A Dual Fuzzy-Enhanced Neurodynamic Scheme for Model-Less Kinematic Control of Redundant and Hyperredundant Robots
Tracking control of redundant and hyperredundant manipulators is a fundamental and critical problem in practical applications. In order to effectively decrease the end-effector position errors, a novel dual fuzzy-enhanced neurodynamic (DFEN) scheme is put forward for solving the position error accum...
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| Veröffentlicht in: | IEEE transactions on fuzzy systems 2022-10, Vol.30 (10), p.4409-4422, Article 4409 |
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| container_title | IEEE transactions on fuzzy systems |
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| creator | Tan, Ning Ye, Zixiao Yu, Peng Ni, Fenglei |
| description | Tracking control of redundant and hyperredundant manipulators is a fundamental and critical problem in practical applications. In order to effectively decrease the end-effector position errors, a novel dual fuzzy-enhanced neurodynamic (DFEN) scheme is put forward for solving the position error accumulation problem followed by achieving accurate tracking control results. The proposed scheme is established based on a zeroing neurodynamic approach in conjunction with two fuzzy adjustment units that are capable of tuning the control parameters by monitoring the tracking error. Moreover, the DFEN scheme can effectively solve the tracking problem without requiring knowing a priori knowledge of the kinematic model of the robot. The convergence and the stability of the proposed approach are demonstrated by theoretical analysis. The effectiveness, accuracy, and robustness of the proposed DFEN scheme are verified on the simulative redundant manipulator, continuum robot, and hybrid robot (integrating the redundant manipulator and the continuum robot). A practical experiment is provided to validate the proposed scheme as well. |
| doi_str_mv | 10.1109/TFUZZ.2022.3152077 |
| format | Article |
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In order to effectively decrease the end-effector position errors, a novel dual fuzzy-enhanced neurodynamic (DFEN) scheme is put forward for solving the position error accumulation problem followed by achieving accurate tracking control results. The proposed scheme is established based on a zeroing neurodynamic approach in conjunction with two fuzzy adjustment units that are capable of tuning the control parameters by monitoring the tracking error. Moreover, the DFEN scheme can effectively solve the tracking problem without requiring knowing a priori knowledge of the kinematic model of the robot. The convergence and the stability of the proposed approach are demonstrated by theoretical analysis. The effectiveness, accuracy, and robustness of the proposed DFEN scheme are verified on the simulative redundant manipulator, continuum robot, and hybrid robot (integrating the redundant manipulator and the continuum robot). 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In order to effectively decrease the end-effector position errors, a novel dual fuzzy-enhanced neurodynamic (DFEN) scheme is put forward for solving the position error accumulation problem followed by achieving accurate tracking control results. The proposed scheme is established based on a zeroing neurodynamic approach in conjunction with two fuzzy adjustment units that are capable of tuning the control parameters by monitoring the tracking error. Moreover, the DFEN scheme can effectively solve the tracking problem without requiring knowing a priori knowledge of the kinematic model of the robot. The convergence and the stability of the proposed approach are demonstrated by theoretical analysis. The effectiveness, accuracy, and robustness of the proposed DFEN scheme are verified on the simulative redundant manipulator, continuum robot, and hybrid robot (integrating the redundant manipulator and the continuum robot). A practical experiment is provided to validate the proposed scheme as well.</description><subject>Adaptation models</subject><subject>End effectors</subject><subject>Fuzzy control</subject><subject>Fuzzy control system</subject><subject>Fuzzy logic</subject><subject>Kinematics</subject><subject>Manipulators</subject><subject>model free</subject><subject>Neurodynamics</subject><subject>Position errors</subject><subject>Redundancy</subject><subject>Robot arms</subject><subject>Robot control</subject><subject>robot manipulators</subject><subject>Robots</subject><subject>Stability analysis</subject><subject>Tracking control</subject><subject>Tracking errors</subject><subject>Tracking problem</subject><subject>Trajectory tracking</subject><subject>unknown models</subject><subject>zeroing neurodynamics</subject><issn>1063-6706</issn><issn>1941-0034</issn><issn>1941-0034</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNp9kMtOwzAQRSMEEs8fgI0l1il-xU6WVaEUUUDisWETOfZETZXarZ0s0q_HpYgFC1YzujN3ruYkySXBI0JwcfM-_fj8HFFM6YiRjGIpD5ITUnCSYsz4YeyxYKmQWBwnpyEsMSY8I_lJshmj2161aNpvt0N6ZxfKajDoGXrvzGDVqtHoTS9gBah2Hj05A206hxDQY2Nhpbo4nzjbedciV6NXML01ynZIWYNmwxq8_5VeXeW6cJ4c1aoNcPFTz5KP6d37ZJbOX-4fJuN5qmmRdakGzLTBWaG04qKuFM1AVqJgQvA6r3LFWB5FqQotgPC8IhnPM0WkkVRVhrOz5Hp_d-3dpofQlUvXexsjSyop4YxJIuIW3W9p70LwUJdr36yUH0qCyx3a8httuUNb_qCNpvyPSTddRLHjoJr2f-vV3toAwG9WIeMHcfoFW3CIfQ</recordid><startdate>20221001</startdate><enddate>20221001</enddate><creator>Tan, Ning</creator><creator>Ye, Zixiao</creator><creator>Yu, Peng</creator><creator>Ni, Fenglei</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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In order to effectively decrease the end-effector position errors, a novel dual fuzzy-enhanced neurodynamic (DFEN) scheme is put forward for solving the position error accumulation problem followed by achieving accurate tracking control results. The proposed scheme is established based on a zeroing neurodynamic approach in conjunction with two fuzzy adjustment units that are capable of tuning the control parameters by monitoring the tracking error. Moreover, the DFEN scheme can effectively solve the tracking problem without requiring knowing a priori knowledge of the kinematic model of the robot. The convergence and the stability of the proposed approach are demonstrated by theoretical analysis. The effectiveness, accuracy, and robustness of the proposed DFEN scheme are verified on the simulative redundant manipulator, continuum robot, and hybrid robot (integrating the redundant manipulator and the continuum robot). 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| identifier | ISSN: 1063-6706 |
| ispartof | IEEE transactions on fuzzy systems, 2022-10, Vol.30 (10), p.4409-4422, Article 4409 |
| issn | 1063-6706 1941-0034 1941-0034 |
| language | eng |
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| source | IEEE Electronic Library (IEL) |
| subjects | Adaptation models End effectors Fuzzy control Fuzzy control system Fuzzy logic Kinematics Manipulators model free Neurodynamics Position errors Redundancy Robot arms Robot control robot manipulators Robots Stability analysis Tracking control Tracking errors Tracking problem Trajectory tracking unknown models zeroing neurodynamics |
| title | A Dual Fuzzy-Enhanced Neurodynamic Scheme for Model-Less Kinematic Control of Redundant and Hyperredundant Robots |
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