The Flexible Two-Wheeled Self-balancing Robot Based on Hopfield

Authors:
Xian-Gang Ruan;Jianwei Zhao
Affiliations:
Institute of Artificial Intelligence and Robots, Beijing University of Technology, Beijing, China 100124;Institute of Artificial Intelligence and Robots, Beijing University of Technology, Beijing, China 100124
Venue:
ICIRA '09 Proceedings of the 2nd International Conference on Intelligent Robotics and Applications
Year:
2009

Citing 3
Cited 0

Visual Attention and Learning of a Cognitive Robot

ICANN '97 Proceedings of the 7th International Conference on Artificial Neural Networks
Dynamic Analysis of a Nonholonomic Two-Wheeled Inverted Pendulum Robot

Journal of Intelligent and Robotic Systems
Linear Hopfield networks and constrained optimization

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

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Abstract

The linear model of flexible two-wheeled self-balancing robot that has been proved is used in the paper. The lumbar of robot is the spring. The discrete Hopfield neural network is used for controlling robot's posture based on association study. Study of biological control method to realize flexible robot posture control in the adaptive, self-organizing capacity, the reasonable energy function is defined for the non-linear and strong coupling robot, then design the Hopfield controller, used the dynamic function of flexible robot, which satisfied the need of robot's dynamic process. Analyze the convergence of the controller. Simulation experiments show the effectiveness of the method and proved the stability of system. Validity and rationality of the system controller designed are verified through the performance experiments of the prototype and analyzed the experiment result in detail. The robot like the human being not only structure, but also physiological intelligence.