A New Approach to Manipulator Control: The Cerebellar Model Articulation Controller (CMAC)

Cited by (999)

Items 501–600 of 999

1. Intelligent Robust Control for Uncertain Nonlinear Multivariable Systems using Recurrent Cerebellar Model Neural Networks
   2015 · Acta Polytechnica Hungarica
2. Real-Time Image Recognition and Path Tracking of a Wheeled Mobile Robot for Taking an Elevator
   2013 · Acta Polytechnica Hungarica
3. Feature Extraction for Excavator Operation Skill Using CMAC
   Kazushige Koiwai, Yuntao Liao, Toru Yamamoto · 2016 · Journal of Robotics and Mechatronics
4. Steering motion control of a snake robot via a biomimetic approach
   Wenjuan Ouyang, Wenyu Liang, Chenzui Li · 2019 · Frontiers of Information Technology & Electronic Engineering
5. Real-Time Dynamic Visual Tracking Using PSD Sensors and Extended Trapezoidal Motion Planning
   Soo‐Hyuk Nam, Se‐Young Oh · 1999 · Applied Intelligence
6. MS_CMAC Neural Network Learning Model in Structural Engineering
   Shih‐Lin Hung, J. C. Jan · 1999 · Journal of Computing in Civil Engineering
7. Classification of autoregressive spectral estimated signal patterns using an adaptive resonance theory neural network
   Chang‐Ching Lin, Hsu‐Pin Wang · 1993 · Computers in Industry
8. A hybrid fuzzy cerebellar model articulation controller based autonomous controller
   Chen Guang Guo, Zhen Ye, Zengqi Sun · 2002 · Computers & Electrical Engineering
9. Best estimated inverse versus inverse of the best estimator
   Amir Karniel, Ron Meir, G.F. Inbar · 2001 · Neural Networks
10. Fuzzy-logic-based Reinforcement Learning of Admittance Control for Automated Robotic Manufacturing
    Sameer M. Prabhu, Devendra P. Garg · 1998 · Engineering Applications of Artificial Intelligence
11. Deconvolution of overlapping chromatographic peaks using a cerebellar model arithmetic computer neural network
    Stuart R. Gallant, Steven P. Fraleigh, Steven M. Cramer · 1993 · Chemometrics and Intelligent Laboratory Systems
12. A fuzzy CMAC structure and learning method for function approximation
    Hung-Ren Lai, Ching‐Chang Wong · 2002 · Proceedings of ... IEEE International Conference on Fuzzy Systems
13. A neuro-adaptive variable structure control for partially unknown nonlinear dynamic systems and its application
    Chih‐Lyang Hwang, Cheng-Ye Hsieh · 2002 · IEEE Transactions on Control Systems Technology
14. On The Revised Theory Of Intelligent Machines
    G.N. Saridis · 2005
15. A sensor-based telerobotic system for the space robot experiment ROTEX
    G. Hirzinger, Gerhard Grunwald, B. Brunner · 2006 · Springer eBooks
16. Rapid learning using CMAC neural networks: real time control of an unstable system
    W.T. Miller, Christiaan Aldrich · 2002 · IEEE International Symposium on Intelligent Control
17. From animals to animats: Proceedings of the First International Conference on Simulation of Adaptive Behavior
    Matthew Brand, Peter N. Prokopowicz, Clark Elliott · 1995 · Artificial Intelligence
18. Robot Systems Completely Based on Sensory Feedback
    G. Hirzinger · 1986 · IEEE Transactions on Industrial Electronics
19. Pattern separability in a random neural net with inhibitory connections
    Toyoshi Torioka · 1979 · Biological Cybernetics
20. Sensorimotor coordination and sensor fusion by neural networks
    Guo-Qing Wei, G. Hirzinger, B. Brunner · 2002 · IEEE International Conference on Neural Networks/IEEE ... International Conference on Neural Networks
21. Perception–Intention–Action Cycle in Human–Robot Collaborative Tasks: The Collaborative Lightweight Object Transportation Use-Case
    J. E. Domínguez-Vidal, Nicolás Rodríguez, Alberto Sanfeliu · 2024 · International Journal of Social Robotics
22. Robust parametric CMAC with self-generating design for uncertain nonlinear systems
    Hung‐Ching Lu, Chih-Ying Chuang · 2010 · Neurocomputing
23. Intelligent total sliding‐mode control with dead‐zone parameter modification for a DC motor driver
    Chun‐Fei Hsu · 2014 · IET Control Theory and Applications
24. CMAC neural network as an SVM with B-spline kernel functions
    Gábor Horváth · 2004
25. The development of neural networks applications from perceptron to deep learning
    Ahmad Jobran Al-Mahasneh, Sreenatha Gopalarao Anavatti, Matthew Garratt · 2017 · International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation (ICAMIMIA)
26. A novel hybrid learning algorithm for parametric fuzzy CMAC networks and its classification applications
    Cheng‐Jian Lin, Jia‐Hong Lee, Chi-Yung Lee · 2007 · Expert Systems with Applications
27. Classification of Liver Diseases from CT Images Using BP-CMAC Neural Network
    Chien-Cheng Lee, Pau‐Choo Chung, Y.M. Chen · 2005 · International Workshop on Cellular Neural Networks and Their Applications
28. Fuzzy CMAC With Incremental Bayesian Ying–Yang Learning and Dynamic Rule Construction
    Daming Shi, Minh Nhut Nguyen, Suiping Zhou · 2009 · IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)
29. Using RBFs in a CMAC to prevent parameter drift in adaptive control
    Chris J. B. Macnab · 2016 · Neurocomputing
30. The Marr and Albus theories of the cerebellum-two early models of associative memory
    James Sacra Albus · 2003 · IEEE Computer Society International Conference (COMPCON Spring)
31. Real-time control of an inverted pendulum system using complementary neural network and optimal techniques
    J. Nelson, L.G. Kraft · 2005 · Proceedings of the ... American Control Conference/Proceedings of the American Control Conference
32. A simple and converged structure of addressing technique for CMAC_GBF
    Ching‐Tsan Chiang, Tung‐Sheng Chiang, Chien-Koo Li · 2005 · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics
33. Implementation of a Variable D-H Parameter Model for Robot Calibration Using an FCMAC Learning Algorithm
    Kuu‐Young Young, Jin-Jou Chen · 1999 · Journal of Intelligent & Robotic Systems
34. One-to-one mapping and its application to neural networks based control systems design
    Hong Wang, Anzhe Wang, Martin Brown · 1996 · International Journal of Systems Science
35. A neuro-fuzzy control model for fine-positioning of manipulators
    Jianwei Zhang, Alois Knoll, Ralf Schmidt · 2000 · Robotics and Autonomous Systems
36. On a primitive skill-based supervisory robot control architecture
    Giulio Milighetti, H.-B. Kuntze, Christian Walter Frey · 2005 · International Conference on Advanced Robotics (ICAR)
37. CMAC-based fault diagnosis of power transformers
    Wei‐Song Lin, Chin-Pao Hung, Mang-Hui Wang · 2003
38. Multiple Neuro-Adaptive Control of Robot Manipulators Using Visual Cues
    Chen‐Yi Lee, Jaewook Lee · 2005 · IEEE Transactions on Industrial Electronics
39. Efficient Memory-Based Dynamic Programming
    Jing Peng · 1995 · Elsevier eBooks
40. Integrating knowledge-based system and neural network techniques for robotic skill acquisition
    David A. Handelman, Stephen H. Lane, Jack J. Gelfand · 1989 · International Joint Conference on Artificial Intelligence
41. Toward an Understanding of the Cerebral Cortex and Reaching Movements: A Review of Recent Approaches
    P. Johnson · 1992 · Springer eBooks
42. Online Speed Controller Scheme Using Adaptive Supervisory TSK ‐fuzzy CMAC for Vector Controlled Induction Motor Drive
    S. Y. Wang, C. L. Tseng, C. J. Chiu · 2013 · Asian Journal of Control
43. Parameter Identification of a Robot Arm Manipulator Based on a Convolutional Neural Network
    Carlos Leopoldo Carreón Díaz de León, Sergio Vergara Limon, María Aurora Diozcora Vargas-Treviño · 2022 · IEEE Access
44. ARTIFICIAL NEURAL NETWORKS OF THE PERCEPTRON, MADALINE, AND BACKPROPAGATION FAMILY
    Bernard Carlos Widrow, Michael A. Lehr · 1993 · Elsevier eBooks
45. Wall-following and Navigation Control of Mobile Robot Using Reinforcement Learning Based on Dynamic Group Artificial Bee Colony
    Tzu-Chao Lin, Chao‐Chun Chen, Cheng‐Jian Lin · 2017 · Journal of Intelligent & Robotic Systems
46. A working memory model improves cognitive control in agents and robots
    Michele Persiani, Alessio Mauro Franchi, Giuseppina Gini · 2018 · Cognitive Systems Research
47. A modified function-link fuzzy cerebellar model articulation controller using a PI-type learning algorithm for nonlinear system synchronization and control
    Tuân-Tú Huỳnh, Chih‐Min Lin, Thanh-Thao T. Pham · 2018 · Chaos Solitons & Fractals
48. New Intelligent Control Strategy Hybrid Grey–RCMAC Algorithm for Ocean Wave Power Generation Systems
    Kai-Hung Lu, Chih-Ming Hong, Zhigang Han · 2020 · Energies
49. Near-optimal neural-network robot control with adaptive gravity compensation
    M. Razmi, Chris J. B. Macnab · 2020 · Neurocomputing
50. Chaotic Synchronization Using a Self-Evolving Recurrent Interval Type-2 Petri Cerebellar Model Articulation Controller
    Tien-Loc Le, Tuân-Tú Huỳnh, Nguyen Vu Quynh, Chih‐Min Lin, Sung-Kyung Hong · 2020 · Mathematics
51. Adaptive robust controller using intelligent uncertainty observer for mechanical systems under non-holonomic reference trajectories
    Xiaolong Chen, Wenyu Liang, Han Zhao · 2021 · ISA Transactions
52. Analytic formulation of intelligent machines as neural nets
    G.N. Saridis, Michael C. Moed · 2003 · The proceedings of the IEEE Conference on Control Applications/The proceedings of the ... IEEE Conference on Control Applications
53. Fault diagnosis of steam turbine-generator using CMAC neural network approach
    Chin-Pao Hung, Mang-Hui Wang, Chin‐Hsing Cheng · 2004
54. A Neural Tactile Architecture Applied to Real-time Stiffness Estimation for a Large Scale of Robotic Grasping Systems
    Juan Luis Pedreño-Molina, Antonio Guerrero González, J. Calabozo-Morán · 2007 · Journal of Intelligent & Robotic Systems
55. Multi-level cognitive machine-learning based concept for human-like “artificial” walking: Application to autonomous stroll of humanoid robots
    Kurosh Madani, Christophe Sabourin · 2010 · Neurocomputing
56. A Bayesian Perspective on Stochastic Neurocontrol
    Randa Herzallah, David G. Lowe · 2008 · IEEE Transactions on Neural Networks
57. Parallel Online Temporal Difference Learning for Motor Control
    Wouter Caarls, Erik Schuitema · 2015 · IEEE Transactions on Neural Networks and Learning Systems
58. Fuzzy neuronal model of motor control inspired by cerebellar pathways to online and gradually learn inverse biomechanical functions in the presence of delay
    Armin Salimi-Badr, Mohammad Mehdi Ebadzadeh, C. Darlot · 2017 · Biological Cybernetics
59. A rotor position estimator for switched reluctance motors using CMAC
    Erkan Meşe · 2002 · Energy Conversion and Management
60. Robotic System Sensitivity to Neural Network Learning Rate: Theory, Simulation, and Experiments
    Christopher Clark, James K. Mills · 2000 · The International Journal of Robotics Research
61. Real time implementation of CTRNN and BPTT algorithm to learn on-line biped robot balance: Experiments on the standing posture
    Patrick Hénaff, Vincent Scesa, F.B. Ouezdou · 2010 · Control Engineering Practice
62. Situated neuro-fuzzy control for vision-based robot localisation
    Jianwei Zhang, Alois Knoll, V. Schwert · 1999 · Robotics and Autonomous Systems
63. Logic-based neural networks
    Kaoru Hirota, Witold Pedrycz · 1993 · Information Sciences
64. A Comparison of CMAC Neural Network and Traditional Adaptive Control Systems
    L.G. Kraft, David P. Campagna · 1989 · Proceedings of the ... American Control Conference/Proceedings of the American Control Conference
65. Multiagent fuzzy-neural control of a 3-link uniped
    Wujian Zhang, K. Kalyana-Kumar, Aofan Li · 2002 · Proceedings of ... IEEE International Conference on Fuzzy Systems
66. Robust CMAC control schemes for dynamic trajectory following
    Ted Tao, Hung‐Ching Lu, Shun‐Feng Su · 2002 · Journal of the Chinese Institute of Engineers
67. Fourier analysis of the generalized CMAC neural network
    F.J. González-Serrano, Aníbal Ramón Figueiras-Vidal, Antonio Artés-Rodrı́guez · 1998 · Neural Networks
68. A self-organizing recurrent fuzzy CMAC model for dynamic system identification
    Cheng‐Jian Lin, Huei-Jen-Chen, Chi-Yung Lee · 2005 · Proceedings of ... IEEE International Conference on Fuzzy Systems
69. Real time experiments in neural network based learning control during high speed nonrepetitive robotic operations
    W.T. Miller, R.P. Hewes · 2003 · IEEE International Symposium on Intelligent Control
70. Improving the generalization capability of the binary CMAC
    T. Szabo, Gábor Horváth · 2000
71. Applications of Neural Networks to Robotics
    Sukhan Lee, George A. Bekey · 1991 · Control and dynamic systems
72. Fuzzy hypercubes: linguistic learning/reasoning systems for intelligent control and identification
    Hoon Kang, George Vachtsevanos · 2002 · Proceedings of the IEEE Conference on Decision & Control, including the Symposium on Adaptive Processes
73. Learning and approximation in database for feedforward control of flexible manipulator
    Dimitry M. Gorinevsky · 1991
74. Crossmodal Learning and Prediction of Autobiographical Episodic Experiences using a Sparse Distributed Memory
    Sascha Jockel · 2010
75. CMAC-based supervisory control for nonlinear chaotic systems
    Chih‐Min Lin, Chiu-Hsiung Chen · 2006 · Chaos Solitons & Fractals
76. Self-Organizing Gaussian Fuzzy CMAC with Truth Value Restriction
    Minh Nhut Nguyen, Daming Shi, Chai Hiok Quek · 2005
77. Hybrid recurrent cerebellar model articulation controller-based supervisory H ∞ motion control system for permanent-magnet synchronous motor servo drive
    Fayez F. M. El-Sousy · 2011 · IET Electric Power Applications
78. Robust task-space tracking for free-floating space manipulators by cerebellar model articulation controller
    Li Liang, Ziyu Chen, Yaobing Wang · 2019 · Assembly Automation
79. A Motor Fault Diagnosis System Based on Cerebellar Model Articulation Controller
    Pi-Yun Chen, Kuei‐Hsiang Chao, Yu-Cheng Tseng · 2019 · IEEE Access
80. Self-Organizing Adaptive Fuzzy Brain Emotional Learning Control for Nonlinear Systems
    Chih‐Min Lin, Ravitej Ramarao, Srinivas Hangaralli Gopalai · 2019 · International Journal of Fuzzy Systems
81. A survey of efficient computational methods for manipulator inverse dynamics
    C. A. Balafoutis · 1994 · Journal of Intelligent & Robotic Systems
82. A Learning Algorithm of CMAC Based on RLS
    Ting Gao Qin, Zonghai Chen, Hai‐Tao Zhang · 2004 · Neural Processing Letters
83. Modeling gait transitions of quadrupeds and their generalization with CMAC neural networks
    Jian-Nan Lin, Shin‐Min Song · 2002 · IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews)
84. Detection of Drinking Water Quality Using CMAC Based Artificial Neural Networks
    İhsan Ömür Bucak, Bekir Karlık · 2011 · Ekoloji
85. A Scalable Model of Cerebellar Adaptive Timing and Sequencing: The Recurrent Slide and Latch (RSL) Model
    Bradley J. Rhodes, Daniel Bullock · 2002 · Applied Intelligence
86. A modular approach to intelligent control of a simulated jointed leg
    Peggy Israel Doerschuk, William E. Simon, Vinh Nguyen · 1998 · IEEE Robotics & Automation Magazine
87. Integration of CMAC and radial basis function techniques
    Ching‐Tsan Chiang, Chun-Shin Lin · 2002 · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics
88. RCS: a reference model architecture for intelligent control
    James Sacra Albus, William G. Rippey · 2005
89. Performance analysis of rotating machinery using enhanced cerebellar model articulation controller (E-CMAC) neural networks
    Chang‐Ching Lin, Hsu‐Pin Wang · 1996 · Computers & Industrial Engineering
90. Multiplication-free radial basis function network
    M. Heiss, S. Kampl · 1996 · IEEE Transactions on Neural Networks
91. Learning to Control Forest Fires
    Marco Wiering, Marco Dorigo · 1998
92. Machine-Intelligent Robots: A Hierarchical Control Approach
    G.N. Saridis · 1987 · Springer eBooks
93. Stable Sampled-data Adaptive Control of Robot Arms Using Neural Networks
    Fuchun Sun, Zengqi Sun · 1997 · Journal of Intelligent & Robotic Systems
94. On the training of a multi-resolution CMAC neural network
    Alberico Menozzi, Mo–Yuen Chow · 2002 · IEEE International Symposium on Industrial Electronics (ISIE)
95. Neural network-based control for the fiber placement composite manufacturing process
    Peter F. Lichtenwalner · 1993 · Journal of Materials Engineering and Performance
96. Learning Virtual Equilibrium Trajectories for Control of a Robot Arm
    Reza Shadmehr · 1990 · Neural Computation
97. Navigating through Temporal Difference
    Peter Dayan · 1990 · UCL Discovery (University College London)
98. A Computationally Efficient Algorithm for Training Recurrent Connectionist Networks
    Mitchell M. Livstone, Jay A. Farrell, Walter L. Baker · 1992 · Proceedings of the ... American Control Conference/Proceedings of the American Control Conference
99. Real-time adaptive on-line traffic incident detection
    H. Xu, Chiman Kwan, L. Haynes · 2002 · IEEE International Symposium on Intelligent Control
100. Dynamic Systems in Neural Networks
     Kevin Warwick, C. Kambhampati, P.C. Parks · 1995 · Advances in industrial control