中文摘要：

针对小脑在运动中学习控制的角色问题,提出了一种为到达指定目标可以学会产生运动信号的肢体运动控制小脑学习模型,该模型由一个小脑学习模块以及硬连线外小脑系统构成,用以控制一个模拟的、由6块肌肉所驱动的双关节手臂。其中,小脑学习模块由1组可调式模式产生器的独立子模块构成;外小脑系统负责在小脑模块不能引导手臂到达指定目标的情况下产生精度较低的矫正运动,通过本体输入,模型的下橄榄通过观察由外小脑系统产生的矫正运动来推断小脑产生的运动误差,以期达到对手臂运动的调节和控制,仿真结果表明,该小脑模型具有较好的理想轨迹跟踪性能。

英文摘要：

The paper presents a model of cerebellar control that can learn to produce motor signals in a muscle synergy space for the purposes of reaching a specified target. The model consists of a learning celrebellar module and a hard-wired extra-cerebellar （EC） system. The model is used to control a simulated two-joint arm, which is actuated by a set of six muscles. In the model, the cerebellar module consists of a group inde- pendent submodules, referred to Adjustable Pattern Generators（APG） ; and the EC system is responsible for producing low-quality corrective movements in situations where the cerebellar module is unable to bring the arm to the specified target. Via proprioceptive inputs, the inferior olive of the model assesses directional error in cerebellar-generated movements by observing subsequent corrective movements produced by the EC system. The simulation results demonstrate that this cerebellar model has better tracing performance of desired trajectory.