关键词：光机电；机器人；小脑；电机控制；仿真
摘 要：The cerebellum has long been thought to play a crucial role in the forming of graceful movements,and it is viewed as a set of modules,each of which can be added to a control system to improve smooth coordinated movement,with improvements continuing and improving over time.The present paper proposes a new feedback error learning scheme for tracing in motor control system.In the scheme,the model of cerebellar cortex is regarded as the feedforward controller.Specifically,a neural network and an estimator are adopted in the cerebellar cortex model which can predict the future state and eliminate faults caused by time delay.The limits of achievable temporal accuracy in feedback-error learning are investigated experimentally and it is shown that motor output can have better temporal resolution than the error signal which is used for adapting the predictive controller.Finally,the algorithm is demonstrated in a simple but demanding simulated robot-control task.