Tracking Control of Flexible Manipulator Based on Command Filtering and Observer
To address the tracking control problem of a single-link flexible manipulator system under com-plex 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 in-to 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.
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