一类施加单向控制量的不确定非线性系统的重复学习控制

发布时间：2018-11-23 21:23

【摘要】：针对存在有界的、周期变化的非线性不确定动态的二阶系统,提出一种使系统渐近地跟踪目标轨迹的控制律。考虑仅能施加单向控制量的系统,所提出的控制律利用饱和函数和基于在线学习的估计器相结合来学习和估计未知非线性动态特性,并对未知动态进行补偿以保证系统跟踪误差渐近收敛于零。同时引入自适应陷波滤波器(Adaptive notch filter,ANF)来在线估计未知非线性动态特性的频率。不同于以前的方法,提出的基于ANF的饱和改进型重复控制律只需要未知动态特性是有界的(未知动态特性的结构、参数、频率是不需要预先知道的)。最后将此控制律应用到只能提供竖直向上电磁力的EMS型磁悬浮系统中,设计出适合磁悬浮系统的控制策略。仿真结果证明了所提出的控制策略的有效性。
[Abstract]:For the second order systems with bounded and periodic nonlinear uncertain dynamics, a control law is proposed to enable the system to track the target trajectory asymptotically. The proposed control law combines the saturation function and the on-line learning estimator to study and estimate the unknown nonlinear dynamic characteristics. The unknown dynamics are compensated to ensure that the tracking error of the system converges to zero asymptotically. At the same time, adaptive notch filter (Adaptive notch filter,ANF) is introduced to estimate the frequency of unknown nonlinear dynamic characteristics online. Different from the previous methods, the proposed saturated modified repetitive control law based on ANF only needs the unknown dynamic characteristics to be bounded (the structure of the unknown dynamic characteristics, the parameters and the frequency are not known in advance). Finally, the control law is applied to the EMS maglev system, which can only provide vertical upward electromagnetic force, and the control strategy suitable for the maglev system is designed. Simulation results show the effectiveness of the proposed control strategy.
【作者单位】：同济大学机械与能源工程学院;同济大学国家磁浮交通工程技术研究中心;
【基金】：国家科技支撑计划(2013BAG19B00-01) “十二五”国家科技支撑计划(2011BAJ02B00)资助项目
【分类号】：TP13

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