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Set-Membership adaptive robot control With Deterministically Bounded Learning Gains

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2023年第8期19卷 8564-8574页

作者： Guo, Kai Zhang, Zekun Zheng, Dong-Dong Sun, Jie Shandong Univ Sch Mech Engn Jinan 250061 Peoples R China Shandong Univ Key Lab High Efficiency & Clean Mech Manu Facture Minist Educ Jinan 250061 Peoples R China Shandong Univ Natl Demonstrat Ctr Expt Mech Engn Educ Jinan 250061 Peoples R China Beijing Inst Technol Sch Automat Beijing 100081 Peoples R China

As a powerful set-membership adaptive identification algorithm, the optimal bounded ellipsoid (OBE) enables fast convergence speeds because it exploits a priori information about system dynamics by estimating sets of feasible solutions rather than single-point solutions. However, its learning gain matrix suffers from vanishing or unbounded growth, which seriously limits its practical performance. In this article, a novel OBE algorithm is proposed to ensure that the learning gain matrix is constrained by upper and lower bounds, which are unaffected by the hardly predictable excitation levels and can be determined before implementing the algorithm. Thus, the system robustness and tracking capability for time-varying dynamics can be improved. In light of the proposed OBE identification algorithm, an adaptive robot control strategy is further proposed, where the robot dynamics are reconstructed through neural networks. The practical partial asymptotic stability of the closed-loop system is demonstrated using the Lyapunov method. Furthermore, noisy acceleration signals and the inversion of the inertial matrix are eliminated with the proposed control strategy. Experimental results on a robot manipulator validate the effectiveness of the proposed approach.

关键词： adaptive robot control neural network (NN) approximation parameter identification robot manipulator

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adaptive robot control AS A SERVICE IN CLOUD MANUFACTURING

ADAPTIVE ROBOT CONTROL AS A SERVICE IN CLOUD MANUFACTURING

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10th ASME International Manufacturing Science and Engineering Conference (MSEC2015)

作者： Adamson, Goran Wang, Lihui Holm, Magnus Moore, Philip Univ Skovde Virtual Syst Res Ctr S-54128 Skovde Sweden Royal Inst Technol Dept Prod Engn S-10044 Stockholm Sweden Falmouth Univ Acad Innovat & Res Penryn TR10 9EZ Cornwall England

ISBN: (纸本)9780791856833

The interest for implementing the concept of Manufacturing-as-a-Service is increasing as concepts for letting the manufacturing shop-floor domain take advantage of the cloud appear. Combining technologies such as Internet of Things, Cloud Computing, Semantic Web, virtualisation and service-oriented technologies with advanced manufacturing models, information and communication technologies, Cloud Manufacturing is emerging as a new manufacturing paradigm. The ideas of on-demand, scalable and pay-for-usage resource-sharing in this concept will move manufacturing towards distributed and collaborative missions in volatile partnerships. This will require a control approach for distributed planning and execution of cooperating manufacturing activities. Without control based on both global and local environmental conditions, the advantages of Cloud Manufacturing will not be fulfilled. By utilising smart and distributable decision modules such as event-driven Function Blocks, run-time manufacturing operations in a. distributed environment may be adjusted to prevailing manufacturing conditions. Packaged in a cloud service for manufacturing equipment control, they will satisfy the control needs. By combining different resource types, such as hard, soft and capability resources, the cloud service robot control-as-a-Service can be realised. This paper describes the functional perspective and enabling technologies for a distributed control approach for robotic assembly tasks in Cloud Manufacturing.

关键词： Cloud manufacturing adaptive robot control service

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Composite adaptation and learning for robot control: A survey

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ANNUAL REVIEWS IN control 2023年 55卷 279-290页

作者： Guo, Kai Pan, Yongping Shandong Univ Sch Mech Engn Jinan 250061 Peoples R China Sun Yat sen Univ Sch Adv Mfg Shenzhen 518100 Peoples R China

Composite adaptation and learning techniques were initially proposed for improving parameter convergence in adaptive control and have generated considerable research interest in the last three decades, inspiring numerous robot control applications. The key idea is that more sources of parametric information are applied to drive parameter estimates aside from trajectory tracking errors. Both composite adaptation and learning can ensure superior stability and performance. However, composite learning possesses a unique feature in that online data memory is fully exploited to extract parametric information such that parameter convergence can be achieved without a stringent condition termed persistent excitation. In this article, we provide the first systematic and comprehensive survey of prevalent composite adaptation and learning approaches for robot control, especially focusing on exponential parameter convergence. Composite adaptation is classified into regressor-filtering composite adaptation and error-filtering composite adaptation, and composite learning is classified into discrete-data regressor extension and continuous-data regressor extension. For the sake of clear presentation and better understanding, a general class of robotic systems is applied as a unifying framework to show the motivation, synthesis, and characteristics of each parameter estimation method for adaptive robot control. The strengths and deficiencies of all these methods are also discussed sufficiently. We have concluded by suggesting possible directions for future research in this area.

关键词： Learning adaptive control Data-driven control adaptive robot control Neural network learning Parameter estimation Parameter convergence Exponential stability

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A singular perturbation based adaptive strategy for bounded controller design in feedback linearizable systems

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INTERNATIONAL JOURNAL OF adaptive control AND SIGNAL PROCESSING 2022年第2期36卷 264-281页

作者： Rayguru, Madan Mohan Ramalingam, Balakrishnan Elara, Mohan Rajesh Delhi Technol Univ Dept Elect Engn Room FW14 SF Delhi 110042 India Singapore Univ Technol & Design Engn Prod Dev Upper Changi Singapore

The saturation of actuators is a critical issue in numerous industrial and robotic applications. The article presents a singular perturbation based adaptive control technique for solving the tracking problem in uncertain feedback linearizable systems. A high gain dynamic controller technique is utilized to enforce time scale separation and facilitating dynamic inversion. The resulting closed loop singularly perturbed system is proved to be partially contracting, and the existence of a unique isolated slow manifold is assured via contraction technique. The parameter adaptation ensures uncertainties compensation and subsequently bounded tracking performance. Further, the technique is extended for multi input multi output systems like mobile robots. The numerical simulations present the usability of the proposed methodology and its effectiveness.

关键词： actuator saturation adaptive robot control contraction theory MIMO systems singular perturbation

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Composite-Learning-Based adaptive Neural control for Dual-Arm robots With Relative Motion

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IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2022年第3期33卷 1010-1021页

作者： Jiang, Yiming Wang, Yaonan Miao, Zhiqiang Na, Jing Zhao, Zhijia Yang, Chenguang Hunan Univ Natl Engn Lab Robot Visual Percept & Control Changsha 410082 Peoples R China Kunming Univ Sci & Technol Fac Mech & Elect Engn Kunming 650093 Yunnan Peoples R China Guangzhou Univ Sch Mech & Elect Engn Guangzhou 510006 Peoples R China Univ West England Bristol Robot Lab Bristol BS16 1QY Avon England

This article presents an adaptive control method for dual-arm robot systems to perform bimanual tasks under modeling uncertainties. Different from the traditional symmetric bimanual robot control, we study the dual-arm robot control with relative motions between robotic arms and a grasped object. The robot system is first divided into two subsystems: a settled manipulator system and a tool-used manipulator system. Then, a command filtered control technique is developed for trajectory tracking and contact force control. In addition, to deal with the inevitable dynamic uncertainties, a radial basis function neural network (RBFNN) is employed for the robot, with a novel composite learning law to update the NN weights. The composite learning is mainly based on an integration of the historic data of NN regression such that information of the estimate error can be utilized to improve the convergence. Moreover, a partial persistent excitation condition is employed to ensure estimation convergence. The stability analysis is performed by using the Lyapunov theorem. Numerical simulation results demonstrate the validity of the proposed control and learning algorithm.

关键词： robots robot kinematics Artificial neural networks Convergence Trajectory Task analysis Force adaptive robot control bimanual robot composite learning neural network relative motion

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Whole-Body control of a Mobile Manipulator for Passive Collaborative Transportation 13

Whole-Body Control of a Mobile Manipulator for Passive Colla...

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13th IFAC Symposium on robot control (SYROCO)

作者： Benzi, F. Mancus, C. Secchi, C. Univ Modena & Reggio Emilia Dept Sci & Methods Engn Modena Italy

ISBN: (纸本)9781713867890

Human-robot collaborative tasks foresee interactions between humans and robots with various degrees of complexity. Specifically, for tasks which involve physical contact among the agents, challenges arise in the modelling and control of such interaction. In this paper we propose a control architecture capable of ensuring a flexible and robustly stable physical human-robot interaction, focusing on a collaborative transportation task. The architecture is deployed onto a mobile manipulator, modelled as a whole-body structure, which aids the operator during the transportation of an unwieldy load. Thanks to passivity techniques, the controller adapts its interaction parameters online while preserving robust stability for the overall system, thus experimentally validating the architecture. Copyright (c) 2022 The Authors. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0/)

关键词： Forcel Compliance control adaptive robot control Robust robot control Haptic Interaction Physical Human-robot Interaction

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Whole-Body control of a Mobile Manipulator for Passive Collaborative Transportation

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IFAC-PapersOnLine 2022年第38期55卷 106-112页

作者： F. Benzi C. Mancus C. Secchi

关键词： Forcel Compliance control adaptive robot control Robust robot control Haptic Interaction Physical Human-robot Interaction

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Light automation for aircraft fuselage assembly

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AERONAUTICAL JOURNAL 2020年第1272期124卷 216-236页

作者： Trabasso, L. G. Mosqueira, G. L. Aeronaut Inst Technol Sao Jose Dos Campos Brazil Eletroimpact Brazil Jacarei Brazil

The ever-growing need to improve manufacturing processes has led recently to an increase in the number of automation solutions used to assemble aircraft structural elements. A process of interest to this industry is the alignment of fuselage sections, which is currently done either manually or by complex, expensive automated systems. The manual method introduces a significant production delay and most automated systems have limited flexibility. This article presents an integration solution implemented in an alternative low-cost, high-flexibility alignment robotic cell. The performance of an optical coordinate measuring machine (CMM) as feedback source for the adaptive control of a conventional industrial manipulator is assessed. Laser interferometry readings are used as reference. The contribution of the work lies in the execution of experiments based on the EN ISO 9283 standard (Manipulating industrial robots - performance criteria and related test methods) to determine the adequacy of the commercial off-the-shelf system to the tolerances and requirements of the fuselage alignment process at hand. The optimal configuration of the integrated system attained the nominal alignment position with an average accuracy of 0.16mm and 0.004 degrees, partially meeting the required tolerances, and the obtained values are nearly 16x better compared to a baseline, open-loop manipulator. These results serve as reference for the aerospace industry in the development of the next generation of tools and automated assembly processes.

关键词： Aircraft assembly fuselage alignment adaptive robot control EN ISO 9283

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FEATURE-BASED adaptive MANUFACTURING EQUIPMENT control FOR CLOUD ENVIRONMENTS 11

FEATURE-BASED ADAPTIVE MANUFACTURING EQUIPMENT CONTROL FOR C...

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11th ASME International Manufacturing Science and Engineering Conference (MSEC)

ISBN: (纸本)9780791849903

The ideas of on-demand, scalable and pay-for-usage resource-sharing in Cloud Manufacturing are steadily attracting more interest. For implementing the concept of Manufacturing as-a-Service in a cloud environment, description models and implementation language for resources and their capabilities are required. A standardized approach for systemived virtualization, servisilisation, retrieval, selection and composition into higher levels of functionality is necessary. For the collaborative sharing and use of networked manufacturing resources there is also a need for a control approach for distributed manufacturing equipment. In this paper, the technological perspective for an adaptive cloud service-based control approach is described, and a supporting information model for its implementation. The control is realized through the use of a network of intelligent and distributable Function Block decision modules, enabling run-time manufacturing activities to be performed according to actual manufacturing conditions. The control system's integration to the cloud service management functionality is described, as well as a feature-level capability model and the use of ontologies and the Semantic Web.

关键词： Cloud manufacturing adaptive robot control ontology

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Analysis of the indoor GPS system as feedback for the robotic alignment of fuselages using laser radar measurements as comparison

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robotICS AND COMPUTER-INTEGRATED MANUFACTURING 2012年第6期28卷 700-709页

作者： Mosqueira, G. Apetz, J. Santos, K. M. Villani, E. Suterio, R. Trabasso, L. G. ITA Aircraft Struct Assembly Automat Lab ASAA Lab BR-12228900 Sao Paulo Brazil Rhein Westfal TH Aachen WZL Aachen Germany INPE Natl Inst Space Res Integrat & Test Lab Sao Paulo Brazil

The alignment of aircraft fuselages in the aerospace sector is currently done either manually or by complex, expensive automated systems. The manual process introduces a significant production delay and the automated systems are purpose-built and have limited flexibility, apart from its financial drawback. This work proposes a low-cost, high-flexibility system and, as part of it, evaluates the performance of a Rotary-Laser Automatic Theodolite (R-LAT) as a feedback source for the adaptive robot control of an anthropomorphic manipulator. In the proposed solution the robot carries a fuselage barrel and aligns it with respect to a second barrel. A high accuracy, frequency-modulated laser equipment is used to generate the reference system for the procedure. The measurements of the R-LAT are then verified with the frequency-modulated laser equipment in order to determine the linear and angular alignment tolerances achieved by the robot/R-LAT closed loop in a predefined work envelope. A throughout, step-by-step analysis of the measuring procedure is carried out to allow the recognition of error sources and thus the determination of an optimized method. These results identify the operation boundaries of the R-LAT within the process and yield its best configuration for the intended purpose. Using the EN ISO 9283 robot evaluation standard, the closed loop system was found to attain the nominal position with an average accuracy of 0.38 mm and 0.01 degrees, contrasting with an average accuracy of 4.53 mm and 0.21 degrees when the robot was operating in an open loop configuration. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： iGPS Laser radar R-LAT adaptive robot control Industrial manipulators Fuselage alignment EN ISO 9283

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