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Design of a CMAC-based smooth adaptive neural controller with a saturation compensator
2011
Neural computing & applications (Print)
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In the conventional CMAC-based adaptive ...
This paper proposes a CMAC-based smooth adaptive neural control (CSANC) system that is composed of a neural controller and a saturation compensator. ...
The neural controller uses a CMAC neural network to online mimic an ideal controller and the saturation compensator is designed to dispel the approximation error between the ideal controller and neural ...
doi:10.1007/s00521-011-0615-5
fatcat:bbirsfvetzhb5n2kv75gnwm7wu
Research on the Operation Control Strategy of a Low-Voltage Direct Current Microgrid Based on a Disturbance Observer and Neural Network Adaptive Control Algorithm
2019
Energies
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Then, in a grid-connected mode, a pre-synchronization control algorithm based on a neural network adaptive control was proposed, and the droop controller was improved to ensure better control accuracy. ...
Firstly, a DC bus control algorithm based on disturbance observer (DOB) was proposed to suppress the impact of system load mutation on DC bus in island mode. ...
[18] , a pre-synchronization control algorithm based on a neural network adaptive control structure is proposed in this paper. ...
doi:10.3390/en12061162
fatcat:m57m2ugo35ha5ahycuy6djxz4a
A Robust Adaptive CMAC Neural Network-Based Multisliding Mode Control Method for Unmatched Uncertain Nonlinear Systems
2020
Mathematical Problems in Engineering
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This paper proposes a new robust adaptive cerebellar model articulation controller (CMAC) neural network-based multisliding mode control strategy for a class of unmatched uncertain nonlinear systems. ...
it reduces the conservativeness for controller parameter design by adopting the CMAC neural network to learn both system uncertainties and virtual control variable derivatives of each order online. ...
] [19] [20] . e main idea of such a scheme is to design adaptive controllers with embedded mechanisms, such that some of the parameters could be adjusted adaptively with all the signals in the adaptive ...
doi:10.1155/2020/1615345
fatcat:6nex35nb4vgpbh2e57rrxjr6ee
A Fast Lut+Cmac Data Predistorter
1996
Zenodo
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Publication in the conference proceedings of EUSIPCO, Trieste, Italy, 1996 ...
Table , , LUT) in parallel with a neural network called CMAC (Cerebellar Model Articulation Controller) 3]. ...
Articulation Controller (CMAC) 3, 5 ] w as proposed as a control method based on the principles of the cerebellum's motor behavior. ...
doi:10.5281/zenodo.35968
fatcat:kogrrv45kvfnxpsvwzisertjjm
Discrete-time CMAC NN control of feedback linearizable nonlinear systems under a persistence of excitation
1999
IEEE Transactions on Neural Networks
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A CMAC neural network-based discrete-time controller which linearizes the unknown multiinput and multioutput (MIMO) nonlinear system through feedback is presented. ...
The local structure of CMAC neural networks (NN) result in better and faster controllers for nonlinear dynamical systems. ...
I N recent years, learning-based neural-network controllers have emerged as an alternative to adaptive control. ...
doi:10.1109/72.737499
pmid:18252509
fatcat:aqe4yoivtjeefc252wgtuqcnji
Adaptive fuzzy CMAC control for a class of nonlinear systems with smooth compensation
2006
IEE Proceedings - Control Theory and Applications
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Adaptive fuzzy cerebellar model articulation controller (CMAC) schemes are proposed to solve the tracking problem for a class of nonlinear systems. ...
In particular, smooth compensation is adopted to overcome the chattering problem associated with conventional switching compensation. ...
Moreover, to suppress the approximated error of the FCMAC, a switching compensation is imposed, and a smooth compensation is developed to resolve the arising chattering problem.
3 Adaptive FCMAC controller ...
doi:10.1049/ip-cta:20050362
fatcat:gp7h7vtq2vezdkcgtuargpcwei
A Brief Review of Neural Networks Based Learning and Control and Their Applications for Robots
2017
Complexity
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Specifically, this survey also reviews a number of NN based robot control algorithms, including NN based manipulator control, NN based human-robot interaction, and NN based cognitive control. ...
As an imitation of the biological nervous systems, neural networks (NNs), which have been characterized as powerful learning tools, are employed in a wide range of applications, such as control of complex ...
A neural adaptive controller was ˆ ˆ ˆ ˆ ˆ ˆ designed to deal with the effect of input saturation of the robot manipulator in [93] as below. z 1 Ŵ D S D (Z D ) 1 Ŵ C S C (Z C ) 1 Ŵ G ...
doi:10.1155/2017/1895897
fatcat:t4rq6ux7brhnjicextnyh5o6dq
Smooth trajectory tracking of three-link robot: a self-organizing CMAC approach
1998
IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)
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The second one is developed based on the concept of the self-organizing fuzzy cerebellar model articulation controller (FCMAC) and adaptive heuristic critic (AHC). ...
Both compose a forward compensator to reduce the chattering effect or cancel the influence of system uncertainties. ...
Sheng, Yuan-Ze Institute of Technology, Taoyuan, Taiwan, R.O.C., for their helpful extensive comments, which have significantly improved the presentation of this research. ...
doi:10.1109/3477.718518
pmid:18255987
fatcat:sbkxjsg7xbaslorjbq5ljtwzte
Positioning Error Analysis and Control of a Piezo-Driven 6-DOF Micro-Positioner
2019
Micromachines
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Afterwards, an inverse Presiach model-based feedforward compensation of the hysteresis nonlinearity is employed by the control scheme, combined with a proportional-integral-derivative (PID) feedback controller ...
Moreover, a back propagation neural network PID (BP-PID) controller and a cerebellar model articulation controller neural network PID (CMAC-PID) controller are also adopted and compared to obtain optimal ...
Meanwhile, the back propagation neural network PID (BP-PID) control and cerebellar model articulation control neural network PID (CMAC-PID) control are also introduced and compared for feedback control ...
doi:10.3390/mi10080542
pmid:31426503
pmcid:PMC6722792
fatcat:jmzyeby7lvbb3mk4guu34jjdiu
Direct Fuzzy CMAC Sliding Mode Trajectory Tracking for Biaxial Position System
2021
Energies
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This research presents an adaptive direct fuzzy cerebellar model articulation controller (CMAC) sliding mode control (DFCMACSMC) for the precise control of the industrial XY-axis motion system. ...
The FCMAC was utilized to approximate an ideal controller, and the weights of FCMAC were on-line tuned by the derived adaptive law based on the Lyapunov criterion. ...
This research [18] proposes a control system consisting of a novel type of fuzzy neural network and a robust compensator controller for robot systems. ...
doi:10.3390/en14227802
fatcat:hlwifobny5f7vjxbzttpyc6lva
Control of a Rehabilitation Robotic Device Driven by Antagonistic Soft Actuators
2021
Actuators
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To fulfill the need for control of the proposed device, a knowledge-guided data-driven modeling approach is used and an adaptive feedforward–feedback control approach is presented to ensure the motion ...
Finally, several simulations and experiments are carried out to evaluate the performance of the developed system, and the results show that the developed system with the proposed controller can achieve ...
In the spirit of this bio-inspired actuator, an artificial neural network controller based on the model of the mammalian cerebellum, namely, CMAC can be a good candidate [38] . ...
doi:10.3390/act10060123
fatcat:banxzbypgjdkjkhj5y3nz7ozta
Neural integrated control for a free-floating space robot with suddenly changing parameters
2011
Science China Information Sciences
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Neural integrated control for a free-floating space robot with suddenly changing parameters. ...
Because the state of a free-floating space robot model is uncertain and sudden changes in the model parameters might undermine the stability of the system, this paper proposes a control strategy based ...
Their common control field uses saturation functions to achieve common control and smooth switching. ...
doi:10.1007/s11432-011-4420-7
fatcat:tfcc3m26jfgk3f4s56yizs7efq
Output feedback control of nonlinear systems using RBF neural networks
2000
IEEE Transactions on Neural Networks
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An RBF neural network is used to adaptively compensate for the plant nonlinearities. The network weights are adapted using a Lyapunov-based design. ...
An adaptive output feedback control scheme for the output tracking of a class of continuous-time nonlinear plants is presented. ...
the order Adaptive output feedback control that uses parameter projection, high adaptation gain, and control saturation has also been considered in a similar setting by [11] . ...
doi:10.1109/72.822511
pmid:18249740
fatcat:j6qadwsaszaipazmutvw76tkci
Optimized state feedback regulation of 3DOF helicopter system via extremum seeking
2013
2013 9th Asian Control Conference (ASCC)
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zhao*; Jun-Min Wang 355 A Hybrid PID and Direct Adaptive Neural Controller for Active Control of Non-Linear Hysteretic Base-Isolation building State Estimation in Discrete-Time Nonlinear Stochastic Systems ...
Controllers
with Two-Stage Compensator Designs
Kazuyoshi MORI*
506
Connectivity Control on Lie Groups
Aykut Satici*; Mark Spong
507
Performance Analysis of MPC Based on Structures
Subject ...
doi:10.1109/ascc.2013.6606363
dblp:conf/ascc/AkmeliawatiR13
fatcat:l7enyvdgurhpdl6yetwsst3u7y
Adaptive nonlinear compensation for CDMA communication systems
2001
IEEE Transactions on Vehicular Technology
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We analyze the performance of the generalized cerebellar model articulation controller neural network in two problems: predistortion in nonlinear transmitters and adaptive interference cancellation in ...
This paper deals with nonlinear compensation in code-division multiple-access communications systems. ...
ACKNOWLEDGMENT The authors would like to acknowledge the suggestions of the anonymous reviewers. ...
doi:10.1109/25.917867
fatcat:tfqdhexkorgmjez52t5c2z64jq
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