基于指令滤波与观测器的柔性机械臂跟踪控制

Tracking Control of Flexible Manipulator Based on Command Filtering and Observer

针对复杂工况下单连杆柔性机械臂(single-link flexible manipulator, SLFM)系统的轨迹跟踪控制问题,提出了一种基于指令滤波与观测器相结合的自适应神经网络控制算法。该算法考虑了SLFM系统的未知外部干扰和未建模动态影响。首先,利用单连杆柔性机械臂机理参数间的物理关系构建了其分数阶动力学模型,通过引入全局坐标变换将其转化为严格反馈控制系统;其次,针对SLFM系统状态不完全可测问题,构建了基于神经网络的分数阶状态观测器,并证明了其有效性;然后,利用观测信息设计了SLFM系统的轨迹跟踪控制算法,同时为了克服高阶求导导致的控制误差,提出了基于指令滤波的反步控制机制。理论分析表明,提出的控制方法可以保证闭环系统信号的半全局一致性与有界性;最后,通过数值仿真验证了所提控制方法的可行性和有效性。

To address the tracking control problem of a single-link flexible manipulator system under complex conditions,an adaptive neural network control algorithm based on command filtering and observer is proposed.The algorithm takes unknown external disturbances and unmodeled dynamics of SLFM system into account.First,a fractional-order dynamic model is constructed based on the physical relationship between the mechanism parameters of the single-link flexible manipulator,and the global coordinate transformation is introduced to transform the system into a strict feedback control system.Secondly,a fractional-order state observer based on neural network is constructed to solve the problem of incomplete state measurement of the SLFM system,and its effectiveness is proved.Furthermore,the trajectory tracking control algorithm of the SLFM system is designed by using the observation information.In order to overcome the control error caused by high order derivation,a backstepping control mechanism based on command filtering is proposed in this algorithm.Theoretical analysis shows that the control method proposed can ensure the semi-global consistency and boundedness of the closed-loop system signal.Finally,the feasibility and effectiveness of the proposed control method are verified by numerical simulation.