伺服系统的复合自适应滑模控制

对于采用自适应方法的鲁棒跟踪控制系统,初始参数估计误差、参数突变、非持续激励等因素均可引起瞬态过程.瞬态性能的好坏对跟踪误差峰值及恢复时间有较大影响,是实现高性能跟踪控制的关键,而目前典型设计多采用直接自适应方法,其较差的瞬态特性制约了跟踪性能的进一步提高.针对该问题,以交流伺服系统为研究对象,将直接自适应、间接自适应及滑模控制相融合,提出一种基于有界增益遗忘最小二乘法的复合自适应滑模控制( CASMC)策略,Lyapunov分析表明该策略可实现持续激励条件下跟踪误差和参数估计误差在较大范围内的指数收敛,瞬态特性较清晰.最后,以某型火炮的方位轴伺服系统为应用背景进行仿真实验,结果显示,该控制策略在瞬态过程的误差峰值和持续时间方面均有显著改善,提高了伺服系统的跟踪性能.

Composite Adaptive Sliding Mode Control for Servo Systems

For adaptive robust tracking control systems,initial parameters estimation error,sudden change in the parameter values and non - persistent - excitation all can lead to transient processes.Thus,better transient response,which means smaller peak error and faster recovery,is very important for achieving high performance tracking control.At present,however,most of the control designs are based on the direct adaptive methods,which limit the tracking performance that can be achieved.This paper proposes a composite adaptive sliding mode control strategy based on Bounded - Gain - Forgetting Least - Squares(BGF - LS) method.Lyapunov analysis shows that exponential convergence can be conserved in a large range under persistent excitation,which improves the performance of servo systems effectively.Simulation experiments on an artillery servo system indicate that the proposed method has achieved smaller peak error and faster recovery and improves the performance of servo systems effectively.