文摘
英文文摘
声明
Chapter 1: Introduction
1.1 Origin and Background of this Research Topic
1.2 Autonomous Robotic Agent
1.2.1 Autonomous Robotic Agent based on Artificial Neural Network
1.2.2 Cognitive Model based on Neurophysiology and Cognitive Science and Robotic Agent
1.3 Motor Control and Internal Model
1.4 The Cerebeller Model
1.4.1 Cerebellar Circuitry
1.4.2 Bio-inspired Computational Cerebellar Model
1.5 Delay and Predictor in Biological Systems
1.5.1 Delay
1.5.2 Kalman Filter
1.5.3 Smith Predictor
1.6 Outline of This Thesis
Chapter 2: An Analysis to Human Balance Control
2.1 Human Balance Control
2.2 Simple model of human body control
2.2.1 System Modeling
2.2.2 Controllers
2.3 Conclusion
Chapter 3: Internal Predictive Model in Cerebellum
3.1 Cerebellum Function
3.1.1 Functional Microcircuity in Cerebellar Cortex
3.1.2 Afferent and Efferent of Cerebellum
3.2 Neural Network
3.2.1 Two-layer Network
3.2.2 Neural Network Training
3.3 Internal Model in Cerebellum
3.3.1 Inverse Model
3.3.2 Forward Model
3.3.3 Prediction in Cerebellum
3.4 Internal Predictive Model
3.5 Conclusion
Chapter 4: A Cerebellar Model Based on Kalman Estimator
4.1 An Introduction to Kalman Estimator
4.2 Kalman Estimator in Cerebellum
4.2.1 Biological Structure of the Cerebellar Model based on Kalman Estimator
4.2.2 Principle of Kalman Estimator
4.3 The Scheme for the Cerebellar Model based on Kalman Estimator
4.3.1 Current Adaptive Controllers
4.3.2 The Learning Regulation for the New FEL Scheme
4.3.3 Motor Learning with an Online Neural Learning
4.4 Simulation and Experimental Results
4.4.1 Task One: Balance Task
4.4.2 Task Two: Robustness Experiment
4.5 Conclusion
Chapter 5: A Cerebellar Model based on Smith Predictor
5.1 An introduction to Smith predictor
5.2 Smith Predictor in Cerebellum
5.2.1 The Scheme for the Cerebellar Model based on Smith Predictor
5.2.2 Motor Learning in Forward Models
5.3 Simulation and Experimental Results
5.3.1 Simulation Examples
5.3.2 Experimental Results with Inverted Pendulum
5.4 Discussion
5.5 Conclusion
Summary and Suggestions for Future Work
Reference
攻读硕士学位期间所发表的学术论文
致谢
