Abstract
The aim of this paper is to implement a novel finite-time feedback linearization (FTFL) controller considering optimal gains on mobile manipulators with differential wheels theoretically and experimentally. To achieve the finite time constraint, optimal gains are obtained from solving the state dependent differential Riccati equation in a time varying dynamic system. Yet, unlike other works, using input-output linearization, the outcome of state dependent coefficient (SDC) parametrization is a couple of linear matrices. This helps the microcontroller to control the process in real time and very quick. Conceiving holonomic and non-holonomic constraints, mobile manipulator dynamic is derived. In addition, due to the fact that it is shown the proposed dynamic is not input-state linearizable, both the FTFL and state dependent Riccati equation (SDRE) are applied on the dynamic system using output feedback strategy and stability analyses are done based on lyapunov principle. Moreover, point-to-point motion and trajectory tracking simulations depict advantages of applying the FTFL method over other nonlinear schemes including sliding mode control (SMC), conventional feedback linearization, SDRE, and finite time SDRE on both the mobile manipulator and wheeled base systems. In addition, certain analysis regarding the look ahead positions and dynamic parameters are carried out to show the superiority of FTFL. Finally, the obtained results are validated by experimental setup of a mobile manipulator (Scout robot).
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Korayem, M.H., Nekoo, S.R. & Kazemi, S. Finite-Time Feedback Linearization (FTFL) Controller Considering Optimal Gains on Mobile Mechanical Manipulators. J Intell Robot Syst 94, 727–744 (2019). https://doi.org/10.1007/s10846-018-0911-8
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DOI: https://doi.org/10.1007/s10846-018-0911-8