【摘要】 针对两轮自平衡机器人的运动平衡问题,提出了一种基于模糊自适应控制算法的自主学习方法,能够在线识别机器人模糊模型,检测机器人参数变化以及跟踪参数随时间变化的特性,利用机器人模型与期望性能指标设计出模糊控制器,构建了基于模糊自适应算法的自主学习方法,并从理论上证明了算法的稳定性。仿真结果表明,所提自主学习算法能在机器人偏离垂直位置较大角度时,实现机器人直立平衡和速度跟踪,并与传统PID控制方法相比,消除了机器人各状态响应的抖动现象,具有较高的动态响应和稳态精度,体现了算法的有效性和可行性。更多还原

【Abstract】 In view of the movement balance problems about the two- wheeled self- balance robot,an autonomic learning fuzzy adaptive algorithm was presented. This method can identify the fuzzy model of the robot online,and detect the parameter variation of the robot and track its characteristics about the parameter variation over time. This paper used the model and the expected performance index of the robot to design a fuzzy controller,so that the autonomous learning method based on the fuzzy adaptive algorithm was formed. And the algorithm was proved theoretically.The simulation results show that the learning algorithm can realize the standing balance and speed tracking of the robot,in the case of deviating from a larger angle to the vertical position. Compared with the traditional PID control method,this method eliminates the chattering phenomena of each state response about the robot,and has higher dynamic response and steady accuracy,and verifies the effectiveness and feasibility.更多还原