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Adaptive Fuzzy Sliding Mode Control Based on a DEAP Flexible Actuator

2016 Revista Técnica de la Facultad de Ingeniería Universidad del Zulia  
Then, a robust adaptive fuzzy sliding mode controller is designed by a combination of sliding mode control and a fuzzy logic system.  ...  In view of this limitation, an adaptive fuzzy sliding mode control algorithm based on a DEAP flexible actuator is proposed.  ...  Finally a direct adaptive fuzzy sliding mode controller is designed.  ... 
doi:10.21311/001.39.3.33 fatcat:goavgqmcyjf75jassxwr3tgvvm

Adaptive Fuzzy-Lyapunov Controller Using Biologically Inspired Swarm Intelligence

Alejandro Carrasco Elizalde, Peter Goldsmith
2008 Applied Bionics and Biomechanics  
The rules of the controller are designed using a computing-with-words approach called Fuzzy-Lyapunov synthesis to improve the stability and robustness of an adaptive fuzzy controller.  ...  This cooperative biological intelligence is the inspiration for an adaptive fuzzy controller developed in this paper.  ...  Our proposed controller is of the third type, which means the controller adapts its own parameters to maintain stability and good performance.  ... 
doi:10.1155/2008/767680 fatcat:cncn3zausvcwpna2y52f64avyy

Adaptive Fuzzy Robust Control of a Bionic Mechanical Leg with a High Gain Observer

Lihui Liao, Baoren Li, Yuanyuan Wang, Yi Xi, Dijia Zhang, Longlong Gao
2021 IEEE Access  
Section IV presents the adaptive fuzzy robust controller design procedure and its theoretical results.  ...  CONTROLLER DESIGN To improve the tracking performance of the BML system, an adaptive fuzzy robust control controller is described in this section.  ... 
doi:10.1109/access.2021.3091132 fatcat:fqa34q74drcm3eljhpst6dfwl4

INTELLIGENT NEURAL NETWORK CONTROL STRATEGY OF HYDRAULIC SYSTEM DRIVEN BY SERVO MOTOR

Ma Yu
2015 International Journal on Smart Sensing and Intelligent Systems  
A novel intelligent neural network control scheme which integrates the merits of fuzzy inference, neural network adaptivity and simple PID method is presented in this paper.  ...  algorithm can effectively improve the system performance, and the system has no steady-state error, good dynamic performance and good robustness, superior to conventional fuzzy controller and PID controller  ...  which integrating the advantages of fuzzy reasoning, adaptive neural network and simple PID control.  ... 
doi:10.21307/ijssis-2017-812 fatcat:ezln2nqclvcizentux5rn4hbzq

生态位贴近度的Type-2直接T-S模糊控制

郝云力,程向阳,王茂华, HAO Yunli, CHENG Xiangyang, WANG Maohua
2020 应用数学和力学  
Direct adaptive type fuzzy control[J]. Applied Intelligence, 2018, 48(3): 541•554. [14] ZHANG F X, LI Y M.  ...  Indirect adaptive fuzzy control of SISO nonlinear systems with input•outputnonlinear relationship[J]. IEEE Transactions on Fuzzy Systems, 2018, 26(5): 2699•2708. [13] ZHANG F X, LI Y M.  ... 
doi:10.21656/1000-0887.400376 fatcat:ttkcmycldbelflat6en2z6qgsa

Table of Contents

2021 2021 IEEE International Conference on Mechatronics and Automation (ICMA)  
Based on Adaptive Mutation Particle Swarm Ji Li, Wenlong Nie, Xiaoning Xu, Lei Shao, Wentao Sun Design of Remote Control Inverter Based on MQTT Communication Protocol 1374 Kunpeng Yang, Baofeng Zhang,  ...  , Xinyun Zhang The Vector Control Scheme for Amphibious Spherical Robots Based on He Yin, Shuxiang Guo, Liwei Shi, Mugen Zhou, Xihuan Hou, Zan Li, Debin Xia Fuzzy-Improved Linear Active Disturbance Rejection  ... 
doi:10.1109/icma52036.2021.9512723 fatcat:ntfz6r2lkrg6vlyrnlzneg7xby

Hybrid control combined with a voluntary biosignal to control a prosthetic hand

Saeed Bahrami Moqadam, Seyed Mohammad Elahi, An Mo, WenZeng Zhang
2018 Robotics and Biomimetics  
In this research, the combination of fuzzy/PD and EMG signals, as direct command control, is proposed.  ...  Although fuzzy/PD strategy was used to control force position of the artificial hand, the combination of that with EMG signaling to voluntary direct command control is a novel method.  ...  The internal control loop, fuzzy logic controller (FLC), is applied to improve anti-interference performance and adaptation of system parameters applied by the fuzzy controller inputs in the position error  ... 
doi:10.1186/s40638-018-0087-5 pmid:30294521 pmcid:PMC6153733 fatcat:lvpozply5vfrnjtrxupavyhbzi

Adaptive PD Control Based on RBF Neural Network for a Wire-Driven Parallel Robot and Prototype Experiments

Yuqi Wang, Qi Lin, Xiaoguang Wang, Fangui Zhou
2019 Mathematical Problems in Engineering  
An adaptive control algorithm is developed to reduce the approximation error and improve the robustness and control precision of the WDPR.  ...  The control scheme combines a PD control and an adaptive control based on a radial basis function (RBF) neural network. The PD control is used to track the trajectory of the end effector of the WDPR.  ...  [7] proposed a new indirect type-2 fuzzy neural network predictive (T2FNNP) controller for a class of nonlinear inputdelay systems in the presence of unknown disturbances and uncertainties.  ... 
doi:10.1155/2019/6478506 fatcat:23qpo452izdzzfeszzogxrt2gu

A Review of End-Effector Research Based on Compliance Control

Ye Dai, Chaofang Xiang, Wenyin Qu, Qihao Zhang
2022 Machines  
This paper describes the design and research results of different end-effectors under impedance-based control, hybrid force/position control, and intelligent flexible control methods, respectively.  ...  Under each control method, the structural characteristics and the optimized control scheme under different drives are introduced.  ...  [106] investigated the behavior of an indirect adaptive fuzzy controller acting as a force controller in a hybrid force/motion solution.  ... 
doi:10.3390/machines10020100 fatcat:d4rle63enfehfisxglyjly46eq

Application of Artificial Intelligence (AI) in Prosthetic and Orthotic Rehabilitation [chapter]

Smita Nayak, Rajesh Kumar Das
2020 Service Robotics [Working Title]  
leg, mind or thought control prosthesis and exoskeletons.  ...  The involvement of human interaction with various agents' i.e. electronic circuitry, software, robotics, etc. has made a revolutionary impact in the rehabilitation field to develop devices like Bionic  ...  Service Robotics 4 Figure 2 . 2 Figure 2. Schematic diagram of flow of information with bento arm [22].  ... 
doi:10.5772/intechopen.93903 fatcat:jp2h7xcms5h3tjx7ichkckplty

Neuromorphic Event-Based Slip Detection and Suppression in Robotic Grasping and Manipulation

Rajkumar Muthusamy, Xiaoqian Huang, Yahya Zweiri, Lakmal Seneviratne, Dongming Gan
2020 IEEE Access  
We use mamdani type fuzzy controller to adjust the grip force using incipient slip feedback. The fuzzy based slip suppression method is summarized in Algorithm 3.  ...  The online method enables the slip detector and fuzzy controller to adapt and handle objects of different shape and size.  ...  and Biomimetics in Frontiers Journal, and a Guest Editor in Applied Bionics and Biomechanics.  ... 
doi:10.1109/access.2020.3017738 fatcat:7hnoloelindltbcswgq64saifi

Learning-Based Neural Adaptive Anti-Coupling Control for a Class of Robots under Input and Structural Coupled Uncertainties

Junlong Niu, Xiansheng Qin, Zheng Wang
2021 IEEE Access  
Moreover, to overcome the system input related uncertainties, an indirect control law and the adaptive boundary estimation law have been designed.  ...  INDEX TERMS Adaptive control, adaptive algorithm, uncertain systems, nonlinear dynamical systems, robot control.  ...  By introducing fuzzy adaptive update law in the DOBC framework, literature [67] proposed an intelligent anti-disturbance control scheme.  ... 
doi:10.1109/access.2021.3060739 fatcat:odztklzu7za4lcwfda3pduccxm

Intelligent sowing depth regulation system based on Flex sensor and Mamdani fuzzy model for a no-till planter

Mingwei Li, 1. School of Biological and Agricultural Engineering, Jilin University, Changchun 130022, China, Xiaomeng Xia, Longtu Zhu, Renyi Zhou, Dongyan Huang, 2. Key Laboratory of Bionic Engineering, Ministry of Education, Jilin University, Changchun 130022, China
2021 International Journal of Agricultural and Biological Engineering  
In addition, the pneumatic spring was used as a downforce generator, and its intelligent regulation model was established by the Mamdani fuzzy algorithm, which can realize the control of the downward force  ...  The working process was simulated based on MATLAB-Simulink, and the results showed that the Mamdani fuzzy model performed well in changing the pressure against ground.  ...  Therefore, a Mamdani type double-input-single output fuzzy controller was designed with the deviation ΔP between the target pressure and the real-time pressure against the ground as well as the change  ... 
doi:10.25165/j.ijabe.20211406.5939 fatcat:a76oxw5id5cplhxndnb23h7viy

Evaluation of Arm Processor-based Bionic Intelligent Controller for a Buck-boost Converter

M.V. Mini, L. Padma Suresh
2015 Research Journal of Applied Sciences Engineering and Technology  
Design of PI controller is based on frequency response of the converter. The optimization of PI controller is based on ant colony algorithm.  ...  This study focuses on performance-comparison of different tuning methods for a PI controller applied to a buck-boost converter.  ...  Proportional-Integral-Derivative (PID) controllers are frequently used in the control process to regulate the time domain behavior of different types of dynamic plants.  ... 
doi:10.19026/rjaset.10.2427 fatcat:jw7f6ubufzb6bcwfyysalbpc6q

Biofeedback game design

Lennart Erik Nacke, Michael Kalyn, Calvin Lough, Regan Lee Mandryk
2011 Proceedings of the 2011 annual conference on Human factors in computing systems - CHI '11  
This has two major design implications for physiologically controlled games: (1) Direct physiological sensors should be mapped intuitively to reflect an action in the virtual world; (2) Indirect physiological  ...  In this paper, we propose a classification of direct and indirect physiological sensor input to augment traditional game control.  ...  We made our fallback weapon more interesting by placing the flame length under variable control (see Figure 2 ). Figure 2.  ... 
doi:10.1145/1978942.1978958 dblp:conf/chi/NackeKLM11 fatcat:ootfky6nhngvjbe5ahtkmtn5hi
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