Robust Laguerre based model predictive control for trajectory tracking of LTV systems

Marzieh Jamalabadi, M. Naraghi, I. Sharifi, Elnaz Firouzmand
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Abstract

In this paper, the trajectory tracking of a nonholonomic and linear time-varying (LTV) mobile robot is studied. The slippery surface condition is a source of uncertainty for this constrained mobile robot and is modeled as a bounded additive disturbance. The primary objective is to design a robust model predictive control based on Laguerre functions utilizing the tubes' theory. The system's time-varying dynamic results in generating time-varying tubes and increasing the operation time. To tackle this challenge, some offline calculations are performed to guarantee the control algorithm's real-time operation, ensuring satisfactory performance and stability. Two controllers were designed. In the first case, the designing inputs changed through the execution time, while the other controller was just designed for the specifically chosen dynamic. Illustrative simulations are presented to show the applicability of the proposed method.
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LTV系统轨迹跟踪的鲁棒拉盖尔模型预测控制
研究了非完整线性时变移动机器人的轨迹跟踪问题。光滑的表面条件是该受限移动机器人的不确定性来源,并被建模为有界加性扰动。主要目标是利用管理论设计基于拉盖尔函数的鲁棒模型预测控制。系统的时变动态导致系统产生时变管,增加了系统运行时间。为了解决这一挑战,进行了一些离线计算,以保证控制算法的实时运行,确保令人满意的性能和稳定性。设计了两个控制器。在第一种情况下,设计输入随着执行时间的变化而变化,而另一种控制器只是针对特定选择的动态而设计。通过实例仿真验证了所提方法的适用性。
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