摘要
在两轮自平衡机器人系统的平衡控制中,为解决因所建立的数学模型不准确和存在未知干扰而影响控制性能的问题,设计了一种自适应模糊控制方法;首先,运用牛顿力学法建立了系统在斜坡上运动的数学模型;基于所建立的非线性动态模型,采用单点模糊化、乘积推理机和中心平均解模糊化的方法构建了自适应模糊逻辑控制器,然后通过李雅普诺夫稳定性分析的方法,导出控制器的自适应律;对自适应模糊控制的两轮自平衡机器人的平衡情况进行了仿真,结果表明,提出的自适应模糊控制器可以实现系统平衡,并具有自适应能力和鲁棒性。
In the dynamic balancing control of two wheeled self--balancing robot, to solve the question that the inaccuracy of established model and the existence of unknown disturbance affect the performance of controller, a kind of adaptive fuzzy control method was investigated. The dynamic math model of robot on the slope was established firstly by Newton＇ s law. On the basis of the established nonlinear dynamic model, the adaptive fuzzy controller was constructed with singleton fuzzier, product inference and center--average defuzzier. The adaptive law was deduced by Lyapunov＇ s stability theory. The simulation of balancing control of two wheeled self--balancing robot under the control of adaptive fuzzy controller was carried in Matlab/simulink. The results show that the proposed adaptive fuzzy controller can make the system stable, and has adaptive capacity and robustness.
出处
《计算机测量与控制》
2015年第3期773-776,共4页
Computer Measurement &Control
基金
浙江省教育厅项目(Y201122728)
