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Redundant Robot Kinematics Control with HCMAC Neural Network Manipulability Enhancement

V. Řikovský, Š. Kozák
2008 IFAC Proceedings Volumes  
This paper deals with new numerically efficient procedures and an application of HCMAC (Hierarchical Cerebellar Model Arithmetic Controller) neural network for manipulability gradient computation and consecutive  ...  Recently, neural networks have found wide application in robotics, because of their feature to learn any complicated system model.  ...  CMAC AND HCMAC NEURAL NETWORK To derive the HCMAC neural network, we first briefly introduce the CMAC neural network based on different basis functions.  ... 
doi:10.3182/20080706-5-kr-1001.00919 fatcat:e5og3lv7p5firpmmqittcak6aa

Dynamic control of a robot arm using CMAC neural networks

G. Cembrano, G. Wells, J. Sardá, A. Ruggeri
1997 Control Engineering Practice  
The solution of this dynamic control problem with CMAC is an encouraging demonstration of "experience-based', as opposed to model-based, control techniques ,and is a good example of the use of on-line  ...  Among the various neural-network p~,~ligms available, the CMAC model was chosen in this c~c because of its f~t convergence and on-line adaptation capability.  ...  ACKNOWLEDGEMENTS This rcscarch work was partially fundcd by the ESPRIT Ill program of thc EEC, undcr project No. 6715 "Robot Control bascd on Ncural Network Systems'.  ... 
doi:10.1016/s0967-0661(97)00028-2 fatcat:fxkby5xo4nh6zmqpdzibzsq3ce

A cooperative CMAC neural network for hydro-generating system with doubly fed induction generators

Li Hui, Han Li
2005 2005 International Conference on Electrical Machines and Systems  
This paper proposes an approach of cooperative cerebellar model articulation controller (CMAC) neural network that is based on the concept of combining CMAC and the adaptive linear neuron controller.  ...  In order to verify the control quality of the proposed cooperative CMAC neural network, the digital simulation of the steady state regulation characteristics for the multivariable and nonlinear control  ...  There are some typical control strategies for CMAC neural network in the control system fields, for instance, CMAC feed-forward control, CMAC feedback control, CMAC direct inverse motion control, etc.  ... 
doi:10.1109/icems.2005.202638 fatcat:lys6unuyvbhdnb4hghjfvd5pju

Improved CMAC neural network control scheme

C.C. Lin, F.C. Chen
1999 Electronics Letters  
The measured results with a ramp signal fvo = 500Hz at the input are shown in Fig. 4b (only the 4th bit is shown).  ...  Improved CMAC neural network control scheme C.C. Lin and F.C.  ...  Chen The cerebellar model articulation controller (CMAC) neural netwsrk control scheme is a powerful tool for practical real-time nonlinear control applications.  ... 
doi:10.1049/el:19990083 fatcat:n3ln7lx3vjexjniny7o4345izq

Neural Optimal Control of PEM Fuel Cells With Parametric CMAC Networks

P.E.M. Almeida, M.G. Simoes
2005 IEEE transactions on industry applications  
First, a new approach to design Neural Optimal Control (NOC) systems is proposed.  ...  This work demonstrates an application of the Parametric CMAC (P-CMAC) Network --a neural structure derived from Albus's CMAC algorithm and Takagi-Sugeno-Kang parametric fuzzy inference systems.  ...  Corrêa for his help in modeling a fuel cell system. The National Science Foundation with grant ECS-0134130, and the Brazilian agency CAPES have partially supported this work.  ... 
doi:10.1109/tia.2004.836135 fatcat:f2fejezuzra47evifi4kmls2se

Missile Control Using Fuzzy Cerebellar Model Arithmetic Computer Neural Networks

Z. Jason Geng, Claire L. McCullough
1997 Journal of Guidance Control and Dynamics  
Section V presents an inner-loop con- troller design using a linearized model and eigenstructure assign- ment. Section VI details the outer-loop controller design based on fuzzy CMAC neural networks.  ...  Fuzzy CMAC Neural Networks A.  ... 
doi:10.2514/2.4077 fatcat:hltjtnedyfbwnkzlxrhbpfgave

CMAC-based compound control of hydraulically driven 6-DOF parallel manipulator

Shou-Kun Wang, Jun-Zheng Wang, Da-Wei Shi
2011 Journal of Mechanical Science and Technology  
In order to improve the precision of both VCAC control and 6-DOF parallel manipulator movement, this paper presents a new, cerebellar model articulation control (CMAC)-based control method.  ...  The theoretical analysis and testing results, compared with those for the PID control, proved that the proposed CMAC-based control method can acquire high movement precision on the 6-DOF motion simulator  ...  Cerebellar model articulation control (CMAC) is a new type of neural network first advanced by Albus [18] .  ... 
doi:10.1007/s12206-011-0329-8 fatcat:jxau6fq6kbd43a55hyjt2nt4t4

A Novel Compound Control Method for Hydraulically Driven Shearer Drum Lifting

Lei Si, Zhongbin Wang, Xinhua Liu, Lin Zhang
2014 Journal of Control Science and Engineering  
In order to adjust shearer drum swiftly and precisely to adapt to the changes of coal seam, a compound control approach based on cerebellar model articulation control and fractional order PID controller  ...  Furthermore, RBF neural network was applied to obtaining reasonable tuning parameters and a control algorithm of proposed controller was designed.  ...  Cerebellar model articulation control (CMAC) is a new type of neural network first advanced by Almeida and Simões [9] .  ... 
doi:10.1155/2014/691787 fatcat:kk5vgggnnjgrnojy6fyeubt2ou


Dusko Katić, Miomir Vukobratović
2005 IFAC Proceedings Volumes  
This paper focusses on the application of intelligent control techniques (neural networks, fuzzy logic and genetic algorithms) and their hybrid forms (neuro-fuzzy networks, neuro-genetic and fuzzy-genetic  ...  Overall, this survey covers a broad selection of examples that will serve to demonstrate the advantages and disadvantages of the application of intelligent control techniques.  ...  Kitamura 1988 proposed a walking controller based on Hopfield neural network in combination with an inverted pendulum dynamic model.  ... 
doi:10.3182/20050703-6-cz-1902.01276 fatcat:wrzes2vitbf4rkkfn3c6evxuxe

Research on the Operation Control Strategy of a Low-Voltage Direct Current Microgrid Based on a Disturbance Observer and Neural Network Adaptive Control Algorithm

Liang Zhang, Kang Chen, Ling Lyu, Guowei Cai
2019 Energies  
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.  ...  pre-synchronization control algorithm based on a neural network adaptive control structure is proposed in this paper.  ... 
doi:10.3390/en12061162 fatcat:m57m2ugo35ha5ahycuy6djxz4a

A Fast Adaptive Artificial Neural Network Controller for Flexible Link Manipulators

Amin Riad, Hosna Meddahi
2016 International Journal of Advanced Computer Science and Applications  
To tackle these challenges, a novel control architecture scheme is presented. First, a neural network controller based on the robot's dynamic equation of motion is elaborated.  ...  Efficiency of the new controller obtained is tested on a two-link flexible manipulator.  ...  Therefore, the controller presented in this paper is based on Artificial Neural Networks (ANNs) that approximate the dynamic model of the robot.  ... 
doi:10.14569/ijacsa.2016.070141 fatcat:3us4k3imnbcpvfuuxcebypydri

Torque Ripple Suppression Method of Switched Reluctance Motor Based on an Improved Torque Distribution Function

Xiao Ling, Chenhao Zhou, Lianqiao Yang, Jianhua Zhang
2022 Electronics  
This paper proposes a new torque ripple suppression method of SRM based on the improved torque distribution function.  ...  Then, the improved torque distribution function is planned based on the torque model to give the reference torque of each phase, and the inverse torque model is used to realize the mapping of the reference  ...  Model Learning Based on CMAC The CMAC is a simple and fast neural network based on local approximation, which is established by the input and output data without depending on the mathematical model of  ... 
doi:10.3390/electronics11101552 fatcat:4jj3ay7afzgs5dqkoea3ly44ke

A Fast Lut+Cmac Data Predistorter

A. Artes-Rodriguez, A.R. Figueiras Vidal, F.J. Gonzalez-Serrano
1996 Zenodo  
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

Optimal design of CMAC neural-network controller for robot manipulators

Y.H. Kim, F.L. Lewis
2000 IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews)  
Index Terms-CMAC neural network, optimal control, robotic control. Frank L. Lewis (S'78-M'  ...  This paper is concerned with the application of quadratic optimization for motion control to feedback control of robotic systems using cerebellar model arithmetic computer (CMAC) neural networks.  ...  He is a member of Sigma Xi. Fig. 1 . 1 Architecture of a CMAC neural network. Fig. 2 . 2 CMAC neural controller based on the H-J-B optimization. "uniformly ultimately bounded."  ... 
doi:10.1109/5326.827451 fatcat:dos4qnrbpbgmrlfwnxwne3drci

A Historical Review of Forty Years of Research on CMAC [article]

Frank Z. Xing
2017 arXiv   pre-print
Two perspective, CMAC as a neural network and CMAC as a table look-up technique are presented. Three aspects of the model: the architecture, learning algorithms and applications are discussed.  ...  In the end, some potential future research directions on this model are suggested.  ...  Most of them can be categorized into two directions of improvement. The first relies on extra supervisory signals or value assignment mechanism based on statistics.  ... 
arXiv:1702.02277v1 fatcat:u6ii3pwkpzdhthb3ofpd4ulo7m
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