MOTION CONTROL STRATEGY OF A ROBOTIC MANIPULATOR WITH FLEXIBLE JOINTS BASED ON FUZZY CONTROL

2015 ◽  
Author(s):  
Karina Assolari Takano ◽  
Fabian Andres Lara Molina ◽  
Edson Hideki Koroishi
Keyword(s):  
Fuzzy Control ◽  
Motion Control ◽  
Control Strategy ◽  
Robotic Manipulator ◽  
Flexible Joints

Fuzzy Control Strategy and Simulation for Dual Electric Tracked Vehicle Motion Control

2011 ◽  
Vol 130-134 ◽  
pp. 309-312 ◽  
Author(s):  
Ze Yu Chen ◽  
Guang Yao Zhao
Keyword(s):  
Fuzzy Control ◽  
Motion Control ◽  
Control Strategy ◽  
Feedback Signal ◽  
Tracked Vehicle ◽  
Straight Line ◽  
Control Section ◽  
Vehicle Motion ◽  
Fuzzy Control Strategy ◽  
Braking Control

Based on tracked vehicle dynamics analysis, a fuzzy control strategy is proposed in this paper for the dual electric tracked vehicle motion control. The inputs of fuzzy system are driver acceleration, braking and steering signals besides vehicle velocity feedback signal, while outputs are dual motors’ torque commands and mechanical braker’s target force. Control strategy contains two fuzzy logics, one is for steering and straight-line running control, the other is for braking control section. Simulation results show that the fuzzy control strategy presented here is correct and effective for electric tracked vehicle motion control.

Triboelectric Self-Powered Wearable Flexible Patch as 3D Motion Control Interface for Robotic Manipulator

ACS Nano ◽  
2018 ◽  
Vol 12 (11) ◽  
pp. 11561-11571 ◽  
Author(s):  
Tao Chen ◽  
Qiongfeng Shi ◽  
Minglu Zhu ◽  
Tianyiyi He ◽  
Lining Sun ◽  
...  
Keyword(s):  
Motion Control ◽  
Robotic Manipulator ◽  
3D Motion ◽  
Control Interface ◽  
Self Powered

Loading path prediction for tube hydroforming process using a fuzzy control strategy

2008 ◽  
Vol 29 (6) ◽  
pp. 1110-1116 ◽  
Author(s):  
Shu-hui Li ◽  
Bing Yang ◽  
Wei-gang Zhang ◽  
Zhong-qin Lin
Keyword(s):  
Fuzzy Control ◽  
Control Strategy ◽  
Tube Hydroforming ◽  
Loading Path ◽  
Hydroforming Process ◽  
Path Prediction ◽  
Fuzzy Control Strategy

scholarly journals Fuzzy Control Model and Simulation for Nonlinear Supply Chain System with Lead Times

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Songtao Zhang ◽  
Yanting Hou ◽  
Siqi Zhang ◽  
Min Zhang
Keyword(s):  
Supply Chain ◽  
Fuzzy Control ◽  
Control Strategy ◽  
Control Model ◽  
Lead Times ◽  
Supply Chain System ◽  
Chain System ◽  
Model And Simulation ◽  
Definition Of ◽  
System Variables

A new fuzzy robust control strategy for the nonlinear supply chain system in the presence of lead times is proposed. Based on Takagi-Sugeno fuzzy control system, the fuzzy control model of the nonlinear supply chain system with lead times is constructed. Additionally, we design a fuzzy robust H∞ control strategy taking the definition of maximal overlapped-rules group into consideration to restrain the impacts such as those caused by lead times, switching actions among submodels, and customers’ stochastic demands. This control strategy can not only guarantee that the nonlinear supply chain system is robustly asymptotically stable but also realize soft switching among subsystems of the nonlinear supply chain to make the less fluctuation of the system variables by introducing the membership function of fuzzy system. The comparisons between the proposed fuzzy robust H∞ control strategy and the robust H∞ control strategy are finally illustrated through numerical simulations on a two-stage nonlinear supply chain with lead times.

scholarly journals Decentralised coordinated energy management for hybrid AC/DC microgrid by using fuzzy control strategy

2020 ◽  
Vol 14 (14) ◽  
pp. 2649-2656
Author(s):  
Zeyan Lv ◽  
Yong Zhang ◽  
Miao Yu ◽  
Yanghong Xia ◽  
Wei Wei
Keyword(s):  
Fuzzy Control ◽  
Energy Management ◽  
Control Strategy ◽  
Dc Microgrid ◽  
Fuzzy Control Strategy

HIL Testbed and Motion Control Strategy for the Hybrid Hydraulic-Electric Architecture (HHEA)

2021 ◽  
Author(s):  
Arpan Chatterjee ◽  
Perry Y. Li
Keyword(s):  
Motion Control ◽  
Control Strategy ◽  
Control Strategies ◽  
Electric Machines ◽  
Hardware In The Loop ◽  
System Efficiency ◽  
Electric Motors ◽  
Test Bed ◽  
Road Vehicles ◽  
Precise Control

Abstract The Hybrid Hydraulic-Electric Architecture (HHEA) was proposed in recent years to increase system efficiency of high power mobile machines and to reap the benefits of electrification without the need for large electric machines. It uses a set of common pressure rails to provide the majority of power hydraulically and small electric motors to modulate that power for precise control. This paper presents the development of a Hardware-in-the-loop (HIL) test-bed for testing motion control strategies for the HHEA. Precise motion control is important for off-road vehicles whose utility requires the machine being dexterous and performing tasks exactly as commanded. Motion control for the HHEA is challenging due to its intrinsic use of discrete pressure rail switches to minimize system efficiency or to keep the system within the torque capabilities of the electric motor. The motion control strategy utilizes two different controllers: a nominal passivity based back-stepping controller used in between pressure rail switches and a transition controller used to handle the event of a pressure rail switch. In this paper, the performance of the nominal control under various nominal and rail switching scenarios is experimentally evaluated on the HIL testbed.

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