Contraction Region Estimate for State-Dependent Riccati Equation-Based Controllers and its Application to a Two-Wheeled Inverted Pendulum

Julio Pérez, Susanne Junghans
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引用次数: 1

Abstract

The state–dependent Riccati equation (SDRE) offers a systematic technique for controller design applicable to a wide range of nonlinear processes, especially to complex systems of higher order with inherently fast dynamics. Despite the numerous benefits of the SDRE technique, an open issue remains in providing stability regions for the regulated system as the closed-loop dynamics are not explicitly known. Standard techniques, such as Lyapunov’s direct method, do not allow to infer global properties from local analysis. However, the recently developed contraction theory enables the study of closed-loop dynamics exclusively known pointwisely, which suggests its applicability to SDRE-controlled systems. Thus, this paper presents a novel technique for computing contraction region estimates for nonlinear stabilisation using SDRE-based controllers. By solving an optimisation problem, the region estimate is generated by a smooth Riemannian metric which assures exponential convergence towards the origin. Moreover, a guaranteed lower bound of the contraction rate is explicitly given. To highlight the benefits of the proposed method, numerical simulations of a Two-wheeled inverted pendulum (TWIP) robot are provided. Thus, this paper presents a novel technique for computing contraction region estimates for nonlinear stabilisation using SDRE-based controllers. By solving an optimisation problem, the region estimate is generated by a smooth Riemannian metric which assures exponential convergence towards the origin. Moreover, a guaranteed lower bound of the contraction rate is explicitly given. To highlight the benefits of the proposed method, numerical simulations of a Two-wheeled inverted pendulum (TWIP) robot are provided.
状态相关Riccati方程控制器的收缩域估计及其在两轮倒立摆上的应用
状态相关Riccati方程(SDRE)提供了一种系统的控制器设计技术,适用于广泛的非线性过程,特别是具有固有快速动力学的高阶复杂系统。尽管SDRE技术有许多好处,但由于闭环动力学尚不明确,因此在为受调节系统提供稳定区域方面仍然存在一个悬而未决的问题。标准技术,如Lyapunov的直接方法,不允许从局部分析推断全局属性。然而,最近发展的收缩理论使闭环动力学的研究只知道点,这表明它适用于sre控制系统。因此,本文提出了一种利用基于sre的控制器计算非线性稳定的收缩区域估计的新技术。通过求解优化问题,区域估计由光滑黎曼度量生成,该度量保证了向原点的指数收敛。此外,还明确给出了收缩率的保证下界。为了突出该方法的优点,给出了两轮倒立摆(TWIP)机器人的数值模拟。因此,本文提出了一种利用基于sre的控制器计算非线性稳定的收缩区域估计的新技术。通过求解优化问题,区域估计由光滑黎曼度量生成,该度量保证了向原点的指数收敛。此外,还明确给出了收缩率的保证下界。为了突出该方法的优点,给出了两轮倒立摆(TWIP)机器人的数值模拟。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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