A novel motor learning method is present based on the cooperation of the cerebellum and basal ganglia for the behavior learning of agent. The motor learning method derives from the principle of CNS and operant learnin...A novel motor learning method is present based on the cooperation of the cerebellum and basal ganglia for the behavior learning of agent. The motor learning method derives from the principle of CNS and operant learning mechanism and it depends on the interactions between the basal ganglia and cerebellum. The whole learning system is composed of evaluation mechanism, action selection mechanism, tropism mechanism. The learning signals come from not only the Inferior Olive but also the Substantia Nigra in the beginning. The speed of learning is increased as well as the failure time is reduced with the cerebellum as a supervisor. Convergence can be guaranteed in the sense of entropy. With the proposed motor learning method, a motor learning system for the self-balancing two-wheeled robot has been built using the RBF neural networks as the actor and evaluation function approximator. The simulation experiments showed that the proposed motor learning system achieved a better learning effect, so the motor learning based on the coordination of cerebellum and basal ganglia is effective.展开更多
This study mainly concerns a motion model and the main control algorithm of two-wheel self-balancing vehicle models.Details of the critical parameters fetching and output value of two-wheel self-balancing vehicle mode...This study mainly concerns a motion model and the main control algorithm of two-wheel self-balancing vehicle models.Details of the critical parameters fetching and output value of two-wheel self-balancing vehicle models are introduced,including those concerning balance control,speed control and direction control.An improved cascade coupling control scheme is proposed for two-wheel vehicles,based on a proportional-integral-derivative(PID)control algorithm.Moreover,a thorough comparison between a classic control system and the improved system is provided,and all aspects thereof are analyzed.It is determined that the control performance of the two-wheel self-balancing vehicle system based on the PID control algorithm is reliable,enabling the vehicle body to maintain balance while moving smoothly along a road at a fast average speed with better practical per-formance.展开更多
文摘A novel motor learning method is present based on the cooperation of the cerebellum and basal ganglia for the behavior learning of agent. The motor learning method derives from the principle of CNS and operant learning mechanism and it depends on the interactions between the basal ganglia and cerebellum. The whole learning system is composed of evaluation mechanism, action selection mechanism, tropism mechanism. The learning signals come from not only the Inferior Olive but also the Substantia Nigra in the beginning. The speed of learning is increased as well as the failure time is reduced with the cerebellum as a supervisor. Convergence can be guaranteed in the sense of entropy. With the proposed motor learning method, a motor learning system for the self-balancing two-wheeled robot has been built using the RBF neural networks as the actor and evaluation function approximator. The simulation experiments showed that the proposed motor learning system achieved a better learning effect, so the motor learning based on the coordination of cerebellum and basal ganglia is effective.
文摘This study mainly concerns a motion model and the main control algorithm of two-wheel self-balancing vehicle models.Details of the critical parameters fetching and output value of two-wheel self-balancing vehicle models are introduced,including those concerning balance control,speed control and direction control.An improved cascade coupling control scheme is proposed for two-wheel vehicles,based on a proportional-integral-derivative(PID)control algorithm.Moreover,a thorough comparison between a classic control system and the improved system is provided,and all aspects thereof are analyzed.It is determined that the control performance of the two-wheel self-balancing vehicle system based on the PID control algorithm is reliable,enabling the vehicle body to maintain balance while moving smoothly along a road at a fast average speed with better practical per-formance.
