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Non-Square Inverse Function Jacobians in controlled Multibody systems: Numerical and Application Examples 7

Non-Square Inverse Function Jacobians in Controlled Multibod...

引用

7th international conference on Material Strength and Applied Mechanics, MSAM 2024

作者： Zelei, Ambrus Department of Whole Vehicle Engineering Audi Hungaria Faculty of Automotive Engineering Széchenyi István University Gyor Hungary

ISBN: (纸本)9781643685472

When control algorithms of robots are constructed, the joint coordinates and the coordinates describing the dynamics might be different and the transformation between them might be necessary in both directions. The back-and-forth transformations are related to the inverse function theorem, which is well understood for single and multivariable continuous functions: the conditions are described under which the inverse function exist, furthermore the method is provided to calculate the Jacobian of the inverse function. A generalization of the theorem is necessary, when there are fewer dependent variables than independent ones, and furthermore there are constraint equations for the independent variables. It is exactly the case for model-based inverse dynamics control of multibody systems, when the dynamic model is given in terms of a redundant coordinate set, but the controller is formulated for minimum set coordinates. The widely used so-called natural coordinates are a typical redundant set. Minimum-coordinates come in the picture when the control is formulated for the joint coordinates. Clearly, when the natural coordinates are transformed to joint coordinates, there is information loss. The inverse transformation is however still possible, since there are constraint equations for the redundant set. This paper demonstrates a method for the transformation from minimum to redundant coordinates and vice versa with the help of the generalized inverse of the non-square constraint Jacobian and the projection matrices related to the constrained and admissible subspace of the redundant set. An illustrative numerical example and a robotic application demonstrate the theory. The results are relevant in the model-based control of complex-structure parallel kinematic chain robots. © The Author(s), 2024.

关键词： Inverse problems

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Methods and Implementation Ideas for Mitigating Errors in complex systems Development

Methods and Implementation Ideas for Mitigating Errors in Co...

引用

Robotics, control and Automation (ICRCA), international conference on

作者： Ju Shichao Project Center. System Engineering and Project Management Research Team Shanghai Aircraft Design and Research Institute Shanghai China

ISBN: (数字)9798331544577

ISBN: (纸本)9798331544584

This paper analyzes the patterns of error discovery in aircraft development and the problems with current industry practices. It delves into the root causes, considering aspects such as issue recording, disciplinary fields, analytical verification, and personnel. It proposes a method for advancing the discovery of developmental issues and discusses the integration of assurance methods and review approaches, grounded in practical review practices.

关键词： Industries Automation Reviews Recording Personnel Aircraft complex systems Robots Aerospace control

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modeling Intelligent Traffic control System for Urban Agglomeration

Modeling Intelligent Traffic Control System for Urban Agglom...

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international conference on control systems, Mathematical Modelling, Automation and Energy Efficiency (SUMMA)

作者： Anatoly Pogodaev Vladimir Klyavin Anton Sysoev Galina Borovkova Svetlana Zhikhoreva Department of Applied Mathematics Lipetsk State Technical University Lipetsk Russia Research Institute Lipetsk State Technical University Lipetsk Russia

ISBN: (数字)9798331532178

ISBN: (纸本)9798331532185

This paper presents the modeling of an intelligent system for traffic control in urban agglomerations. The modeling process is complex and consists of several stages. The first step consists of modeling the capacity of urban transportation network using neural networks. The second step is to evaluate the level of traffic controllability using hierarchical sensitivity analysis. The third step involves classification of the transportation network using neuro- fuzzy classifier. All these stages precede managerial decisions on creation and regulation of traffic flows within the urban network.

关键词： Analytical models Sensitivity analysis Neural networks Transportation Traffic control Mathematical models Data models Regulation Safety Intelligent systems

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Digital Twin modeling Method for Assembly Quality control of complex Products 4

Digital Twin Modeling Method for Assembly Quality Control of...

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4th international conference on Circuits, systems and Simulation, ICCSS 2021

作者： Du, Rihuang Li, Guoxi Zhang, Meng Wang, Dong National University of Defense Technology College of Intelligence and Science Changsha China

ISBN: (纸本)9781728167527

Digital twin technology can realize the integration and iterative optimization between the physical model and information model of complex products through real-time data collection, data integration and monitoring, thereby shortening the product development cycle and improving the product quality. Aiming at the problems of insufficient predictability of quality control in the assembly process of complex products, timeliness of quality control and weak systematicity, this paper applied the digital twin to the quality control of the complex products assembly process and analyzed the research progress of the digital twin technology. From the perspective of the whole process of product assembly, it discussed the information expression and model integration of the digital twin model of the assembly process and studied the typical characteristics of the digital twin model's multi-level and multi-dimensional and the modeling process of the model. The equipment, materials, process, environment, and other elements of the company are modeled, and the problem of the coordinated operation of multi-disciplinary models in the assembly process of complex products is solved by optimizing the model of the assembly quality control of complex products. A case verified the feasibility of the proposed digital twin modeling method. © 2021 IEEE.

关键词： Data integration

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ICAC 2023 - 28th international conference on Automation and Computing

ICAC 2023 - 28th International Conference on Automation and ...

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28th international conference on Automation and Computing, ICAC 2023

ISBN: (纸本)9798350335859

The proceedings contain 126 papers. The topics discussed include: data-driven prediction of polymer intrinsic viscosity with incomplete time series data;a joint order cost optimization model for multi-item spare parts manufacturing systems considering the requirement of support;ultimately bounded state estimation for discrete-time singularly perturbed complex networks under bit rate constraints;an expert data generation method for multi-agent cooperative planning method;robotic machining: status, challenges and future trends;an overview of path planning for autonomous robots in smart manufacturing;heuristic data-driven adaptive model predictive control strategy;ontology-based product modeling for disassembly sequence planning in remanufacturing;applying and exploring supervised contrastive regression for vision-based steering prediction;and procurement practices influencing availability of drugs at public healthcare facilities.

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Foundations of Probabilistic Behavior Networks Aiming for Structured, Distributed control of complex systems like Legged Robots

Foundations of Probabilistic Behavior Networks Aiming for St...

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IEEE/RAS-EMBS international conference on Biomedical Robotics and Biomechatronics (BioRob)

作者： Patrick Vonwirth Oleksandr Sivak Karsten Berns Department of Computer Science RPTU Kaiserslautern-Landau Kaiserslautern Germany

ISBN: (数字)9798350386523

ISBN: (纸本)9798350386530

Advancements in legged robotics permanently push modern control approaches to their manageability and computational limits. To overcome these barriers, computer scientists rely on the well-known principle of divide and conquer, e.g., behavior-based control decomposition. Unfortunately, existing behavioral frameworks do not offer validatable math-ematical structures. However, in the highly dynamic, complex, and high-dimensional context of legged robotics, an algebraic structure is required to guarantee mathematical properties modeling control features or system behaviors. Interestingly, the human nervous system is a promising blueprint to achieve those requirements. Inspired by that, this work introduces a new theoretical foundation for well-structured behavioral control, the Probabilistic Behavior Network (PBN). The support of state-of-the-art robotic technology within the PBNs is discussed.

关键词： Legged locomotion Computational modeling Decentralized control Biomechatronics Probabilistic logic Nervous system Mathematical models complex systems Robots Context modeling

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Multimodal Biometric Authentication systems: Exploring Iris and EEG Data

Multimodal Biometric Authentication Systems: Exploring Iris ...

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Cyber Resilience (ICCR), international conference on

作者： Elyazia Baha Abdulla Fadhel Patricia Buenaventura Chan Yeob Yeun Jamal Zemerly Khouloud Eldelbi Department of Computer Science Khalifa University Abu Dhabi United Arab Emirates

ISBN: (数字)9798350394962

ISBN: (纸本)9798350394979

Authentication systems are usually classified depending on the types of characteristics they use. Biometric authentication systems rely on biological characteristics that can be unique to the individual for identification or verification purposes. Multimodal biometric authentication systems utilize multiple biometric features to improve accuracy, offset noise in collected data, or improve the trust factor of the system. As biometric data becomes more complex, many studies explored the use of deep learning and machine learning to train models that can identify or verify individuals. One of the concerns with such implementations is that they can operate as black-box solutions, which is where explainable AI (XAI) becomes favorable. This paper is an overview of the differences between unimodality and multimodality in biometric authentication systems, the identification and verification problems, deep learning and machine learning, explainable AI (XAI), and various implementations of iris and EEG data in biometric authentication systems.

关键词： Deep learning Biometrics (access control) Explainable AI Biological system modeling Noise Authentication Brain modeling

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Dynamic Phasor-Based Small-Signal modeling of DFIG

Dynamic Phasor-Based Small-Signal Modeling of DFIG

引用

2023 international conference on Power System Technology, PowerCon 2023

作者： Guo, Xiaolong Wang, Xiaodong Zhang, Hao Kang, Pengpeng Song, Pengfei Chen, Wuhui State Grid Xinjiang Electric Power Company Urumchi China Taiyuan University of Technology Power System Operation and Control Laboratory Taiyuan China

ISBN: (纸本)9798350300222

As the share of wind power in the power system increases, the grid-connected wind farms may affect the complex high-frequency harmonics dynamics. When the conventional wind turbine transient model is used, it is difficult to accurately reflect the complex high-frequency dynamics of the power systems with a high wind penetration rate. The dynamic phasor (DP) model can convert time-domain signals to a sum of time-varying sets of Fourier series, thus improving the accuracy of power system models in capturing complex high-frequency dynamics. In this paper, a DP-based small-signal modeling of doubly fed induction generator (DFIG) to investigate the complex high-frequency dynamics. The DP-based small-signal model of the DFIG is built. Then, the modal analysis is implemented by using the developed DP-based small-signal model. The effect of mechanical and electrical parameter changes on the small-signal stability of the DFIG grid-connected system is studied. The results show that, compared to the dq-axis model, the DP-based model can observe the modes corresponding to high-frequency harmonics. The mechanical parameters of wind turbines have a significant impact on the shaft system mode, while the electrical parameters almost have impacts on the damping of all modes. When designing a DFIG, appropriately increasing the resistance value of the stator and rotor is beneficial for improving the small signal stability of the system, while the leakage inductance value of the stator and rotor should not be designed too large. © 2023 IEEE.

关键词： Stators

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modeling and control Design of an Activated Sludge Process: a Multi-Model Approach 21

Modeling and Control Design of an Activated Sludge Process: ...

引用

21st IEEE international conference on Sciences and Techniques of Automatic control and Computer Engineering, STA 2022

作者： Dhouibi, Saida Bouallegue, Soufiene Le Belvéd re Tunis1002 Tunisia Gabes6032 Tunisia

ISBN: (纸本)9781665482615

Wastewater treatment systems, especially those using biochemical processes, present recently new challenges resulting from the growing awareness of environmental risks. In this paper, a multi-model-based method is proposed and successfully applied for modeling and control design of an Activated Sludge Plant (ASP). A quasi Linear Parameter-Varying (LPV) representation of such a wastewater treatment system is firstly established to build a corresponding multi-model by the use of a convex polytopic transformation. Such a global ASP's multi-model structure is then used to design state-feedback controllers based on the Parallel Distributed Compensation (PDC) formalism. Local control laws for the modeled dynamics, i.e. effluent volume and concentrations of the heterotrophic biomass, the biodegradable substrate and the dissolved oxygen are merged to obtain global PDC control laws stabilizing these nonlinear variables. Simulation results are effectuated to show the validity and efficiency of the proposed multi-model-based modeling and control approach for such a complex biochemical process. © 2022 IEEE.

关键词： Dissolved oxygen

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Machine Learning Based Multiple Impedance control of a Space Free-Flying Robot

Machine Learning Based Multiple Impedance Control of a Space...

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RSI/ISM international conference on Robotics and Mechatronics (ICROM)

作者： Amirhossein Safdari Payam Zarafshan Khalil Alipour Bahram Tarvirdizadeh Gu Fang Department of Mechatronics Engineering School of Intelligent Systems Engineering College of Interdisciplinary Science and Technology University of Tehran Tehran Iran School of Engineering Design and Built Environment Western Sydney University Sydney Australia

ISBN: (数字)9798331529734

ISBN: (纸本)9798331529741

This study investigates the application of Machine Learning (ML) to reduce the inherent computational burden in Multiple Impedance control (MIC) for robotic systems. Impedance control (IC) is a powerful method for robots to interact with their environment by simultaneously controlling position and force. However, the increasing complexity of control methods such as MIC requires more and more complex computations, which can lead to problems such as increased response time and reduced efficiency in the control system, making implementation on the controller impractical. To address this challenge, this paper proposes a new ML-based method called ML-MIC. This method aims to reduce the computational complexity associated with MIC using ML techniques, thereby improving the efficiency and speed of robotic control systems. The development of ML-MIC not only leads to improved control system performance but also enables more effective implementation of robotic and mechatronic systems.

关键词： Microwave integrated circuits Adaptation models Mechatronics Accuracy Machine learning algorithms Computational modeling control systems Stability analysis Impedance Robots

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