中文摘要：

两轮机器人是一个典型的不稳定，非线性，强耦合的自平衡系统，在两轮机器人系统模型未知和没有先验经验的条件下，将强化学习算法和模糊神经网络有效结合，保证了函数逼近的快速性和收敛性，成功地实现两轮机器人的自学习平衡控制，并解决了两轮机器人连续状态空间和动作空间的强化学习问题；仿真和实验表明：该方法不仅在很短的时间内成功地完成对两轮机器人的平衡控制，而且在两轮机器人参数变化较大时，仍能维持两轮机器人的平衡。

英文摘要：

Two--wheeled robot is a non--stable, non--linear, strong coupling system. This paper present a novel method to control the balance of a two--wheeled robot by using reinforcement learning and fuzzy neural networks which can guarantees the convergence and rapidity when the model of the robot is not available and the agent has no prior knowledge. It also can effectively control the task of continuous states and actions. The simulation and experiment results demonstrate that it can learn to control the two--wheeled robot system in a short time.