ニューラルダイナミクスに基づく移動マニピュレータのモデル予測制御（拡張版）
Model Predictive Control For Mobile Manipulators Based On Neural Dynamics(Extended version)
移動マニピュレータの軌道追従問題に対し、位置・姿勢のモデル予測制御と有限時間収束ニューラルダイナミクス、非特異高速終端スライディングモード制御を組み合わせた手法を提案し、シミュレーションと実験で有効性を示した。
著者: Tao Su, Shiqi Zheng
分類: cs.RO, cs.SY, eess.SY
原文アブストラクト
This article focuses on the trajectory tracking problem of mobile manipulators (MMs). Firstly, we construct a position and orientation model predictive tracking control (POMPTC) scheme for mobile manipulators. The proposed POMPTC scheme can simultaneously minimize the tracking error, joint velocity, and joint acceleration. Moreover, it can achieve synchronous control for the position and orientation of the end-effector. Secondly, a finite-time convergent neural dynamics (FTCND) model is constructed to find the optimal solution of the POMPTC scheme. Then, based on the proposed POMPTC scheme, a non-singular fast terminal sliding model (NFTSM) control method is presented, which considers the disturbances caused by the base motion on the manipulator at the dynamic level. It can achieve finite-time tracking performance and improve the anti-disturbances ability. Finally, simulation and experiments show that the proposed control method has the advantages of strong robustness, fast convergence, and high control accuracy.