Flatness-based control in successive loops for mechatronic motion transmission systems

IF 2.7 4区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS
Gerasimos Rigatos, Jorge Pomares, Pierluigi Siano, Mohammed AL-Numay, Masoud Abbaszadeh, Gennaro Cuccurullo
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引用次数: 0

Abstract

Mechatronic systems with nonlinear dynamics are met in motion transmission applications for vehicles and robots. In this article, the control problem for the nonlinear dynamics of mechatronic motion transmission systems is solved with the use of a flatness-based control approach which is implemented in successive loops. The state-space model of these systems is separated into a series of subsystems, which are connected between them in cascading loops. Each one of these subsystems can be viewed independently as a differentially flat system, and control about it can be performed with inversion of its dynamics as in the case of input–output linearized flat systems. In this chain of i = 1 , 2 , , N $$ i&amp;amp;#x0003D;1,2,\dots, N $$ subsystems, the state variables of the subsequent ( i + 1 $$ i&amp;amp;#x0002B;1 $$ )-th subsystem become virtual control inputs for the preceding i $$ i $$ -th subsystem and so on. In turn, exogenous control inputs are applied to the last subsystem and are computed by tracing backwards the virtual control inputs of the preceding N 1 $$ N-1 $$ subsystems. The whole control method is implemented in successive loops, and its global stability properties are also proven through Lyapunov stability analysis. The validity of the control method is confirmed in the following two case studies: (a) control of a permanent magnet linear synchronous motor (PMLSM)-actuated vehicle's clutch and (ii) control of a multi-Degrees of Freedom (multi-DOF) flexible joint robot.

机电运动传动系统连续回路中基于平坦度的控制
在车辆和机器人的运动传输应用中,会遇到具有非线性动态特性的机电一体化系统。在本文中,机电运动传输系统的非线性动力学控制问题是通过使用基于平面度的控制方法来解决的,该方法在连续回路中实施。这些系统的状态空间模型被分为一系列子系统,子系统之间通过级联回路相连。这些子系统中的每一个都可以独立地看作是一个差分平面系统,对其进行控制时,可以像输入输出线性化平面系统那样,对其动态进行反演。在这个由 i=1,2,...,N$$ i&amp;#x0003D;1,2,\dots, N $子系统组成的链中,后面(i+1$$ i&amp;#x0002B;1 $$)-th子系统的状态变量成为前面 i$$ i $$-th子系统的虚拟控制输入,以此类推。反过来,外源控制输入应用于最后一个子系统,并通过向后追踪前 N-1$$ N-1$ 子系统的虚拟控制输入来计算。整个控制方法是在连续循环中实现的,其全局稳定性也通过 Lyapunov 稳定性分析得到了证明。控制方法的有效性在以下两个案例研究中得到了证实:(a) 永磁线性同步电机(PMLSM)驱动车辆离合器的控制;(ii) 多自由度(multi-DOF)柔性关节机器人的控制。
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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来源期刊
Asian Journal of Control
Asian Journal of Control 工程技术-自动化与控制系统
CiteScore
4.80
自引率
25.00%
发文量
253
审稿时长
7.2 months
期刊介绍: The Asian Journal of Control, an Asian Control Association (ACA) and Chinese Automatic Control Society (CACS) affiliated journal, is the first international journal originating from the Asia Pacific region. The Asian Journal of Control publishes papers on original theoretical and practical research and developments in the areas of control, involving all facets of control theory and its application. Published six times a year, the Journal aims to be a key platform for control communities throughout the world. The Journal provides a forum where control researchers and practitioners can exchange knowledge and experiences on the latest advances in the control areas, and plays an educational role for students and experienced researchers in other disciplines interested in this continually growing field. The scope of the journal is extensive. Topics include: The theory and design of control systems and components, encompassing: Robust and distributed control using geometric, optimal, stochastic and nonlinear methods Game theory and state estimation Adaptive control, including neural networks, learning, parameter estimation and system fault detection Artificial intelligence, fuzzy and expert systems Hierarchical and man-machine systems All parts of systems engineering which consider the reliability of components and systems Emerging application areas, such as: Robotics Mechatronics Computers for computer-aided design, manufacturing, and control of various industrial processes Space vehicles and aircraft, ships, and traffic Biomedical systems National economies Power systems Agriculture Natural resources.
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