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QFT Robust Control Design for 3-Axis Flight Table Servo System with Large Friction 被引量:3
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作者 刘金琨 尔联洁 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2004年第1期34-38,共5页
The 3-axis flight table is an important device and a typical high performanceposition and speed servo system used in the hardware-in-the-loop simulation of flight controlsystem. Friction force and uncertainty are the ... The 3-axis flight table is an important device and a typical high performanceposition and speed servo system used in the hardware-in-the-loop simulation of flight controlsystem. Friction force and uncertainty are the main characteristics in the 3-axis flight table servosystem. Based on the description of dynamic and static model of a nonlinear Stribeck frictionmodel, and taking account of the practical uncertainties of 3-axis flight table servo system, theQFT controller is designed. Simulation and realtime results are presented. 展开更多
关键词 quantitative feedback theory 3-axis flight table friction model ROBUSTCONTROL
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Adaptive-backstepping force/motion control for mobile-manipulator robot based on fuzzy CMAC neural networks 被引量:2
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作者 Thang-Long MAI Yaonan WANG 《Control Theory and Technology》 EI CSCD 2014年第4期368-382,共15页
In this paper, an adaptive backstepping fuzzy cerebellar-model-articulation-control neural-networks control (ABFCNC) system for motion/force control of the mobile-manipulator robot (MMR) is proposed. By applying t... In this paper, an adaptive backstepping fuzzy cerebellar-model-articulation-control neural-networks control (ABFCNC) system for motion/force control of the mobile-manipulator robot (MMR) is proposed. By applying the ABFCNC in the tracking-position controller, the unknown dynamics and parameter variation problems of the MMR control system are relaxed. In addition, an adaptive robust compensator is proposed to eliminate uncertainties that consist of approximation errors, uncertain disturbances. Based on the tracking position-ABFCNC design, an adaptive robust control strategy is also developed for the nonholonomicconstraint force of the MMR. The design of adaptive-online learning algorithms is obtained by using the Lyapunov stability theorem. Therefore, the proposed method proves that it not only can guarantee the stability and robustness but also the tracking performances of the MMR control system. The effectiveness and robustness of the proposed control system are verified by comparative simulation results. 展开更多
关键词 Backstepping control Fuzzy CMAC (cerebellar model articulation controller) neural networks Adaptive robustcontrol Mobile-manipulator robot
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