摘要
针对转台伺服系统中周期性波动力矩扰动抑制问题,利用重复控制算法能以十分简单的控制器形式高精确度地完成跟踪或抑制周期性参考信号或扰动信号的优点,提出了一种基于扰动观测器的鲁棒学习控制算法。给出了基于扰动观测器的转台伺服系统结构图,并将重复控算法引入到基于扰动观测器的扰动补偿策略中。L2稳定性定理证明该方法保证了闭环系统的稳定性和对期望信号的渐近跟踪;仿真结果也表明,该方法较传统方法既有效地抑制了系统周期性波动力矩,又提高了系统运动曲线的跟踪性能。
A robust learning control algorithm based on disturbance-observer is proposed for reducing periodical ripple moment in turntable servo system by the advantage of repetitive control algorithm that repetitive control algorithm can track or restrain precisely periodical reference signal or disturbance signal in the simple controller form. First, the structure of system based on the disturbance-observer is offered and repetitive control algorithm is added into the disturbance-observer based on disturbance compensation scheme. Then, the system stability and the uniformly ultimate position tracking performance are guaranteed by L2 stability theorem. Finally, Computer simulations verify that the proposed scheme constrains effectively periodical ripple moment and improves tracking performance in the system.
出处
《电机与控制学报》
EI
CSCD
北大核心
2007年第5期508-511,共4页
Electric Machines and Control
基金
武器装备预研基金(5145400204HT01)
关键词
重复控制
转台
伺服系统
周期性波动力矩
跟踪性能
repetitive control
turntable
servo system
periodical ripple moment
tracking performance