process, where wind speed is described by a class of stochastic differential equations. Then, we design a distributed control scheme that achieves load frequency control and economic dispatch, ensuring the stochastic stability of the controlled network. © 2021 EUCA.

关键词： Random processes

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Multivariate Mutual Information Measures Functional Connectivity Accurately

Multivariate Mutual Information Measures Functional Connecti...

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International Conference of Signal processing and intelligent Systems (ICSPIS)

作者： Mahnaz Ashrafi Hamid Soltanian-Zadeh Control and Intelligent Processing Center of Excellence (CIPCE) School of Electrical and Computer Engineering University of Tehran Tehran Iran

ISBN: (纸本)9781665409391

Most studies use linear correlation as an estimator of functional connectivity. This measure does not detect the nonlinear dependence between two variables. During resting state, there are nonlinear relations among time series discarded by common functional connectivity measures such as Pearson correlation. Another limitation of linear correlation is the inability of calculating the association between two multivariate variables. Typically, a dimension reduction such as averaging is applied to each region time series. This reduction leads to a loss of spatial information across voxels within the region. Here, we propose to use a new information-theoretic measure as an interaction estimator between brain regions. Using simulated data, we show that this measure, multivariate mutual information (MVMI), overcomes the above mentioned limitations.

关键词： Dimensionality reduction Correlation Time series analysis Signal processing Time measurement intelligent systems Mutual information

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Model-Free Dynamic control of a 3-DoF Delta Parallel Robot for Pick-and-Place Application based on Deep Reinforcement Learning

Model-Free Dynamic Control of a 3-DoF Delta Parallel Robot f...

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RSI/ISM International Conference on Robotics and Mechatronics (ICROM)

作者： Hasan Jalali Saba Samadi Ahmad Kalhor Mehdi Tale Masouleh Human and Robot Interaction Laboratory School of Electrical and Computer Engineering University of Tehran Tehran Iran Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran

ISBN: (纸本)9781665454537

This article investigates the performance of the Delta robot using model-free controller. Since it is difficult to obtain an accurate dynamic model of the robot and identification methods are complex and challenging. Therefore, in this article, a new approach is presented which checks the performance of the Delta robot in pick-and-place operation using model-free dynamic controllers. For the purposes of this paper, Deep Reinforcement Learning (DRL) and also the Deep Deterministic Policy Gradient (DDPG) network is used. The DDPG algorithm is implemented for the first time on the Delta robot, and according to the obtained results, it reveals that it can provide a favorable approach for the pick-and-place operation. In this method, based on the science of DRL, a reward function based on the pick-and-place operation is also defined, which gives negative reward (punishment) or a positive reward according to the way the robot performs. It is noteworthy that according to the obtained results, it is possible to generalize other points for the pick-and-place operation. It should be noted that the robot was able to learn the target after a long episode and its graph converged after approximately 18,000 episodes.

关键词： Training Deep learning Parallel robots Actuators Mechatronics Heuristic algorithms Reinforcement learning

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Experimental Study on Motion controller based on NN-ARX and ARMAX Actuator Identification for 3-DoF Delta Parallel Robot

Experimental Study on Motion Controller based on NN-ARX and ...

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RSI/ISM International Conference on Robotics and Mechatronics (ICROM)

作者： Hasan Jalali Hossein Damavandi Ahmad Kalhor Mehdi Tale Masouleh Human and Robot Interaction Laboratory School of Electrical and Computer Engineering University of Tehran Tehran Iran Faculty of Computer Engineering and Information Technology Sadjad University Mashhad Iran Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran

Today, system identification plays a pivotal role in control science and offering a myriad of applications. This paper places its focus on the identification of actuator models within real-world delta robots for informing controller design. Two identification methods, namely NN-ARX and ARMAX, have been employed to extract the dynamic characteristics of the robot actuators, resulting in dynamic models of these integral components being derived. These dynamic models have been utilized in simulations for controller design, and due to the disparities in the identification models, distinct controllers have been realized. Subsequently, these controllers have been practically implemented on delta robots, and their performances have been subjected to a comprehensive comparative analysis. The results demonstrate that controllers integrating the identified actuator models outperformed those designed without the incorporation of the identification models. In practice, the implementation of controllers based on NN-ARX yielded the most favorable results among all the tested controllers. This research not only underscores the importance of accurate actuator models in control system design but also highlights the superior performance of neural network-based controllers in real-world robotic applications. In particular, the practical results of NN-ARX-based controllers were able to achieve significantly lower RMSE of 2.3562, 1.9531, and 2.1185 for the three motors, respectively, as opposed to the 4.1369, 3.0125, and 3.0363 achieved by the ARMAX-based controllers.

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Distributed formation control of networked mechanical systems

arXiv

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arXiv 2022年

作者： Javanmardi, Najmeh Borja, P. Yazdanpanah, M.J. Scherpen, J.M.A. Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Department of Cognitive Robotics Delft University of Technology Delft Netherlands Jan C. Wilems Center for Systems and Control ENTEG Faculty of Science and Engineering University of Groningen Groningen Netherlands

关键词： Networked control systems

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IsoCost-Based Dynamic Programming for Solving Infinite Horizon Optimal control Problems

arXiv

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arXiv 2022年

作者： Rahimi, Saeed Lafmejani, Amir Salimi Kalhor, Ahmad School of Mechanical Engineering University of Tehran Tehran Iran School of Electrical Computer and Energy Engineering Arizona State University United States Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran

An innovative numerical algorithm for solving infinite-horizon optimal control problems is introduced in this paper, using the IsoCost-HyperSurface (ICHS) concept. In the state space of an optimal control system, an ICHS is defined as a set of state points having a certain amount of the cost value. In this paper, it is proved that for a certain cost amount, the ICHS resulting from the infinite-horizon optimal control solution, surrounds all other ICHSs resulting from non-optimal control strategies. Regarding this geometric feature, the novel Isocost Dynamic Programming (IDP) algorithm is introduced to search for optimal control solutions. As an illustration of the introduced ICHS concepts and to demonstrate the effectiveness of the proposed IDP algorithm, several simulated examples are presented. The results are compared with those of conventional DP. These comparisons demonstrate that the proposed algorithm has better relative optimality compared to the DP algorithm with 18 % lower cumulative cost value, by comparing results from the closed-loop control of two nonlinear systems with random initial conditions. More significantly, when compared to the DP algorithm, the IDP was able to enhance computational performance by reducing the execution time by 21 % while using less *** Codes Dynamic programming in optimal control and differential games(49L20) © 2022, CC BY.

关键词： Dynamic programming

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Self-supervised denoising for multimodal structured illumination microscopy enables long-term super-resolution live-cell imaging

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PhotoniX 2024年第1期5卷 654-675页

作者： Xingye Chen Chang Qiao Tao Jiang Jiahao Liu Quan Meng Yunmin Zeng Haoyu Chen Hui Qiao Dong Li Jiamin Wu Department of Automation Tsinghua UniversityBeijing 100084China Research Institute for Frontier Science Beihang UniversityBeijing 100083China Institute for Brain and Cognitive Sciences Tsinghua UniversityBeijing 100084China National Laboratory of Biomacromolecules New Cornerstone Science LaboratoryCAS Center for Excellence in BiomacromoleculesInstitute of BiophysicsChinese Academy of SciencesBeijing 100101China College of Life Sciences University of Chinese Academy of SciencesBeijing 100049China Laboratory of Image Processing and Intelligent Control of Ministry of Education of China School of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China

Detection noise significantly degrades the quality of structured illumination microscopy(SIM)images,especially under low-light *** supervised learning based denoising methods have shown prominent advances in eliminating the noise-induced artifacts,the requirement of a large amount of high-quality training data severely limits their *** we developed a pixel-realignmentbased self-supervised denoising framework for SIM(PRS-SIM)that trains an SIM image denoiser with only noisy data and substantially removes the reconstruction *** demonstrated that PRS-SIM generates artifact-free images with 20-fold less fluorescence than ordinary imaging conditions while achieving comparable super-resolution capability to the ground truth(GT).Moreover,we developed an easy-to-use plugin that enables both training and implementation of PRS-SIM for multimodal SIM platforms including 2D/3D and linear/nonlinear *** PRS-SIM,we achieved longterm super-resolution live-cell imaging of various vulnerable bioprocesses,revealing the clustered distribution of Clathrin-coated pits and detailed interaction dynamics of multiple organelles and the cytoskeleton.

关键词： Super-resolution microscopy Structured illumination microscopy Deep learning Self-supervised learning Live-cell imaging

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Modification of a Herbal MRI Contrast Agent: Biological Effect and Relaxivity

Modification of a Herbal MRI Contrast Agent: Biological Effe...

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Iranian Conference of Biomedical Engineering (ICBME)

作者： Ali Yazdani Ahmadreza Okhovat Raheleh Doosti Maryam Saber Hamid Soltanian-Zadeh Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Central Herbarium School of Biology College of Science University of Tehran Tehran Iran College of Science University of Tehran Tehran Iran Department of Stem Cells and Developmental Biology Royan Institute for Stem Cell Biology and Technology Tehran Iran

We modified a modern herbal MRI contrast agent for biological applications. This modification was realized by omitting salinity and free ions of the contrast media. As a result, both the toxicity and the relaxivity of the product improved. We also chemically analyzed the modified agent and confirmed the elimination of some annoying free ions and molecules.

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Distributed Optimal Load Frequency control with Stochastic Wind Power Generation

Distributed Optimal Load Frequency Control with Stochastic W...

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European control Conference (ECC)

作者： Amirreza Silani Michele Cucuzzella Jacquelien M. A. Scherpen Mohammad Javad Yazdanpanah Jan C. Willems Center for Systems and Control ENTEG Faculty of Science and Engineering University of Groningen Groningen The Netherlands Control & Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran University of Pavia Pavia Italy

关键词： Renewable energy sources Wind speed Decentralized control Stochastic processes Doubly fed induction generators Differential equations Wind power generation

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