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Development of a Fuzzy Sliding Mode Controller with adaptive tuning technique for a MRI guided robot in the human vasculature

机译:具有自适应调整技术的模糊滑模控制器的开发,用于人体血管系统中的MRI引导机器人

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The concept of using a Magnetic Resonance Imaging (MRI) device for chemotherapy, by employing a micro robot, consisting of a polymer bound aggregate of ferromagnetic particles, is explored in this paper. We primarily contribute towards the design of a Fuzzy Sliding Mode Controller (FSMC) for trajectory tracking of the micro robot in the human vasculature considering a highly non-linear model available in literature. An adaptive algorithm based on Lyapunov stability theory is used to estimate the parameters associated with the FSMC. The proposed FSMC is able to eliminate the chattering phenomenon completely which is present in conventional sliding mode control. Since the system in consideration is a biological one, many parameters are difficult to estimate resulting in parametric uncertainties. A significant merit of the proposed framework is its ability to estimate the dielectric density of blood on-line with great accuracy. Simulation results also indicate perfect tracking with very fast dynamical response. To illustrate the efficacy of our controller, a detailed comparison is made between the performances of a state-of-the-art adaptive backstepping control and our proposed control action in the presence of bounded model uncertainties for micro-robots made up of different ferromagnetic materials.
机译:本文探讨了通过使用微型机器人(由聚合物结合的铁磁颗粒聚集体组成)来使用磁共振成像(MRI)装置进行化学疗法的概念。考虑到文献中存在的高度非线性模型,我们主要致力于模糊滑模控制器(FSMC)的设计,以对人体脉管系统中的微型机器人进行轨迹跟踪。使用基于Lyapunov稳定性理论的自适应算法来估计与FSMC相关的参数。所提出的FSMC能够完全消除常规滑模控制中存在的颤振现象。由于所考虑的系统是生物系统,因此难以估计许多参数,从而导致参数不确定性。所提出的框架的显着优点是其能够以很高的精度估计在线血液的介电密度的能力。仿真结果还表明,具有非常快速的动态响应的完美跟踪。为了说明我们控制器的功效,在由不同铁磁材料构成的微型机器人存在有限模型不确定性的情况下,将最新的自适应反推控制的性能与我们提出的控制动作进行了详细的比较。 。

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